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Exam Code: A00-212 Practice exam 2022 by team
SAS Advanced Programming for SAS 9
SASInstitute Programming course outline
Killexams : SASInstitute Programming course outline - BingNews Search results Killexams : SASInstitute Programming course outline - BingNews Killexams : Best 5 Programming Certifications for IT Pros 2019

Anthropologists reckon that humans around the globe speak somewhere between 6,000 and 7,000 distinct languages, with a number around 6,700 appearing most frequently in online sources. Nobody has conducted an exhaustive survey for all computer programming languages in use around the world, but there are focused studies available.

These studies include the U.S. Department of Defense Survey of Computing Languages (also known as the DoD Language Survey) conducted in 1995, which identified no fewer than 450 programming languages in use in various weapons and automated information systems in the 1970s, with 37 total languages recounted as part of the 1995 survey of languages in use for weapons systems.

CodeLani estimates that there are somewhere between 500 and 2,000 active general-purpose programming languages out there. The number of all active computer programming languages is estimated to be between 5,000 and 25,000. A number from hundreds to thousands of such languages appears both reasonable and defensible, depending on what types of systems and applications might be under consideration.

In this certification guide, we provide you with our top five programming certifications for IT professionals. These days, computer programming certifications are as much about development platforms and environments as they are about specific programming languages. You’ll find an interesting mix of language-focused or language-specific credentials available, such as C/C++ certifications as well as various platform-oriented credentials like Microsoft’s MCSD certification.

Because many desktop programs are now either universal or web-related apps, programming professionals may want to consider adding web and mobile application development credentials to their portfolios. Numerous excellent certifications and related training materials for web and mobile app developers are available. Some of the certifications discussed here, such as the MCSD, also transfer into certification programs for web or mobile apps.

We performed an informal job search that gives you an idea of the relative frequency with which our top five certifications appear in real job postings.

Job board search results (in alphabetical order, by certification)

Certification SimplyHired Indeed LinkedIn Jobs Linkup Total
C Language Certified Associate 591 707 214 1,660 3,172
Chef Badges (Chef Software)* 1,757 2,530 785 439 5,511
CSSLP [(ISC)2] 284 358 746 219 1,607
MCSD (Microsoft) 445 579 886 237 2,147
PCP (Puppet) 5,906 7,873 12,200 3,317 29,296

*Chef uses a badge certification format, and our search parameter focused on “Chef certified.”

Salaries vary depending on the job role, but, on average, software and application developers can expect to earn something over $85,000. Simply Hired reported average earnings for application developers at almost $85,000 and more than $91,000 for software developers. Earnings on the high side were reported at slightly less than $134,000 ($126,775 for application developers and $139,692 for software developers), with low earnings in the upper-$50,000s. Computer programmers earn slightly less, with average earnings reported at $70,400. Salaries ranged from lows in the mid-$50,000s to $92,077 for top earners.

C and C++ certifications

The programming languages C and C++ have been around for years, making their debut in the 1960s to 1970s (C) and the 1980s to 1990s (C++). Although nearly every college and university in the U.S. offers a C/C++ programming course, the C++ Institute and Pearson VUE decided to carve a niche in this part of the certification landscape by offering the world’s first international C/C++ certifications.

Candidates can choose the C or the C++ path and move up the certification ladder from associate to professional to senior. Of the six potential certifications, four certifications are currently available:

  • CLA: C Programming Language Certified Associate
  • CLP:  C Certified Professional Programmer
  • CPA: C++ Certified Associate Programmer
  • CPP: C++ Certified Professional Programmer

C++ Institute certifications are good for life, because these languages haven’t changed much over the years. But that doesn’t mean there isn’t high demand for such skills. And a C/C++ certification is a perfect steppingstone to many platform- and vendor-specific certs, such as the MCSD.

C/C++ facts and figures

Certification Name C or C++ Associate and Professional C Programming Language Certified Associate (CLA)

C Certified Professional Programmer (CLP)

C++ Certified Associate Programmer (CPA)

C++ Certified Professional Programmer (CPP)

Prerequisites & Required Courses Professional- and senior-level credentials require certification in the lower credential

Recommended: Online courses are free and offer a 50 percent discount on the cost of the exam if you score at least 70 percent on the course exam

Number of Exams One exam per credential (up to 75 minutes, 55 to 65 questions, 80 percent required to pass)

Exams are administered by Pearson VUE

Cost Per Exam   $295 for nonstudents (includes one free retake)

$147.50 if taken in conjunction with the course (which is free)

Retakes are free for candidates who paid full exam price or who completed the CPP course in self-study mode. Retake vouchers must be requested within 30 days after exam fail. Retake vouchers are valid for 45 days

Self-Study Materials C++ Institute maintains links on the respective exam webpage to the exam syllabus, exam objectives, study resources and more. Free online courses are available at the C++ Institute.

Chef-certified badges

As job board numbers demonstrate, there’s strong demand for Chef certified professionals. This earns Chef certifications a well-deserved place on this year’s top five list. All Chef Software certifications are offered in the form of badges, providing professionals flexibility to match skills to emerging technologies and problems. At present, there are five badges:

  • Basic Chef Fluency: An entry-level badge that includes basic chef terminology, describing Chef concepts and features, design philosophy, workflow basics and basic Chef code.
  • Local Cookbook Deployment: The exam is available in Windows or Linux environments, and covers search and data bags, troubleshooting, testing frameworks, Cookbook components, test kitchens, Chef DK tools, and authoring and setup theory for Cookbooks. Candidates should be able to develop a basic Chef Cookbook and automate existing processes with Chef recipes.
  • Extending Chef: Extending Chef badge holders can add extended features and functionality, customize Chef, use Ohai and write custom Ruby classes. exam Topics include extending Ohai, custom resources, Chef handlers, definitions and handlers, Knife plugins, CHEP API, and basic Ruby.
  • Deploying Cookbooks: This badge targets professionals who are proficient managing nodes and deploying Chef recipes. exam Topics include Chef Run anatomy, uploading Cookbooks to Chef Server, using Knife, bootstrapping, Chef Solo, Policy Files, search, Data Bags, roles and environments.
  • Auditing with InSpec: A successful candidate will possess in-depth knowledge of InSpec core principles and is able to execute InSpec in remote and local environments. The exam covers installing and running InSpec, InSpec profiles, troubleshooting, and InSpec controls and metadata.

All badges are good for three years.

Chef facts and figures

Certification Name Basic Chef Fluency

Local Cookbook Development

Extending Chef

Deploying Cookbooks

Auditing with InSpec

Prerequisites & Required Courses None, but training is highly recommended
Number of Exams One exam per badge

Basic Chef Fluency exam is 60 minutes; all other exams are 90 minutes. All exams consist of a combination of performance challenges and multiple-choice questions

Cost Per Exam   Basic Chef Fluency exam: $75

All other exams: $99

Self-Study Materials The Learn Chef Rally offers free learning opportunities, including learning tracks, modules and demos. Online instructor-led training is available. Candidates can expect to pay between $495 and $995 depending on the course. In-person training is also available. Community forums, a skills library and other training resources are also available from Chef.

CSSLP: Certified Secure Software Lifecycle Professional

Like other (ISC)2 certifications, the CSSLP is a vendor-neutral credential relevant to many kinds of programming and development projects. Aimed at software developers, engineers, architects, QA and penetration testers, security specialists and the like, the CSSLP recognizes competency in securing applications throughout the software development lifecycle.

The exam covers all phases of this lifecycle, including secure software concepts, requirements, design, implementation and coding, and testing. Candidates should also be up to speed on the eight CSSLP Common Body of Knowledge (CBK) domains which include software concepts, requirements, design, implementation/programming, testing, lifecycle management, deployment, operations and maintenance, along with supply chain and software acquisition.

Interestingly, the CSSLP was the first (ISC)2 exam to be offered through Pearson VUE testing centers, instead of occasional pencil-and-paper testing at various scheduled and proctored testing sites globally. As such, this certification has done a lot to bring (ISC)2 into the 21st century, cert-wise. According to (ISC)2, the CSSLP is the only credential that currently emphasizes building security into the software development lifecycle phases and inclusion of best practices.

CSSLP facts and figures

Certification Name Certified Secure Software Lifecycle Professional (CSSLP)
Prerequisites & Required Courses At least four years’ full-time work-related experience in the software development lifecycle (SDLC) in at least one of the eight CSSLP domains, or three years’ experience plus a bachelor’s degree or equivalent in an IT-related field such as computer science or information technology

Passing score on the CSSLP exam

Endorsement from (ISC)2 active member within nine months of exam completion

Recertification is required every three years via 90 credits of continuing professional education (CPE); must earn 30 CPE credits each year; annual maintenance fee is $100

Number of Exams One (four hours, 175 questions, 700 out of 1,000 points required to pass)

Exam administered by Pearson VUE

Cost Per Exam   $599
Self-Study Materials The certification webpage maintains links to multiple study tools, including exam outlines, textbooks, glossaries, study guides, interactive flashcards and training seminars.

Third-party certification prep materials are available at Amazon and other retailers.

MCSD App Builder: Microsoft Certified Solutions Developer App Builder

The Microsoft Certified Solutions Developer is Microsoft’s prevailing certification for programmers and application developers. Microsoft professionals are probably most familiar with its five former MCSD credentials: Web Applications, SharePoint Applications, Azure Solutions Architect, Application Lifecycle Management and Universal Windows Platform.

Microsoft revamped its MCSD certification program in September 2016 to more closely align with technical requirements commonly used by the Microsoft Partner Network. Most MCSD credentials are now retired. The MCSD: Azure Solutions Architect was replaced by the MCSE: Cloud and Platform Infrastructure credential. All other MCSD credentials (Web Applications, SharePoint Applications, Application Lifecycle Management and Universal Windows Platform) have been replaced by the MCSD: App Builder credential discussed here.

MCSD: App Builder focuses on application developers and validates a candidate’s knowledge and the technical skills necessary to build web services, web applications and mobile apps. To earn this credential, candidates must first obtain either the Microsoft Certified Solutions Associate (MCSA): Web Applications or MCSA: Universal Windows Platform certification. Then candidates must pass one MCSD elective exam. Currently, elective exams include concentrations in the following areas:

  • Microsoft Azure (developing solutions, architecting solutions, and developing Azure and web services)
  • Microsoft Visual Studio (administering team foundation servers, software testing and application lifecycle management)

Recertification is not required for the MCSD: App Builder credential. However, candidates may re-earn the credential each year by passing a new elective exam that is added to their transcripts. Microsoft encourages this behavior as a form of constant education or ongoing certification, in fact.

MSCD facts and figures

Certification Name Microsoft Certified Solutions Developer (MCSD): App Builder
Prerequisites & Required Courses Required:

Microsoft Certified Solutions Associate (MCSA): Web Applications or MCSA: Universal Windows Platform (two exams each)


Training recommended but not required

Two to three years’ experience developing solutions using Microsoft development technologies for mobile or web

Number of Exams One MCSD elective exam (choose from the following):

70-357: Developing Mobile Apps

70-480: Programming in HTML5 with JavaScript and CSS3

70-487: Developing Microsoft Azure and Web Services

70-483: Programming in C#

70-486: Developing ASP.NET MVC Web Applications

70-487: Developing Microsoft Azure and Web Services

Cost Per Exam   $165 per exam; prices vary by location outside the U.S.
Self-Study Materials Exam reference materials, including practice tests, instructor-led training, self-paced training kits, Microsoft Press books and Microsoft online resources, are available at Microsoft Learning.

PCP: Puppet Professional 2019 Certification

The Puppet Certified Professional (PCP) first appeared in this roundup in 2017. Founded in 2005 by Luke Kanies, Puppet is best known for its configuration management tool (offered in both open source and commercial formats) and its automation software. Since its inception, Puppet has grown considerably. Its reach now extends to offices not only in the U.S. (Portland, Oregon) but in London, Ireland, Australia and the Czech Republic as well. According to Puppet, more than 35,000 companies use the Puppet tool and software.

The PCP validates a candidate’s technical knowledge and expertise administering systems using Puppet. While there are no formal requirements to earn the PCP, successful candidates should possess an understanding of Puppet documentation and best practices, working with data (developing modules, external sources and data separation), and maintaining OS components.

Candidates should also have hands-on experience using Puppet, and the company highly recommends that candidates take both the Foundation and Practitioner training courses (or possess equivalent skills) before attempting the exam. The cert does not expire, but exams are updated to match the current version of Puppet software. Candidates should plan on recertifying about every 18 months on the newest version of Puppet.

Puppet Professional facts and figures

Certification Name Puppet Professional Certification (PCP)
Prerequisites & Required Courses Familiarity with Puppet documentation, best practices and the Puppet Language Style Guide

Experience working with Puppet automation software and administration of system infrastructure; ability to develop basic modules

Recommended: Puppet Fundamentals and Practitioner training courses or equivalent skills

Number of Exams One: PPT 206 – System Administration Using Puppet (60 questions, 90 minutes)
Cost Per Exam   $200

Exam administered by QuestionMark

Self-Study Materials The certification and exam webpages maintain links to various Puppet docs, the Puppet Language Style Guide, practice exams, the Puppet Enterprise Users Guide, training opportunities (Fundamentals and Practitioner skill level) and more.

Beyond the top 5: More programming certifications

There are lots of other certification programs that can help further the careers and professional development of IT professionals who work as programmers. While the Adobe Certified Expert didn’t make the leader board this year, it is still a credential worth pursuing. The SaltStack Certified Engineer is another powerful automation framework for data center infrastructures and application environments used worldwide.

On the one hand, it makes sense to investigate the plethora of vendor-neutral certification programs available for those who work with specific programming languages or development platforms, particularly those that are open source, like the Zend Framework and Zend PHP, or Ruby on Rails and the Ruby Association’s Certified Ruby Programmer credential. You can also find offerings from providers such as Brainbench and ExpertRating. These and similar organizations offer programmer training and testing on dozens to hundreds of topics, including such white-hot areas as mobile applications development, Android and iOS, and web programming.

In addition, a careful examination of vendor-specific certification programs with broad developer footprints – such as BMC, IBM, SAS, Oracle (Java programming, OCA, OCP, OCM, OCE and more) and Teradata – can also open doors for developers and provide ongoing job or contract opportunities. Those interested in programming certifications have no shortage of choices to make. That’s why we urge candidates to choose carefully and wisely, especially if venturing outside items covered in this article.

Tue, 11 Oct 2022 12:00:00 -0500 en text/html
Killexams : The 11 Best Free Online Coding Courses for Computer Programming © Provided by MUO

Right now, there's an abundance of in-demand programming jobs, and a growing number of free courses to help you land one of them—even without a traditional computer science degree.

To excel in the field of computer programming, you need to know where to look for free computer programming courses, and work with the best on each site. Whether you're a total beginner or a pro looking for free online coding courses with certificates, there's something for you on this list.

MIT OpenCourseWare (OCW) is one of the best free coding courses for beginners. It's incredible for dedicated self-starters, as you can go through them at your own pace.

The courses start from the basics and include all the lectures, slides, and assignments used in the video tutorials. MIT OCW's computer programming courses have introductory lessons on Computer Science and programming in Python along with other languages. Additionally, you can expect plenty of comprehensive material on specific fields like machine learning and electronics.

The introductory ones are split into General Introductions, Follow-Up Courses, and Language-Specific Courses.

To help you get started, here are the best free MIT OCW Programming Courses:

edX provides free college-level online courses, jointly spearheaded by MIT and Harvard University. Not only are the courses available without charge, but the organization itself is also non-profit. So you can rest easy knowing that you won't be exploited by ulterior motives.

Courses on edX can be weekly or self-paced, and you can attend the programming classes online. Subjects span the entire range of Topics you might find at any accredited university, but there's a heavy skew towards Computer Science, Engineering, and Business & Management. They're also divided into Introductory, Intermediate, and Advanced levels for your convenience.

If you want to experience some of the best free coding courses, you should head to edX. The platform offers Certificate Programs, which offer a rich course curriculum that allows mastery in a specific area, like Front-End Web Development or Data Science.

To learn to code online for free, here are some of the top picks for the best free edX Programming courses:

Coursera is a free online course platform backed by Stanford University and venture capitalists. The platform collaborates with various universities and organizations to provide their courses, while earning revenue through its certificate programs.

Coursera focuses on specializations, including sets of courses designed to build your skills in a particular topic; However, it is not as comprehensive as to emulate a full program.

For example, the Data Structures and Algorithms six-course specialization covers Basic Data Structures, Basic Algorithms, Graph Algorithms, String Algorithms, Advanced Algorithms, and Genome Assembly. When it comes to coding for beginners, there’s a lot of variety, whether you’re eyeing software engineering or data science as a future career.

Coursera features a list of free and paid online programming courses. Courses are self-paced but have definite start and end dates, meaning you'll have to go through them as they're available. Today's courses may not be there tomorrow, but new ones may show up in their place. Check out the best Coursera courses worth paying for if you need some ideas.

Here are the best of Coursera's free online coding classes:

Udacity is another online course platform, but unlike MIT OCW, edX, and Coursera, Udacity strictly focuses on Topics related to programming, data science, and engineering. No math, social sciences, or humanities. It's all about technology, and we believe it's arguably better for it.

The goal of Udacity is to prepare you for occupational success in one of its tech-related fields. The platform places a lot of attention on its Nanodegree Programs, which are compact curriculums (usually completed in under a year) designed to get you job-ready as quickly as possible.

Nanodegrees cost anywhere from $100 to $500 each.

Don't want to pay anything? That's fine. You can eschew the whole curriculum-based approach and stick to free computer programming courses. Most of Udacity's free programming courses are basic introductions intended to kick-start learning in a full curriculum environment, so they're not particularly in-depth. You won't become a pro with them, but you'll learn the basics to get you going.

If you're taking coding classes on Udacity, here are some recommendations of the best free coding courses to get you started.

Udemy is an online education marketplace where anyone can create (and even sell) their own courses for others to consume. This is quite the double-edged sword: it allows skilled folks to share their knowledge without an education degree, but you may have to wade through a lot of options to find the perfect fit for yourself.

The programming courses on Udemy span all kinds of topics. You'll find everything from Python-based data crunching to the basics of ethical hacking, from Java fundamentals to master-level web development. You'll also find a lot of courses related to game development.

Note: Never pay full price for a Udemy course! The Udemy marketplace frequently holds massive sales, slashing prices anywhere from 50 to 90 percent off.

While you wait, here are some of the best free Udemy coding classes to get started:

If your goal is to become a proficient web developer, whether front-end or back-end, then you should consider coding classes on Free Code Camp (which primarily teaches HTML, CSS, JavaScript, and React).

You can get certifications by completing courses in various categories from freeCodeCamp's 3000-hour curriculum. freeCodeCamp offers content on Web Design, Quality Assurance, Data Visualization, Machine Learning, and other additional topics.

If you want to know more about Agile/Scrum methodologies, you can enroll in some related courses on Free Code Camp.

Even if you have no coding experience at all, you'll be fine. Expect to invest several months from start to finish so you can really understand the concepts taught. Don't rush it.

Khan Academy is one of the internet's greatest treasures. This non-profit education platform has been a wonderful source of free education for the past decade, and it's only getting better. Want to learn Calculus? Biology? World History? How to do your taxes or invest your money? It's all here.

Khan Academy offers online courses in JavaScript, as well as HTML, CSS, and SQL. It's still a fledgling catalog compared to the other sites on this list, but it's worth keeping an eye on as it grows.

Get started with the Khan Academy Computer Programming Course.

YouTube is very hit or miss. Thousands of tutorial playlists exist, but too many of them are superficial or downright inaccurate. Of those that seem promising, a good chunk of them are incomplete. And of the ones that are complete, a significant portion are outdated.

However, if you have a discerning eye, YouTube can be a great resource for learning how to program. Start with our roundup of the best YouTube programming tutorials.

OpenCourser isn't an education platform like the other sites listed here. Rather, it's a search engine that aggregates thousands of free online courses from around the web and brings them to your fingertips.

As of this writing, OpenCourser catalogues over 900 free online programming courses, and adds more every day. Yes, you'll find a bunch of courses from edX, Coursera, Udacity, etc. but you'll also find some from other course providers, like Saylor Academy.

At the very least, it's a convenient way to search many of the aforementioned platforms at once.

Codecademy is a series of interactive programming courses online that aim to teach you the basics of a handful of programming languages and frameworks. Each course is a gamified, step-by-step process that holds your hand all the way from beginning to end.

But a word of caution before you dive into Codecademy: the things you'll learn here are somewhat basic and superficial. Codecademy teaches you how to write code, but it doesn't teach you how to think like a programmer very well.

Many first-time newbies end up frustrated because they don't know what to do with the knowledge they've picked up.

If you have prior coding experience and simply want to learn the syntax of a new language, then Codecademy is extremely useful. If you consider yourself a beginner, then you should avoid Codecademy for now.


The Odin Project is another free, comprehensive, programming-focused platform. It teaches HTML, CSS, JavaScript, and Ruby on Rails. Because it's free, it's a great way to see if you want to pursue a career in the industry without having to pay for an expensive bootcamp. Even if you don't want to create an account, you can use the resources for free.

The curriculum is expansive, the moderators are extremely helpful, and the projects you complete are based on real-world scenarios that you might encounter in a dev role.

Plus, The Odin Project boasts of a community that's constantly encouraging growth and actively assisting members.

Coding is a key skill for the times and can be a foundation that helps you navigate the evolving tech space from a creator's mindset. It's not a walk in the park, but it'll pay off if you're determined to stick with it.

Mon, 19 Sep 2022 02:08:00 -0500 en-US text/html
Killexams : Rust programming language outlines plan for updates to style guide
Image: skynesher/Getty

The Rust programming language is getting so popular that the people behind it are creating a team that's dedicated to defining the default Rust coding style. 

Rust, as developer analyst RedMonk puts it, is the "developer darling" of the moment and the most desirable contender for new code that would otherwise be written in C or C++, thanks to its automated way of ensuring secure memory management. 

Rust is not one of the most popular languages, such as Java or Python, but it's being used by developers on big infrastructure projects. Rust has been officially welcomed by Linux kernel creator Linus Torvalds and has made inroads into Android, Windows, Amazon Web Services, and Facebook parent Meta, to name a few – often in cases where a project sees fit for Rust to be used where C/C++ would have been adopted instead.  

Every programming language has style guides and, if they're popular enough, they might have multiple style guides from major users, such as Google, which has its guide for C++ – the language Chrome is written in. Python's Guido van Rossum has posted his styling conventions here

Also: The most popular programming languages and where to learn them

Rust, which reached version 1.0 in 2015, has a style guide in the "rustfmt" or 'Rust formatting tool' published on GitHub. The tool automatically formats Rust code to let developers focus on output. It aims to reduce the steep learning curve confronting new Rust developers. The guide instructs developers to "Use spaces, not tabs" and says "each level of indentation must be 4 spaces", for example.

As Josh Triplett explains in a accurate Rust blog post: "The standardized style helps Rust developers feel comfortable and at home in many different projects, and the tooling support from rustfmt makes it easy to maintain and to incorporate in continuous integration."

But the team responsible for writing the style guide between 2016 and 2018 has "by design" come to an end, so now it's now been decided to create the new Rust style team, consisting of Triplett, Caleb Cartwright, Michal Goulet, and Jane Lusby. 

The crew will first tackle a "backlog of new language constructs that lack formatting guidance" and move on to "defining and implementing the mechanisms to evolve the default Rust style, and then begin introducing style improvements."

The work includes minor language changes, big structural changes, and backwards compatibility. Also, the style team wants to craft the tool to make it current for easier coding in Rust, and help adoption. 

"As the Rust language develops, we have a regular need for improvements to the style guide, such as to support new language constructs. This includes minor language changes, as well as highly anticipated new features such as let-chaining (RFC 2497) and let-else (RFC 3137). New constructs like these, by default, get ignored and not formatted by rustfmt, and subsequently need formatting added. Some of this work has fallen to the rustfmt team in accurate years, but the rustfmt team would prefer to implement style determinations made by another team rather than making such determinations itself," writes Triplett. 

"In addition, rustfmt maintains backwards compatibility guarantees: code that has been correctly formatted with rustfmt won't get formatted differently with a future version of rustfmt. This avoids churn, and avoids creating CI failures when people use rustfmt to check style in CI. However, this also prevents evolving the Rust style to take community desires into account and Improve formatting over time. rustfmt provides various configuration options to change its default formatting, and many of those options represent changes that many people in the community would like enabled by default."

Fri, 07 Oct 2022 01:32:00 -0500 en text/html
Killexams : Best Cryptocurrency Trading Courses

Udemy’s Complete Cryptocurrency Investment Course covers all of the fundamentals of cryptocurrency investing in an affordable, self-paced, mobile-friendly format, making it the best overall cryptocurrency trading course on our list.

Originally created as a simple virtual classroom software in 2012, Udemy has since grown to become one of the largest online learning platforms offering over 185,000 courses taught by more than 64,000 instructors in 75 languages. Its Complete Cryptocurrency Investment Course introduces students to the basics of cryptocurrencies and advances them quickly into investing techniques featuring live examples. As a result, it’s our clear choice as the best course overall.  

The Complete Cryptocurrency Investment Course is led by Mohsen Hassan, a programmer, trader, and financial risk manager who has taught investing to more than 300,000 Udemy students. The course consists of over 12.5 hours of on-demand video, one article, and one downloadable resource and can be accessed on the Udemy mobile app.

The Complete Cryptocurrency Investment Course walks beginners through the fundamentals of cryptocurrency and quickly moves to live examples of buying, transferring, and using wallets as well as portfolio management techniques for both passive and active investing. Through this course, Hassan buys, transfers, secures, and builds a portfolio with real money so students can see exactly how it’s done.

The Complete Cryptocurrency Investment Course costs just $84.99 and includes full lifetime access, a certificate of completion at the end of the course, and a 30-day money-back guarantee. Udemy runs specials all the time, so you may be able to purchase the course for a much lower price.

Tue, 16 Feb 2021 04:28:00 -0600 en text/html
Killexams : Everything about programming languages: for beginners

A programming language is designed to describe a set of consecutive actions executed by a computer. A programming language is, therefore, a practical way for us humans to supply instructions to a computer.

What are the differences between languages?

Computers use languages to communicate with each other and have nothing to do with programming languages. They are referred to as communication protocols, which is pretty different from the former. A very strict programming language, wherein each instruction corresponds to one processor action.

The language used by the processor is called machine code. The code that reaches the processor consists of a series of 0s and 1s, known as binary data. Machine code is, therefore, difficult for humans to understand, which is why intermediary languages, which humans can understand, have been developed. The code written in this type of language is transformed into machine code so the processor can process it.

The assembly language (or assembler language) was the first programming language ever used. This is very similar to machine code but can be understood by developers. Nonetheless, it is so similar to machine code that it strictly depends on the type of processor used (each processor type may have its own machine code).

Thus, a program developed for one machine may not be portable to another type of machine. The term portability describes the ability to use a software program on different types of machines. A software program written in assembler code may sometimes have to be rewritten entirely to work on another type of computer.

In conclusion, a programming language is much more understandable than machine code and allows greater portability.

What are imperative and functional programming languages?

Programming languages are generally divided into two major groups according to how their commands are processed: imperative languages and functional languages.

  • Imperative programming language

Imperative language programs use a series of commands, grouped into blocks and composed of conditional statements that allow the program to return to a block of commands if the condition is met. These were the first programming languages in use and, even today, many modern languages still use this principle.

Structured imperative languages suffer from lack of flexibility due to the sequentiality of instructions.

  • Functional programming language

A functional programming language (often called procedural language) is a language that creates programs using functions, returning to a new output state and receiving as input the result of other functions. When a function invokes itself, we refer to this as recursion.

What about interpretation and compilation languages?

Programming languages may be roughly divided into two categories: interpreted and compiled.

A programming language is, by definition, different from machine code. This must, therefore, be translated so that the processor can understand the code. A program written in an interpreted language requires an extra program (the interpreter), which translates the program's commands as needed.

A program written in a compiled language is translated by an additional program called a compiler, which creates a new stand-alone file that does not require any other program to execute itself. Such a file is called an executable.

A program written in a compiled language does not require an additional program to run once it has been compiled. Furthermore, as the translation only needs to be done once, at compilation, it executes much faster.

However, it is not as flexible as a program written in an interpreted language. Each modification of the source file means that the program must be recompiled for the changes to take effect.

On the other hand, a compiled program can guarantee the source code's security. In effect, interpreted language, being a directly legible language, means that anyone can find out the secrets of a program and, thus, copy or modify the program. There is, therefore, a risk of copyright violation. On the other hand, certain secure applications need code confidentiality to avoid illegal copying (e.g., bank transactions, online payments, secure communications, etc.).

Some languages belong to both categories (i.e. LISP, Java, Python, etc.) as programs written in these languages may undergo an intermediary compilation phase into a file written in a language different from the source file and non-executable (requiring an interpreter). Java applets, small programs often loaded on web pages, are compiled files that can only be executed from within a web browser — these are files with the .class extension.

You have heard some of them, such as Java, C Programming Language, R Programming Language, or Python. Here is a non-exhaustive list of current programming languages:

Language Main application area Compiled/interpreted
ADA Real-time Compiled language
BASIC Programming for educational purposes Interpreted language
C System programming Compiled language
C++ System object programming Compiled language
Cobol Management Compiled language
Fortran Calculation Compiled language
Java Internet oriented programming Intermediary language
MATLAB Mathematical calculations Interpreted language
Mathematica Mathematical calculations Interpreted language
LISP Artificial intelligence Intermediary language
Pascal Education Compiled language
PHP Dynamic website development Interpreted language
Prolog Artificial intelligence Interpreted language
Perl Processing character strings Interpreted language
Wed, 05 Oct 2022 21:44:00 -0500 ElenaKM en text/html
Killexams : Statistical & Data Sciences

The program is designed to produce highly skilled, versatile statisticians and data scientists who possess powerful abilities for analyzing data. As such, SDS students learn not only how to build statistical models that generate predictions, but how to validate these models and interpret their parameters. Students learn to use their ingenuity to “wrangle” with complex data streams and construct informative data visualizations.

The major in statistical & data sciences consists of 10 courses, including depth in both statistics and computer science, an integrating course in data science, a course that emphasizes communication and an application domain of expertise. All but the application domain course must be graded; the application course can be taken S/U.

Benjamin Baumer, Randi Garcia, Albert Y. Kim, Katherine Kinnaird, Scott LaCombe, Lindsay Poirier. If you wish to declare an SDS major and need an advisor, please fill out this form at

Study Abroad Adviser
Scott LaCombe


See the major diagram below for prerequisites, and see the Note on course substitutions following the description of the major.

  1. Foundations and Core (5 courses): The following required courses build foundational skills in mathematics, statistics and computer science that are necessary for learning from modern data.
    • SDS 201 or SDS 220: Introductory Statistics
    • SDS 291: Multiple Regression
    • CSC 110: Introduction to Computer Science or CSC 111: Intro to Programming
    • SDS 192: Intro to Data Science
    • MTH 211: Linear Algebra
  2. Statistical Depth (1 course): One additional course that provides exposure to additional statistical models.
    • SDS 290: Research Design and Analysis
    • SDS 293: Modeling for Machine Learning
    • MTH/SDS 320: Mathematical Statistics
    • SDS 390: Topics in SDS. Offerings may vary; previous versions of this course include:
      • Bayesian Statistics
      • Ecological Forecasting
      • Structural Equation Modeling
      • Statistical Analysis of Social Networks
  3. Programming Depth (1 course): One additional course that deepens exposure to programming.
    • CSC 120: Object Oriented Programming
    • CSC 151: Programming Languages
    • CSC 210: Data Structures and Basic Algorithms
    • CSC 212: Data Structures
    • CSC 220: Advanced Programming Techniques
    • CSC/SDS 235: Visual Analytics (must take programming intensive track)
    • CSC 240: Computer Graphics
    • SDS 270: Advanced Programming for Data Science
    • CSC 294: Computational Machine Learning
    • CSC/SDS 352: Parallel & Distributed Computing
  4. Communication (1 course): One course that focuses on the ability to communicate in written, graphical and/or oral forms in the context of data.
    • CSC/SDS 109: Communicating with Data
    • FYS 105: Ethics of Big Data
    • FYS 189: Data and Social Justice
    • CSC/SDS 235: Visual Analytics
    • SDS 236: Data Journalism
    • SDS 237: Data Ethnography
  1. Application Domain (1 course): Every student is required to take a course that allows them to conduct a substantial data analysis project evaluated by an expert in a specific domain of application.

    Please consult our continuously-updated, nonexhaustive list of previously approved application domain courses, which includes:

    • SDS 300: Applications of Statistical & Data Sciences
    • Dual-prefixed research seminars offered by SDS:
      • GOV/SDS 338: Research Seminar in Political Networks
      • CSC/SDS 354: Seminar: Music Information Retrieval
      • PSY/SDS 364: Research Seminar on Intergroup Relationships
    • Research seminars (normally 300-level) or special studies of at least two credits. Normally, the domain would be outside of mathematics, statistics and computer science.
    • Departmental honors theses in another major (normally not MTH or CSC)

A student and their adviser should identify potential application domains of interest as early as possible, since many suitable courses will have prerequisites. Normally, this should happen during the fourth semester or at the time of major declaration, whichever comes first. The determination of whether a course satisfies the requirement will be made by the student’s major adviser.

  1. Capstone (1 course): Every student is required to complete a capstone experience, which exposes them to real-world data analysis challenges.
  2. Electives: (as needed to complete to 10 courses): Provided that the requirements listed above are met, any of the courses listed above may be counted as electives to reach the 10 course requirement. Five College courses in statistics and computer science may be taken as electives. Additionally, the following courses may be counted toward completion of the major:
    • MTH 246: Probability
    • CSC 230: Introduction to Database Systems
    • CSC 252: Algorithms
    • CSC 256: Intelligent User Interfaces
    • CSC 290: Artificial Intelligence
    • CSC 330: Database Systems
    • CSC 390: Seminar on Artificial Intelligence

Notes on course substitutions:

  • CSC 110 or 111 may be replaced by a 4 or 5 on the AP computer science exam.
  • SDS 220 or SDS 201 may be replaced by a 4 or 5 on the AP statistics exam. Replacement by AP courses does not diminish the total number of courses required for either the major or the minor (see Electives above). Any one of ECO 220, GOV 203, PSY 201, or SOC 204 may directly substitute for SDS 220 or SDS 201 without the need to take another course, in both the major and minor. Note that SDS 220 and ECO 220 require Calculus. Students should be aware that substituting for SDS 220 or SDS 201 could leave them without R programming experience, which is needed in subsequent courses, such as SDS 290 & 291.
  • MTH 211 may be replaced by petition in exceptional circumstances.
  • Five-College equivalents may substitute with permission of the program.
  • SDS 107 and EDC 206 are important courses but do not count for the major or the minor.
  • An Honors Thesis (SDS 430D) generally cannot substitute for the capstone SDS 410.

The Major in Mathematical Statistics

Students interested in doctoral programs in Statistics should consider the Major in Mathematical Statistics jointly operated by SDS and MTH.

Sun, 10 Jul 2022 15:34:00 -0500 en text/html
Killexams : Pennsylvania Motorcycle Safety Program offering free courses

PENNSYLVANIA (WHTM) — Motorcycle Safety Training is being offered for Pennsylvanians that are interested in taking the course through the Pennsylvania Motorcycle Safety Program (PAMSP).

The course will be provided, weather pending, by Third-Party Motorcycle Training Providers. If you have a Pennsylvania Class M permit and motorcycle license you can take the classes for free if they are operating under the PAMSP.

There are many different safety courses that are offered through Third-Party Training Providers. PennDOT reminds riders that it is important to have proper and required safety gear before participating in the course.

More information about the courses can be found here.

You can find out if the courses are available in your area here.

Below is a list of the courses that are currently offered:

Basic Rider Course (BRC)

The BRC is the starting place for a novice rider or someone that has not been through any training to learn the basic fundamentals of operating a motorcycle safely. Motorcycles are provided. This IS a licensing course.

Intermediate Rider Course (IRC)

The IRC is for experienced riders who have their own street legal motorcycle and want to develop more skills in traction management. Riders bring their own motorcycle. This IS a licensing course.

3 Wheel Rider Course (3WRC)

The 3WRC is for riders interested in learning to ride a 3 Wheel motorcycle.  This course includes trikes, sidecars and Can AM Spyders. Riders will experience the proper way to corner and more on three wheels. Bring your own approved vehicle or use a provided one. This IS a licensing course.

Advanced Rider Course (ARC)

The ARC is for experienced riders with at least 3,000 miles of riding experience and a desire to learn to maximize mid-corner traction and ground clearance to Improve street safety. Riders bring their own motorcycle and protective gear. This is NOT a licensing course.

Thu, 22 Sep 2022 08:06:00 -0500 en-US text/html
Killexams : Electrical & Computer Engineering Course Listing Introduction to Electrical and Computer Engineering (Formerly 25/16.107)


This course is divided into two parts in which students focus on core skills to help them thrive in electrical and computer engineering. The first half of the course focuses on application programming in Matlab where students learn basics of Programming, Digital Signal Processing, and Data Analysis. In the second part of the course students program a micro-controller and learn about the function of basic electronic components. Students learn to use basic test equipment such as an Oscilloscope, Function Generator, Volt Meter. This course is project and lab based.

Curricula Practical Training


Curricula Practical Training. "Variable credit course, student chooses appropriate amount of credits when registering."

Circuit Theory I (Formerly 16.201)


This course covers ideal elements, active and passive. It introduces and applies Ohm's Law and Kirchoff's Laws. Introduces concepts of network topology, independent and dependent variables, mesh and nodal analysis, the definition and consequences of linearity, source transformation, the superposition principle, Thevenin's and Norton's theorems, and maximum power transfer. Also covers ideal inductance and capacitance in simple circuits with the study of transient response and behavior under DC conditions.


Pre-req: MATH.1320 Calculus II, and Co-req: EECE.2070 Basic Electrical Engineering Lab I, and a 'C' or higher in MATH.1320.

Circuit Theory II (Formerly 16.202)


This course covers AC circuits under sinusoidal steady-state conditions using the concept of the frequency domain. Introduces the use of complex numbers, phasors, impedance and admittance for the application of circuit laws introduced in Circuit Theory I: Thevenin and Norton's theorems, source transformation, superposition, maximum power transfer, nodal and mesh analysis. Covers power in the frequency domain, including RMS values, average power, reactive power, and apparent power. Introduction to magnetic coupling, mutual inductance, and the ideal transformer. Introduction to transfer functions, poles and zeroes in the s-plane.


Pre-Req: C- or better in EECE 2010 Circuit Theory I, or Spring 2020 grade of "P" and Co-Req: EECE 2080 Basic EE Lab II.

Basic Electrical Engineering Laboratory I (Formerly 16.207)


Experimental work designed to verify theory and to acquaint students with electrical measurement techniques: experiments on meters, bridges, and oscilloscopes. Experiments are correlated with Circuit Theory I and concern: resistive measurements, Kirchhoff's laws, network theorems, conservation of power and maximum power transfer, inductance and capacitance, and first and second-order transients, operational amplifiers. MATLAB will be utilized throughout the course.


Co-Req: EECE.2010 Circuit Theory I.

Basic Electrical Engineering Lab II (Formerly 16.208)


Presents experimental work designed to emphasize electrical measurement techniques of linear systems with time-varying signals. Waveform measurements with DC and AC meters as well as advanced use of the oscilloscope are also discussed. Experiments are integrated with Circuit Theory II. Experiments cover: Kirchhoff's laws for phasors, magnitude and phase measurements of impedance, network theorems, frequency response, resonance, inductance, maximum power transfer, and MATLAB techniques.


Pre-Req: EECE 2070 Basic EE Lab I; Co-Req: EECE 2020 Circuit Theory II.

Fundamentals of Electricity I (Formerly 16.211/213)


This course serves as an introduction to direct current (DC) and alternating current (AC) analysis of electric circuits, with emphasis on energy and power. Covers the explanation of basic components (resistor, capacitor and inductor) and their use in electronics. Cover also the design and use of multi-range voltmeters, ammeters, and ohmmeters, series, parallel and series parallel circuits, the use of bridges, phasor analysis of AC circuits, transformers, relays, solenoids, etc. Different techniques like Superposition theorem, Thevenin equivalent circuit or Maximum Power will be presented. Students will also be introduced to DC and AC motors and generators, first and second order filters as well as basic sensors. Not for ECE students.


Pre-Req: MATH 1320 Calculus II.

Fundamentals of Sound Recording (Formerly 16.214)


This course serves to instruct sound recording technology through the concepts of voltage, current, power, resistance and Ohm's law; series, parallel and resonant circuits, Kirchhoff's voltage and current laws; the Wheatstone bridge, Thevenin equivalent circuits and maximum power transfer theorem; magnetism, electromagnetism, electromagnetic devices, and transformers; a.c. current, RF signals, capacitors, and inductors; RC, RL, and RLC circuits; d.c. power sources; diodes, transistors, tubes (thermionic emission), and amplifiers. Use of voltmeters, ammeters, ohmmeters, and oscilloscopes are discussed and used in lab throughout the course. Not for ECE students.


Sound Recording Technology majors; Pre-Req: MATH 1320 Calculus II.

ECE Application Programming (Formerly 16.216)


Introduces C programming for engineers. Covers fundamentals of procedural programming with applications in electrical and Computer engineering and embedded systems. Topics include variables, expressions and statements, console input/output, modularization and functions, arrays, pointers and strings algorithms, structures, and file input/output. Introduces working with C at the bit manipulation level. Laboratories include designing and programming engineering applications.

History of Radio (Formerly 16.233)


Intended primarily for students majoring in the liberal arts. The course develops the theory of electricity from an historical perspective. Sufficient background in circuit theory, resonance, field theory and radio waves is given to provide an understanding of the principles of radio from its antecedents in the nineteenth century through the invention of the transistor in the mid twentieth century. The fundamental contributions of, for example Volta, Oersted, Morse, Maxwell, Faraday, Hertz, Lodge, and Marconi are considered. In the present century the technical advances of such figures as de Forest, Fleming, Fessenden, Armstrong and Shockley are studied. The growth, regulation and culture of American broadcasting are also central to the course. Laboratory work is required and students may use this course toward fulfilling the General Education (science/experimental component) requirement of the University. Not open to students in the College of Engineering.

Introduction to Data Communication Networks


This course is designed to convey the essentials of data communication and networking. This includes an understanding of the Open Systems Interconnection (OSI), TCP/IP and Internet models. It covers various protocols and architectures of interconnection technologies. Several concepts will be discussed that will enable students to apply the basic concepts of data communication and networking technology in many practical situations.


Pre-req: EECE.1070 Introduction to Electrical and Computer Engineering, and MATH.1310 Calculus I, and PHYS.1410 Physics I.

Logic Design (Formerly 16.265)


Number systems and binary codes. Boolean algebra. Canonical and fundamental forms of Boolean functions. Function expansion and its applications to digital circuit design. Minimization of Boolean functions by Boolean algebra and Karnaugh maps. Two-level and multi-level digital circuits. Decoder, encoders, multiplexers, and de-multiplexers. Latches and flip-flops. Registers and counters. Analysis and synthesis of synchronous sequential circuits. Design of more complex circuits: data-path and control circuits. Use of software tools to implement a design on modern hardware.


Pre-req: MECH.1070 intro to Mechanical Eng, or COMP.1020 Computing II, or EECE.1070 Intro to Elec. & Comp. Engin, or EECE.2160 ECE Application Programming.

Electronics I Lab (Formerly 16.311)


Laboratory experiments coordinated with the subject matter of Electronics I. This lab explores the characteristics and use of electronic instrumentation for making measurements on electronic circuits. Labs will utilize the methods of designing and characterizing diode and transistor circuits. They will analyze the performance characteristics of digital and linear semiconductor circuits, including logic elements and amplifiers. The design and construction of circuits using monolithic op amps will also be explored.


Pre-req: EECE.2080 Basic EE Lab II, and Co-req: EECE.3650 Electronics I.

Electronics II Laboratory (Formerly 16.312)


This course covers laboratory experiments coordinated with the subject matter of Electronics II, Study of high-frequency characteristics of transistors and transistor amplifiers. Covers feedback in electronic circuits, electronic oscillators and differential amplifier. Covers also the properties of linear IC operational amplifiers and their application in amplifier circuits and waveform generation circuits. Design and analysis of linear circuits.


Pre-req: EECE.3110 Electronics I Lab, and Co-req: EECE.3660 Electronics II.

Microprocessors Systems Design I (Formerly 16.317)


Introduction to microprocessors, Uses assembly language to develop a foundation on the hardware which executes a program. Memory and I/O interface design and programming. Design and operation of computer systems. Study of microprocessor and its basic support components, including detailed schematics, timing and functional analysis of their interactions. Laboratories directly related to microprocessor functions and its interfaces (e.g. memory subsystem, I/O devices and coprocessors).


Pre-req: EECE.2160 ECE Application Programming, and EECE 2650 Logic Design.

Data Structures (Formerly 16.322)


Covers algorithms and their performance analysis, data structures, abstraction, and encapsulation. Introduces stacks, queues, linked lists, trees, heaps, priority queues, and hash tables, and their physical representation. Discusses efficient sorting (quicksort and heapsort) and experimental algorithm analysis. Examines several design issues, including selection of data structures based on operations to be optimized, algorithm encapsulation using classes and templates, and how and when to use recursion. Assignments include programming of data structures in an object-oriented language.


Pre-Req: EECE.2160 ECE Application Programming

Electromechanics (Formerly 16.355)


Alternating current circuits, three phase circuits, basics of electromagnetic field theory, magnetic circuits, inductance, electromechanical energy conversion. Ideal transformer, iron-core transformer, voltage regulation, efficiency equivalent circuits, and three phase transformers. Induction machine construction, equivalent circuit, torque speed characteristics, and single phase motors. Synchronous machine construction, equivalent circuits, power relationships phasor diagrams, and synchronous motors. Direct current machines construction, types, efficiency, power flow diagram, and external characteristics.


Pre-Req: EECE.2020 Circuit Theory II.

Engineering Electromagnetics I (Formerly 16.360)


Electromagnetics I is the study of fundamental electrostatic and magnetostatic equations building up to the foundation of electrodynamics, Maxwell's Equations. This course is put into an engineering perspective by describing transmission line properties using circuit models and deriving these model parameters directly from Maxwell's Equations. To accomplish these tasks, Engineering Electromagnetics I implements: Transmission lines as Distributed Circuits, Smith Charts, impedance Matching, Electrostatics and Capacitance, steady current flow and Resistance, and Magnetostatics and Inductance.


Pre-Req: EECE 2020 Circuit Theory II and PHYS 1440 Physics II.

Signals and Systems I (Formerly 16.362)


This course covers various continuous voltage/current time functions and their applications to linear time-invariant (LTI) electrical systems. It reviews pertinent Topics from previous courses on circuit theory, such as system functions, S-plane concepts and complete responses. It introduces step and impulse functions and their responses in LTI circuits. It covers the solving of convolution integrals and differential equations, the transformation of signals to Fourier series, the Fourier and Laplace transforms, with their application, in continuous and discrete time, and Parseval's theorem. It also describes analog filter responses and design. A computing project is proposed in this course.


Pre-Req: EECE 2020 Circuit Theory II and MATH 2360 Eng Differential Equations or MATH.2340 Differential Equations.

Introduction to Probability and Random Processes (Formerly 16.363)


Introduction to probability, random processes and basic statistical methods to address the random nature of signals and systems that engineers analyze, characterize and apply in their designs. It includes discrete and continuous random variables, their probability distributions and analytical and statistical methods for determining the mean, variance and higher order moments that characterize the random variable. Descriptive and inferential statistics, as well as time-varying random processes and their spectral analysis are introduced. The course provides the skills required to address modeling uncertainty in manufacturing and reliability analysis, noise characterization, and data analysis.


Pre-Req: EECE.2020 Circuit Theory II.

Engineering Mathematics (Formerly 16.364)


Complex number, Argand plane, derivatives of complex numbers, limits and continuity, derivative and Cauchy Riemann conditions, analytic functions, integration in the complex plane, Cauchy's integral formula, infinite series for complex variables. Taylor series, Laurent series, residue theory, evaluation of integrals around indented contours. Linear vector spaces, matrices and determinants, eigenvalues and eigenvectors.


Pre-Req: MATH 2360 Eng Differential Equations or MATH.2340 Differential Equations.

Electronics I (Formerly 16.365)


A brief introduction to solid-state physics, leading to discussion of physical characteristics of p-n junction diodes, bipolar junction transistors, and field-effect transistors: active, saturated, and cutoff models of bipolar transistors and triode, constant current, and cutoff models of MOSFETs. Circuit models for diodes, and diode applications. Circuit models for transistors, and transistor applications in bipolar and MOS digital circuits and low-frequency amplifier circuits. Analysis of digital circuits and linear circuits based on application of circuit models of devices and circuit theory.


Pre-req: EECE 2020 Circuit Theory ll, and PHYS 1440 Physics ll, and Co-req: EECE 3110 Electronics l Lab.

Electronics II (Formerly 16.366)


A continuation of 16.365 with discussion of differential amplifiers, operation amplifiers and op amp applications, transistor amplifiers at very high frequencies; direct-coupled and band pass amplifiers; small and large signal amplifiers; feedback amplifiers and oscillators. Active filters, wave form generation circuits including Schmitt trigger, multiplexers, and A/D and D/A converters. Circuit design employing integrated circuit operational amplifiers and discrete devices. Circuit analysis using SPICE. An electronic design project constitutes a major part of the course.


Pre-Req: C- or better in EECE 3650 Electronics I,or Spring 2020 grade of "P", Co-Req: EECE 3120 Electronics Lab II.

Capstone Proposal (Formerly 16.399)


This course is the first in a two semester capstone sequence. In a group, students will work with a client to define their project, by identifying the problem, objective and requirements, and engage in design, analysis, test and fabrication tasks as appropriate to meet the project goals. Project management tools are discussed and applied in this process.


Pre-Reqs: EECE 3110 Electronics I Lab, and EECE 3170 Microprocessor Sys Desgn I, and EECE 3650 Electronics I.

Microwave Engineering (Formerly 16.403)


An introductory course in the analysis and design of passive microwave circuits beginning with a review of time-varying electromagnetic field concepts and transmission lines. Smith Chart problems; single and double stub matching; impedance transformer design; maximally flat and Chebyshev transformers; microstrip transmission lines, slot lines, coplanar lines; rectangular and circular waveguides; waveguide windows and their use in impedance matching; design of directional couplers; features of weak and strong couplings; microwave filter design; characteristics of low-pass, high-pass, band-pass, band-stop filter designs; two-port network representation of junctions; Z and Y parameters, ABCD parameters, scattering matrix; microwave measurements; measurement of VSWR, complex impedance, dielectric constant, attenuation, and power. A design project constitutes a major part of the course.


Pre-Req: EECE.4610 Emag Theory II.

VLSI Fabrication (Formerly 16.470/EECE.4700)


Fabrication of resistors, capacitors, p-n junction and Schottky barrier diodes, BJT's and MOS devices and integrated circuits. Topics include: silicon structure, wafer preparation, sequential techniques in microelectronic processing, testing and packaging, yield and clean room environments. MOS structures, crystal defects, Fick's laws of diffusion; oxidation of silicon, photolithography including photoresist, development and stripping. Metallization for conductors, Ion implantation for depletion mode and CMOS transistors for better yield speed, low power dissipation and reliability. Students will fabricate circuits using the DSIPL Laboratory.


Pre-Req: EECE.3650 Electronics I.

Antenna Theory and Design (Formerly 16.462/EECE.4620)


An introduction to properties of individual antennas and arrays of antennas. Retarded potentials, dipoles of arbitrary length, radiation pattern, gain, directivity, radiation resistance. The loop antenna. Effects of the earth. Reciprocity, receiving antennas, effective length and area. Moment methods. Arrays: collinear, broadside, endfire. Array synthesis. Mutual coupling. Log-periodic and Yagi arrays. Radiation from apertures: the waveguide horn antenna, parabolic dish. Antenna noise temperature. Numerical software packages. A design project is required in the course.


Pre-Req: EECE.4610 Emag Theory II.

Directed Studies (Formerly 16.409)


Provides an opportunity for qualified Electrical Engineering students to investigate specific areas of interest. The real project undertaken may be software or hardware oriented. The most important characteristics of the projects are that the end results represent independent study, that they are research and development oriented, and that they are accomplished in an engineering environment. Design reviews and progress reports are expected for each project. A final formal report to be permanently filed in the EE Department is required for each project. Engineering Design (100%).


Pre-Reqs: EECE 3550 Electromechanics,EECE 3600 Emag Theory I, EECE 3620 Signals & Systems I, EECE 3650 Electronics I,and EECE 3660 Electronics II.

Directed Studies (Formerly 16.410)


The purpose of this course is to provide an opportunity for qualified Electrical Engineering students to investigate specific areas of interest. The real project undertaken may be software or hardware oriented. The most important characteristics of the projects are that the end results represent independent study and that they are research and development oriented, and that they are accomplished in an engineering environment. Design reviews and progress reports are expected for each project. A final formal report to be permanently filed in the EE Department is required for each project.


Pre-Reqs: EECE 3550 Electromechanics,EECE 3600 Emag Theory I,EECE 3620 Signals & Systems I,EECE 3650 Electronics I, and EECE 3660 Electronics II.

Directed Studies (Formerly 16.412)


The purpose of this course is to provide an opportunity for qualified Electrical Engineering students to investigate specific areas of interest. The real project undertaken may be software or hardware oriented. The most important characteristics of the projects are that the end results represent independent study and that they are research and development oriented, and that they are accomplished in an engineering environment. Design reviews and progress reports are expected for each project. A final formal report to be permanently filed in the EE Department is required for each project.


Pre-Reqs: EECE 3550 Electromechanics,EECE 3600 Emag Theory I, EECE 3620 Signals & Systems I, EECE 3650 Electronics I,and EECE 3660 Electronics II.

Linear Feedback System (Formerly 16.413)


Concepts of feedback; open loop and closed loop systems. Feedback in electrical and mechanical systems. Mathematical models of systems and linear approximations. Transfer functions of linear systems, block diagrams and signal flow graphs. Sensitivity, control of transient response, disturbance signals. Time domain performance: steady state errors, performance indices. Stability related to s-plane location of the roots of the characteristic equation. Routh-Hurwitz criterion. Graphical analysis techniques: root locus, frequency response as polar plot and Bode diagrams. Closed loop frequency response. A control system design project is included in the course.


Pre-Req: EECE 3620 Signals & Systems I and EECE 3640 Engineering Math.

Integrated Power Systems (Formerly 16.414/514)


Power System Operations and Electricity Markets provide a comprehensive overview to understand and meet the challenges of the new competitive highly deregulated power industry. The course presents new methods for power systems operations in a unified integrated framework combining the business and technical aspects of the restructured power industry. An outlook on power policy models, regulation, reliability, and economics is attentively reviewed. The course lay the groundwork for the coming era of unbundling, open access,, power marketing, self-generation, and regional transmission operations.


Pre-Req: EECE.2020 Circuit Theory II.

Power Electronics (Formerly 16.473/515 & EECE.4730/5150)


A one-semester course with emphasis on the engineering design and performance analysis of power electronics converters. Topics include: power electronics devices (power MOSFETs, power transistors, diodes, silicon controlled rectifiers SCRs, TRIACs, DIACs and Power Darlington Transistors), rectifiers, inverters, ac voltage controllers, dc choppers, cycloconverters, and power supplies. The course includes a project, which requires that the student design and build one of the power electronics converters. A demonstrative laboratory to expose the students to all kinds of projects is part of the course.


Pre-Reqs: EECE 3550 Electromechanics and EECE 3660 Electronics II.

Wireless Communication (Formerly 16.418)


Cellular systems and design principles, co-channel and adjacent channel interference, mobile radio propagation and determination of large scale path loss, propagation mechanisms like reflection, diffraction and scattering, outdoor propagation models, Okumura and Hata models, small scale fading and multipath, Doppler shift and effects, statistical models for multipath, digital modulation techniques QPSK, DPSK, GMSK, multiple access techniques, TDMA, FDMA, CDMA, spread spectrum techniques, frequency hopped systems, wireless systems and worldwide standards.


Pre-req: EECE.3630 Introduction to Probability and Random Process.

Real Time Digital Signal Processing (Formerly 16.421)


This course provides an introduction to real-time digital signal processing techniques using floating point and fixed point processors. The architecture, instruction set and software development tools for these processors will be studied via a series of C and assembly language computer projects where real-time adaptive filters, modems, digital control systems and speech recognition systems are implemented.


Pre-req: EECE.3620 Signals and Systems I.

Semiconductor Physics for Solid-State Electronics (Formerly 16.423)


The course covers fundamental solid-state and semiconductor physics relevant for understanding electronic devices. Topics include quantum mechanics of electrons in solids, crystalline structures, ban theory of semiconductors, electron statistics and dynamics in energy bands, lattice dynamics and phonons, carrier transport, and optical processes in semiconductors.


Pre-req: EECE.3650 Electronics I, and EECE.3640 Engineering Mathematics, and EECE.3600 Engineering Electromagnetics I, or permission of instructor.

Computational Methods for Power System Analysis (Formerly 16.424/524)


The course explores some of the mathematical and simulation tools used for the design, analysis and operation of electric power systems. Computational methods based on linear and nonlinear optimization algorithms are used to solve load flow problems, to analyze and characterize system faults and contingencies, and to complete economic dispatch of electric power systems. Real case studies and theoretical projects are assigned to implement the techniques learned and to propose recommendations. Different software applications will be used concurrently including ATP, PowerWorld Simulator, Aspen, MatLab with Simulink and Power System Toolbox, PSCAD, etc.


Pre-Req: EECE.2020 Circuit Theory II.

Power Distribution System (Formerly 16.4440/EECE.4440)


An intermediate course in analysis and operation of electrical power distribution systems using applied calculus and matrix algebra. Topics include electrical loads characteristics, modeling , metering, customer billing, voltage regulation, voltage levels, and power factor correction. The design and operation of the power distribution system components will be introduced: distribution transformers, distribution substation, distribution networks, and distribution equipment.


Pre-req: EECE.2020 Circuit Theory II, and EECE.2080 Basic EE Lab II.

Power Systems Stability and Control (Formerly 16.426/526)


Stability definition and cases in power systems. System model for machine angle stability. Small signal and transient stability. Voltage stability phenomenon, its characterization. Small and large signal models for voltage stability analysis. Frequency stability and control. Compensation methods for system voltage regulation including classical and modem methods. Stability of multi-machine system.


Pre-Req: EECE.2020 Circuit Theory II.

Advanced VLSI Design Techniques (Formerly 16.427/527)


This course builds on the previous experience with Cadence design tools and covers advanced VLSI design techniques for low power circuits. Topics covered include aspects of the design of low voltage and low power circuits including process technology, device modeling, CMOS circuit design, memory circuits and subsystem design. This will be a research-oriented course based on team projects.


Pre-req: EECE.4690 VLSI Design, or EECE.5690 VLSI Design, or Permission of Instructor.

Alternative Energy Sources (Formerly 16.428)


PV conversion, cell efficiency, cell response, systems and applications. Wind Energy conversion systems: Wind and its characteristics; aerodynamic theory of windmills; wind turbines and generators; wind farms; siting of windmills. Other alternative energy sources: Tidal energy, wave energy, ocean thermal energy conversion, geothermal energy, solar thermal power, satellite power, biofuels. Energy storage: Batteries, fuel cells, hydro pump storage, flywheels, compressed air.

Electric Vehicle Technology (Formerly 16.429)


Electric vehicle VS internal combustion engine vehicle. Electric vehicle (EV) saves the environment. EV design, EV motors, EV batteries, EV battery chargers and charging algorithms, EV instrumentation and EV wiring diagram. Hybrid electric vehicles. Fuel cells. Fuel cell electric vehicles. The course includes independent work.

Introduction to Medical Image Reconstruction


This course provides both traditional and state-of-the-art tomographic reconstruction algorithms in a unified way. It includes analytic reconstruction, iterative reconstruction, and deep reconstruction based on the state-of-the-art deep learning techniques. This course provides fundamental knowledge for careers in medical image reconstruction.


Pre-req: EECE.3620 Signals and Systems I.

R F Design (Formerly 16.431)


Two-port network parameters, Smith chart applications for impedance matching, transmission line structures like stripline, microstrip line and coaxial line, filter designs for low-pass, high-pass and band-pass characteristics, amplifier design based on s-parameters, bias network designs, one port and two port oscillator circuits, noise in RF systems.


Pre-Req: EECE.3600 Emag Theory I.

Electronic Materials (Formerly 16.333/EECE.3330)


The production and processing of materials into finished products constitute a large part of the present economy. To prepare students for the use of a variety of traditional and new materials, this course will cover: atomic structure and chemical bonding, crystal geometry and defects, mechanical properties and phase diagrams of metals and alloys, electrical and optical properties of semiconductors, ceramics, and polymers; brief description of electronic, quantum electronic and photonic devices; benefits and difficulties of materials design with decreasing dimensions from millimeters to micrometers and to nanometers.


Pre-req: MATH.1320 Calculus II and PHYS.1440 Physics II.

Introduction to Biosensors (Formerly 16.441/541)


This course introduces the theory and design of biosensors and their applications for pathology, pharmacogenetics, public health, food safety civil defense, and environmental monitoring. Optical, electrochemical and mechanical sensing techniques will be discussed.

Analog Devices and Techniques (Formerly 16.445/565 & EECE.4450/5650)


A survey of analog devices and techniques, concentrating on operational amplifier design and applications. Operational amplifier design is studied to reveal the limitations of real opamps, and to develop a basis for interpreting their specifications. Representative applications are covered, including: simple amplifiers, differential and instrumentation amplifiers, summers, integrators, active filters, nonlinear circuits, and waveform generation circuits. A design project is required.


Pre-Req: EECE.3660 Electronics II.

Advanced Digital System Hardware Design (Formerly 16.450)


Design of logic machines. Finite state machines, gate array designs, ALU and 4 bit CPU unit designs, micro-programmed systems. Hardware design of advanced digital circuits using XILINX. Application of probability and statistics for hardware performance, and upgrading hardware systems. Laboratories incorporate specification, top-down design, modeling, implementation and testing of real advanced digital design systems hardware. Laboratories also include simulation of circuits using VHDL before real hardware implementation and PLDs programming.


Pre-req: EECE.2650 Logic Design, and EECE.3650 Electronics I, and EECE.3110 Electronics I Lab, and EECE.3170 Microprocessor Systems Design I, or permission of Instructor.

Heterogeneous Computing


This course introduces heterogeneous computing architecture and the design and optimization of applications that best utilize the resources on such platforms. The course Topics include heterogeneous computer architecture, offloading architecture/API, platform, memory and execution models, GPU/FPGA acceleration, OpenCL programming framework, Data Parallel C++ programming framework, performance analysis and optimization. Labs are included to practice design methodology and development tools.


Pre-req: EECE.3170 Microprocessors Systems Design I, or EECE.4821 Computer Architecture and Design, or Permission of Instructor.

Microprocessor Systems II & Embedded Systems (Formerly 16.480/EECE.4800)


CPU architecture, memory interfaces and management, coprocessor interfaces, bus concepts, bus arbitration techniques, serial I/O devices, DMA, interrupt control devices. Including Design, construction, and testing of dedicated microprocessor systems (static and real-time). Hardware limitations of the single-chip system. Includes micro-controllers, programming for small systems, interfacing, communications, validating hardware and software, microprogramming of controller chips, design methods and testing of embedded systems.


Pre-Reqs: EECE 3110 Electronics I Lab, and EECE 3170 Microprocessor Sys Desgn I, and EECE 3650 Electronics I.

Software Engineering (Formerly 16.453)


Introduces software life cycle models, and engineering methods for software design and development. Design and implementation, testing, and maintenance of large software packages in a dynamic environment, and systematic approach to software design with emphasis on portability and ease of modification. Laboratories include a project where some of the software engineering methods (from modeling to testing) are applied in an engineering example.


Pre-Req: EECE 2160 ECE Application Programming and EECE 3220 Data Structures. or Permission of Instructor.

Computer System Security


An introduction to computer system security. This course introduces the threats and vulnerabilities in computer systems. This course covers the elementary cryptography, program security, security in operating system, database security, network, web, and e-commerce. It also covers some aspects of hardware security, legal, ethical and privacy issues in computer system security.


Pre-req: EECE.3220 Data Structures.

Fundamentals of Robotics


The material in this course is a combination of essential topics, techniques, algorithms, and tools that will be used in future robotics courses. Fundamental Topics relevant to robots (linear algebra, numerical methods, programming) will be reinforced throughout the course using introductions to other robotics Topics that are each worthy of a full semester of study (dynamics, kinematics, controls, planning, sensing). Students will program real robots to further refine their skills and experience the material fully.


Pre-Req: COMP.1010 Computing 1 or EECE.2160 ECE Computing Application.

Introduction to Nanoelectronics (Formerly 16.459/559)


This course introduces the use of nanomaterials for electronic devices such as sensors and transistors. Synthesis methods for nanoparticles, nanotubes, nanowires, and 2-D materials such as graphene will be covered. The challenges in incorporating nanomaterials into devices will also be discussed. These methods will be compared to techniques used in the semiconductor industry and what challenges, technically and financially, exist for their widespread adoption will be addressed. Finally, examples of devices that use nanomaterials will be reviewed. The course will have some hands on demonstrations.

Biomedical Instrumentation (Formerly 16.460/560)


A survey of biomedical instrumentation that leads to the analysis of various medical system designs and the related factors involved in medical device innovation. In addition to the technical aspects of system integration of biosensors and physiological transducers there will be coverage of a biodesign innovation process that can translate clinical needs into designs. A significant course component will be project-based prototyping of mobile heath applications. The overall goals of the course are to provide the theoretical background as well as specific requirements for medical device development along with some practical project experience that would thereby enable students to design electrical and computer based medical systems.


Pre-req: ECE senior/grad or BMEBT student

Engineering Electromagnetics II (Formerly 16.461)


Continuation of Magnetostatics, Maxwell's Equations for Time-varying Fields, plane waves: time-harmonic fields, polarization, current flow in good conductors and skin effect, power density and Poynting vector, wave reflection and transmission; Snell's Law, fiber optics, Brewster angle, radiation and simple antennas, electromagnetic concepts involved in a topical technology in development.


Pre-Req: EECE.3600 Emag Theory I.

Special Topics (Formerly 16.467)


Topics of current interest in Electrical and Computer Engineering. Subject matter to be announced in advance.

Electro-optics & Integrated Optics (Formerly 16.468)


An introduction to physical optics, electro-optics and integrated optics. Topics include: Waves and polarization, optical resonators, optical waveguides, coupling between waveguides, electro-optical properties of crystals, electro-optic modulators, Micro-Optical-Electro-Mechanical (MEMS) Devices and photonic and microwave wireless systems.


Pre-Req: EECE.3600 Emag Theory I.

VLSI Design (Formerly 16.469/502 & EECE.4690/5020)


Introduction to CMOS circuits including transmission gate, inverter, NAND, NOR gates, MUXEs, latches and registers. MOS transistor theory including threshold voltage and design equations. CMOS inverter's DC and AC characteristics along with noise margins. Circuit characterization and performance estimation including resistance, capacitance, routing capacitance, multiple conductor capacitance, distributed RC capacitance, multiple conductor capacitance, distributed RC capacitance, switching characteristics incorporating analytic delay models, transistor sizing and power dissipation. CMOS circuit and logic design including fan-in, fan-out, gate delays, logic gate layout incorporating standard cell design, gate array layout, and single as well as two-phase clocking. CMOS test methodologies including stuck-at-0, stuck-at-1, fault models, fault coverage, ATPG, fault grading and simulation including scan-based and self test techniques with signature analysis. A project of modest complexity would be designed to be fabricated at MOSIS.

Embedded Real Time Systems (Formerly 16.472)


Designing embedded real-time computer systems. Types of real-time systems, including foreground/background, non-preemptive multitasking, and priority-based pre-emptive multitasking systems. Soft vs. hard real time systems. Task scheduling algorithms and deterministic behavior. Ask synchronization: semaphores, mailboxes and message queues. Robust memory management schemes. Application and design of a real-time kernel. A project is required.


Pre-Reqs: EECE.2160 ECE Application Programming,EECE.3170 Microprocessor Sys Desgn I, EECE.3220 Data Structures.

Principles Of Solid State Devices (Formerly 16.474/EECE.4740)


This course introduces the operating principles of Solid State Devices. Basic semiconductor science is covered including crystalline properties, quantum mechanics principles, energy bands and the behavior of atoms and electrons in solids. The transport of electrons and holes (drift and diffusion) and the concepts of carrier lifetime and mobility are covered. The course describes the physics of operation of several semiconductor devices including p-n junction diodes (forward/reverse bias, avalanche breakdown), MOSFETs (including the calculation of MOSFET threshold voltages), Bipolar transistor operation, and optoelectronic devices (LEDs, lasers, photodiodes).


Pre-Req: EECE.3650 Electronics I.

Operating Systems (Formerly 16.481/EECE.4810)


Covers the components, design, implementation, and internal operations of computer operating systems. Topics include basic structure of operating systems, Kernel, user interface, I/O device management, device drivers, process environment, concurrent processes and synchronization, inter-process communication, process scheduling, memory management, deadlock management and resolution, and file system structures. laboratories include examples of components design of a real operating systems.


Pre-req: EECE.2160 ECE Application Programming, and EECE.3170 Microprocessor System Design I, and EECE.3220 Data Structures, or Permission of Instructor.

Computer Architecture and Design (Formerly 16.482/EECE.4820)


Structure of computers, past and present: first, second, third and fourth generation. Combinatorial and sequential circuits. Programmable logic arrays. Processor design: information formats, instruction formats, arithmetic operations and parallel processing. Hardwired and microprogrammed control units. Virtual, sequential and cache memories. Input-output systems, communication and bus control. Multiple CPU systems.


Pre-Reqs: EECE 3170 Microprocessor Sys Desgn I,EECE 2650 Intro Logic Design.

Network Design: Principles, Protocols & Applications (Formerly 16.483)


Covers design and implementation of network software that transforms raw hardware into a richly functional communication system. Real networks (such as the Internet, ATM, Ethernet, Token Ring) will be used as examples. Presents the different harmonizing functions needed for the interconnection of many heterogeneous computer networks. Internet protocols, such as UDP, TCP, IP, ARP, BGP and IGMP, are used as examples to demonstrate how internetworking is realized. Applications such as electronic mail and the WWW are studied.


Pre-req: EECE.3220 Data Structures.

Computer Vision and Digital Image Processing (Formerly 16.484/EECE.4840)


Introduces the principles and the fundamental techniques for Image Processing and Computer Vision. Topics include programming aspects of vision, image formation and representation, multi-scale analysis, boundary detection, texture analysis, shape from shading, object modeling, stereo-vision, motion and optical flow, shape description and objects recognition (classification), and hardware design of video cards. AI techniques for Computer Vision are also covered. Laboratories include real applications from industry and the latest research areas.


Pre-req; EECE 2160 ECE Application Programming, and EECE 3620 Signals and Systems or Permission of Instructor.

Fundamentals of Network and Cyber Security


This course will cover two categories of topics: One part is the fundamental principles of cryptography and its applications to cyber & network security in general. This part focuses on cryptography algorithms and the fundamental cyber & network security enabling mechanisms. Topics include cyber-attack analysis and classifications, public key cryptography (RSA, Diffie-Hellman), secret key cryptography (DES, IDEA), Hash (MD2, MD5, SHA-1) algorithms, key distribution and management, security handshake pitfalls and authentications, and well-known cyber & network security protocols such as Kerberos, IPSec, SSL/SET, PGP & PKI, WEP, etc. The second part surveys unique challenges and the general security & Privacy solutions for the emerging data/communication/information/computing networks (e.g., Ad Hoc & sensor network, IoTs, cloud and edge computing, big data, social networks, cyber-physical systems, critical infrastructures such as smart grids and smart transportation systems, etc.).


Pre-req: EECE.2460 Intro to Data Communication Networks, or EECE.4830 Network Design: Principles, Protocols and Applications, or Permission of Instructor.

Fiber Optic Communication (Formerly 16.490)


Optical fiber; waveguide modes, multimode vs single mode; bandwidth and data rates; fiber losses; splices, couplers, connectors, taps and gratings; optical transmitters; optical receivers; high speed optoelectronic devices; optical link design; broadband switching; single wavelength systems (FDDI, SONET, ATM); coherent transmission; wavelength division multiplexing and CDMA; fiber amplifiers.


Pre-Reqs: EECE 3600 Emag Theory I, EECE 3620 Signals & Systems I or Instructor permission.

Capstone Project (Formerly 16.499)


The objective of this course is to execute the project defined in Capstone Proposal. The design of the project will be completed, prototyped, tested, refined, constructed and delivered to the client. Practical experience will be gained in solving engineering problems, designing a system to meet technical requirements, using modern design elements and following accepted engineering practices. Students will work in a team environment and deliver the completed system to the project client. Proper documentation of activities is required.


Pre-Req: EECE.3991 Capstone Proposal.

Sat, 16 Jan 2016 11:08:00 -0600 en text/html
Killexams : Genetic Counseling Program Course Descriptions

Foundations of Genetic Counseling II
Course Number: GCFGC 63002 DLECT
(Credits: 3, Spring)
Course Director: Daniel Riconda, MS, CGC
Course Description: This course is designed to prepare students for their clinical rotations. Emphasis will be on learning to effectively communicate a broad spectrum of genetic concepts to patients. This includes communicating both orally and in writing information about genetic disorders, procedures, laboratory tests, and risks. Students will practice oral presentation skills and develop patient education aids, which they will use in directed role-plays. They will build upon the skills obtained in Foundations of Genetic Counseling I and will learn how to facilitate decision making, conduct psychosocial assessments, practice critical thinking, and employ ethical practice in genetic counseling. They will also build upon their initial introduction to prenatal, pediatric, adult, cancer, and laboratory practice areas.

Medical Genetics II
Course Number: GCMEG 63002 DLEOL
(Credits 3, Spring)
Course Director: Lindsay Burrage, M.D., Ph.D. & Pilar Magoulas, MS, CGC
Course Description: This course is designed for genetic counseling students in their first year of training. This course provides an overview of genetic disorders encountered in prenatal genetics, pediatric genetics and, adult genetics, as well as advanced Topics in biochemical genetics. An emphasis will be placed on etiology, diagnosis, prognosis, differential diagnosis, and management of these disorders. This course will be taken in sequence with Medical Genetics I with both live and pre-recorded lectures. This course will combine didactic lectures with case studies, problem sets, quizzes, short presentations by the students, and direct patient and parent interaction to reinforce Topics presented in the lectures. For example, there are three hours per week: One hour will be live, one hour will be video and one hour will include a combination of Topic reviews, assignments, quizzes, an short presentations.

Medical Ethics
Ethics Course Number: GCETH 62201 DLECT
(Credits 2, Spring)
Course Director: Christi Guerrini, JD, MPH
Course Description: This course introduces students from the School of Health Professions and the School of Medicine to basic concepts and terms of clinical ethics and to use of the Ethics-Work-Up to resolve clinical ethics cases. The course is comprised of didactic lectures for all learners (live and pre-recorded), small group sessions with a genetic counseling focus, and clinical ethics rounds. Topics covered include professionalism, confidentiality and privacy, informed consent, decision-making capacity, end-of-life decision making, health policy and responsible resource management, and ethical issues in human subject research.

Ethical and Legal Issues in Human Genetics: Ethics
Course Number: GCELI 61000 DLECT
(Credit 1, Spring)
Course Director: Elizabeth Mizerik, MS, CGC and Abigail Yesso, MS, CGC
Course Description: This course focuses on the legal and ethical issues in the practice of genetic counseling and clinical genetics. The NSGC Code of Ethics will also be explored and applied to clinical and research case scenarios. Through the exploration of Topics such as eugenics, incidental findings through genetic testing including non-paternity and consanguinity, genetic privacy and GINA, and prenatal testing/PGT, students will begin to appreciate ethical considerations and ethical decision making within the scope of clinical practice.

Fundamentals in Epidemiology
Course Number: GCFEP 62000 DLECT
(Credits 2, Spring)
Course Co-Directors: Michael Scheurer, Ph.D. & Philip Lupo, Ph.D.
Course Description: This course introduces the basic principles and methods of epidemiology, with an emphasis on critical thinking, analytic skills, and application to clinical practice and research. Topics include outcome measures, methods of adjustment, surveillance, quantitative study designs, and sources of data. The course is designed for professionals intending to engage in, collaborate in, or interpret the results of epidemiological research as a substantial component of their career.

Genetic Epidemiology and Population Genetics
Course Number: GCEPG 61000 DLECT
(Credits 1, Spring)
Course Director: Philip Lupo, Ph.D. & Melissa Richard, Ph.D.
Course Description: This introductory level course in genetic epidemiology will build upon the Topics covered in foundations in epidemiology with a focus on the design of studies to identify disease-gene associations. The lectures concentrate on common study designs for genetic association studies, including case-control studies, cohort studies, and parent-offspring trios. There is a focus on epidemiologic approaches for genetic studies of non-Mendelian diseases, disease-gene associations, and maternal genetic effects. Students will learn about study design and data analysis through class lectures, independent readings, and related projects.
The objectives of this course are to provide the student with an understanding of complex genetic diseases; population genetics; common designs for studies of disease-gene association; and approaches for assessing maternal genetic effects. At the conclusion of the course, students will be able to design case-control and family-based studies to detect disease-gene associations and should have an understanding of the various statistical approaches that can be used to analyze the resulting data.

Thesis I
Course Number: GCTHE 81001 DLECT
(Credits 1, Spring)
Course Director: Sarah Scollon, MS, CGC
Course Description: This course will continue the work begun in Research Methods in Genetic Counseling. The course is designed to prepare students for submission of their thesis projects. This course will provide the framework for development of strong thesis projects from evaluation of ideas through execution of the project to publication of the data. Students will learn about writing human research protocols, obtaining informed consent, developing research projects, study design, and presentation of research in the form of abstracts and posters. Through this course, students will present ideas and outlines of their thesis project for evaluation by their instructors and peers and will submit a protocol to the IRB for their thesis project. Thesis Advisory Committee members will be identified and thesis proposal will be presented to class and advisors for candidacy.

Psychosocial Practicum I
Course Number: GCPSP 62001 DLECT
(Credits: 2, Spring)
Course Co-Directors: Salma Nassef, MS, CGC; Patti Robbins-Furman, MPH, CGC; & Tammy Solomon, MS, CGC
Course Description: This course is designed to introduce and expand on various concepts pertaining to psychosocial aspects of a genetic counseling session. This will be a combined class incorporating both first and second-year genetic counseling students. Students will learn through didactic lectures, group discussion, role plays, interactive sessions, and reflective exercises. Through the exploration of Topics such as ethics, cultural competency, difficult patients, and autonomy, students will be able to develop skills specific to clinical practice.

Journal Club II
Course Number: GCJOC 61002 DLECT
(Credit 1, Spring)
Course Co-Directors: Tanya Eble, MS, CGC & Lauren Desrosiers, MS, CGC
Course Description: This course covers a review of current literature relating to advancements in genetic counseling, including the risk, diagnosis, and management of genetic diseases. Through this course, students will be able to: 1) review published literature and summarize significant findings, 2) analyze and critically evaluate data from the literature, and 3) present relevant data to provide an overview of key findings published in the literature.

Clinical Practicum II (for site listings, see Clinical Practicum I, First-Year, Fall)
Course Number: GCCLP 72002 CPRAC
(Credits 2, Spring)
Course Co-Directors: Salma Nassef, MS, CGC
Course Description: Students will rotate through three clinical sites for 6-week blocks. During this semester students begin to take on additional case responsibilities. These responsibilities may include case preparation, including review of the medical records and literature, obtaining family, medical and pregnancy histories, providing inheritance counseling, presenting cases to the medical staff, participating in case conferences, and composing counseling letters.

Laboratory Course
Course Number: GCLAB 71000 DLELA
(Credits: 1, Spring I)
Course Co-Directors: Ning Liu, PhD & Nicole Owen, PhD
Course Description: This course is designed for genetic counseling students at the end of their first year of training. Through this course students will become familiar with current molecular, biochemical, and cytogenetic techniques. Additionally, through this course students will understand the basics of the role of a laboratory genetic counselor, processes to enhance communication with the laboratory, and the distinctive role of the diagnostic laboratory in patient care.

Thu, 17 Dec 2020 21:22:00 -0600 en text/html
A00-212 exam dump and training guide direct download
Training Exams List