Since graduating with a degree in biology, Lisa Magloff has worked in many countries. Accordingly, she specializes in writing about science and travel and has written for publications as diverse as the "Snowmass Sun" and "Caterer Middle East." With numerous published books and newspaper and magazine articles to her credit, Magloff has an eclectic knowledge of everything from cooking to nuclear reactor maintenance.
Enterprise IT architect certifications appear most often at the apex of certification programs, where less than 1% of IT professionals ultimately ascend. Even so, many IT architect certifications are available, and you don’t need to invest in one certification sponsor’s vision to reach the top.
Many IT certifications in this area fall outside vendor umbrellas, which means they are vendor-neutral or vendor-agnostic. Nevertheless, the number of vendor-specific IT certifications exceeds vendor-neutral ones by a factor of more than 2 to 1. That’s why we devote the last section of this article to all such credentials, as we encountered them in search of the best enterprise architect certifications.
For IT pros who’ve already invested in vendor-specific certification programs, credentials at the architect level may indeed be worth pursuing. Enterprise architects are among the highest-paid employees and consultants in the tech industry.
Enterprise architects are technical experts who are able to analyze and assess organizational needs, make recommendations regarding technology changes, and design and implement those changes across the organization.
The national average salary per SimplyHired is $130,150, in a range from $91,400 to a whopping $185,330. Glassdoor reports $133,433 as the average. Ultimately, the value of any IT certification depends on how long the individual has worked and in what part of the IT patch.
Becoming an enterprise architect is not easy. While the requirements may vary by employer, most enterprise architects have a bachelor’s degree or higher in a computer-related field along with 5-10 years of professional work experience. Many enterprise architects obtain additional certifications past graduation.
Certifications are a great way to demonstrate to prospective employers that you have the experience and technical skills necessary to do the job and provide you a competitive edge in the hiring process. Certification holders also frequently earn more than their uncertified counterparts, making certifications a valuable career-building tool.
Below, you’ll find our top five certification picks. Before you peruse our best picks, check out the results of our informal job board survey. Data indicates the number of job posts in which our featured certifications were mentioned on a given day. The data should provide you an idea of the relative popularity of each of these certifications.
|AWS Certified Solution Architect (Amazon Web Services)||1,035||464||2,672||240||4,411|
|ITIL Master (Axelos)||641||848||1,218||1,119||3,826|
|TOGAF 9 (The Open Group)||443||730||271||358||1,802|
|Zachman Certified – Enterprise Architect (Zachman)||86||107||631||252||1,076|
Making its first appearance on the leaderboard is the Certified Solutions Architect credential from Amazon Web Services (AWS). AWS, an Amazon subsidiary, is the global leader in on-demand cloud computing. AWS offers numerous products and services to support its customers, including the popular Amazon Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2). AWS also offers numerous cloud applications and developer tools, including Amazon Comprehend, Amazon SageMaker Batch Transform and Amazon Lightsail.
AWS offers certifications at the foundation, associate and professional levels across five role-based categories: architect, developer, operations, cloud and specialty certifications. Foundation-level certifications validate a candidate’s understanding of the AWS Cloud and serve as a prerequisite to AWS specialty certifications. Foundation certifications are a recommended starting place for those seeking higher-level credentials.
Associate credentials typically have no prerequisites and focus on technical skills. They are required to obtain professional-level certifications, which are the highest level of technical certification available. Specialty certs, meanwhile, focus on skills in targeted areas.
AWS currently offers the following credentials:
The AWS Certified Solutions Architect credential is available at the associate and professional levels. The associate credential targets candidates with at least one year of experience architecting and implementing solutions based on AWS applications and technologies. AWS updated the associate-level exam in February 2018 to include architecture best practices and new services.
The AWS Certified Solutions Architect – Professional certification targets senior AWS architects who can architect, design, implement and manage complex enterprise-level AWS solutions based on defined organizational requirements. Candidates should have a minimum of two years’ direct experience deploying and designing on the AWS cloud and be able to translate organizational requirements into solutions and recommend best practices. The associate credential is a mandatory prerequisite.
|Certification name||Certified Solution Architect – Associate
Certified Solution Architect – Professional
|Prerequisites and required courses||Associate: One year of hands-on experience recommended, AWS Certified Cloud Practitioner
Professional: Certified Solution Architect – Associate credential plus a minimum of two years of hands-on experience
|Number of exams||Associate: One exam (65 questions, 130 minutes to complete)
Professional: One exam (170 minutes to complete)
|Certification fees||Associate: $150 (practice exam $20)
Professional: $300 (practice exam $40)
|Self-study materials||AWS makes demo questions, practice exams, exam guides, whitepapers and more available on the certification home page.|
CTA: Certified Technical Architect
In 1999, Salesforce revolutionized the world of CRM when it introduced the concept of using the cloud to provide top-notch CRM software. Today, Salesforce has more than 150,000 customers, making it the industry leader for CRM enterprise cloud platforms. Currently, Salesforce offers solutions for various focus areas, including sales, service, marketing, commerce, engagement, community, productivity (Quip), platform and ecosystem, integration, analytics, enablement, internet of things (IoT), artificial intelligence, mobility, and industry (financial and health).
To meet industry needs for qualified and experienced professionals with the skills necessary to support its growing customer base, Salesforce developed and maintains a top-tier certification program. It offers many paths to candidates, including for administration, app building, architecture and marketing.
Salesforce Architect certifications are hierarchical, with most (but not all) lower-level credentials serving as prerequisites for more advanced credentials. At the top of the certification pyramid is the highest credential a Salesforce professional can earn – the Certified Technical Architect (CTA), which is our featured Salesforce certification.
The Salesforce Architect certification pyramid has three levels:
Salesforce requires CTAs to maintain current skills. Credential holders must pass maintenance module exams with each new product release cycle (typically in summer, winter and spring). While challenging to earn, the CTA is important for IT professionals who are serious about a Salesforce technologies career.
|Certification name||Certified Technical Architect (CTA)|
|Prerequisites and required courses||Salesforce Certified Application Architect and Salesforce Certified System Architect credential:
|Number of exams||One exam (four hours to complete; candidates must formulate, justify and present recommendations based on a hypothetical scenario to a review board)|
Retake fee: $3,000
|Self-study materials||Salesforce maintains links on the certification webpage to numerous review materials, including the online documentation, tip sheets, user guides, exam guide and outline, Architect Journey e-books, Trailhead trails, and the Salesforce Certification Guide.|
ITIL Master Certificate – IT Service Management
One of our favorite credential sets (and for employers as well, judging by job board numbers) is the ITIL for IT Service Management credentials from Axelos. Axelos is a global provider of standards designed to drive best practices and quality throughout organizations. ITIL (Information Technology Infrastructure Library) joined the Axelos family in 2013.
Axelos manages ITIL credentialing requirements and updates, provides accreditation to Examination Institutes (EIs), and licenses organizations seeking to use ITIL. In addition to ITIL certifications, Axelos offers credentials for Prince2 2017 (which includes Foundation, Practitioner and Agile qualifications), Prince2 Agile, Resilia, MSP, MoP, M_o_R, P30, MoV, P3M3 and AgileSHIFT.
ITIL is a set of well-defined and well-respected best practices that specifically target the area of IT service management. There are more than 2 million ITIL-certified practitioners worldwide. ITIL is perhaps the most widely known and globally adopted set of best practices and management tools for IT service management and support.
Axelos maintains a robust ITIL certification portfolio consisting of five ITIL credentials:
Axelos introduced ITIL 4 in early 2019. ITIL 3 practitioners should check the Axelos website frequently for updates about the transition to ITIL 4 and availability of the ITIL 4 transition modules.
The ITIL Master is the pinnacle ITIL certification, requiring experience, dedication, and a thorough understanding of ITIL principles, practices, and techniques. To gain the ITIL Master designation, candidates must have at least five years of managerial, advisory or other leadership experience in the field of IT service management. They must also possess the ITIL Expert certification. Once the skill and certification requirements are met, the real certification work begins.
Upon completing the prerequisites, candidates must register with PeopleCert, the sole approved Axelos Examination Institute, and submit an application. Next, candidates prepare and submit a proposal for a business improvement to implement within their organization. The proposal submission is followed by a “work package,” which documents a real-world project that encompasses multiple ITIL areas.
The work package (1) validates how the candidate applied ITIL principles, practices, and techniques to the project; and (2) documents the effectiveness of the solution and the ultimate benefit the business received as a result of the ITIL solution. Finally, candidates must pass an interview with an assessment panel where they defend their solution.
Axelos will soon be sponsoring 50 lucky people in their quest to obtain the ITIL 4 Master certification. You can register your interest in the program here.
|Certification name||ITIL Master Certificate – IT Service Management|
|Prerequisites and required courses||ITIL Expert Certificate: Five years of IT service experience in managerial, leadership or advisory roles|
|Number of exams||No exam required, but candidates must complete the following steps:
|Certification fees||$4,440 if all ITIL credits obtained through PeopleCert
$5,225 if some ITIL credits were obtained from other institutes
|Self-study materials||Axelos provides documentation to guide candidates in the preparation of proposal and work package submissions. Available documents include ITIL Master FAQs, ITIL Master Proposal Requirements and Scope, and ITIL Master Work Package Requirements and Scope.|
A leader in enterprise architecture, The Open Group’s standards and certifications are globally recognized. The TOGAF (The Open Group Architecture Framework) standard for enterprise architecture is popular among leading enterprise-level organizations. Currently, TOGAF is the development and architecture framework of choice for more than 80% of global enterprises.
TOGAF’s popularity reflects that the framework standard is specifically geared to all aspects of enterprise-level IT architectures, with an emphasis on building efficiency within an organization. The scope of the standard’s approach covers everything from design and planning stages to implementation, maintenance, and governance.
The Open Group offers several enterprise architect credentials, including TOGAF, Open CA, ArchiMate, IT4IT and the foundational Certified Technical Specialist (Open CTS).
The Open Group reports that there are more than 75,000 TOGAF-certified enterprise architects. At present, there are two TOGAF credentials: the TOGAF 9 Foundation (Level 1) and TOGAF 9 Certified (Level 2). (The TOGAF framework is currently based on version 9.2, although the credential name still reflects version 9.)
The TOGAF 9 Foundation, or Level 1, credential targets architects who demonstrate an understanding of TOGAF principles and standards. A single exam is required to earn the Level 1 designation. The Level 1 exam focuses on TOGAF-related concepts such as TOGAF reference models, terminology, core concepts, standards, ADM, architectural governance and enterprise architecture. The Level 1 credential serves as a steppingstone to the more advanced TOGAF Level 2 certification.
The TOGAF 9 Certified, or Level 2, credential incorporates all requirements for Level 1. Level 2 TOGAF architects possess in-depth knowledge of TOGAF standards and principles and can apply them to organizational goals and enterprise-level infrastructure. To earn this designation, candidates must first earn the Level 1 credential and pass the Level 2 exam. The Level 2 exam covers TOGAF concepts such as ADM phases, governance, content framework, building blocks, stakeholder management, metamodels, TOGAF techniques, reference models and ADM iterations.
Candidates wanting a fast track to Level 2 certification may take a combination exam, which covers requirements for both Level 1 and 2. Training is not mandatory for either credential but is highly recommended. Training classes run 2-5 days, depending on the provider and whether you’re taking the combined or single-level course. The Open Group maintains a list of approved training providers and a schedule of current training opportunities on the certification webpage.
|Certification name||TOGAF 9 Foundation (Level 1)
TOGAF 9 Certified (Level 2)
|Prerequisites and required courses||TOGAF 9 Foundation (Level 1): None
TOGAF 9 Certified (Level 2): TOGAF 9 Foundation (Level 1) credential
|Number of exams||Level 1: One exam (40 questions, 60 minutes, 55% required to pass)
Level 2: One exam (eight questions, 90 minutes)
Level 1 and 2 combined exam (48 questions, 2.5 hours)
|Certification fees||$320 each for Level 1 and Level 2 exams
$495 for combined Level 1 and Level 2 exam
Exams are administered by Pearson VUE. Some training providers include the exam with the training course.
|Self-study materials||A number of resources are available from The Open Group, including whitepapers, webinars, publications, TOGAF standards, the TOGAF Foundation Study Guide ($29.95 for PDF; includes practice exam), VCE exam (99 cents for PDF) and the TOGAF 9 Certified Study Guide (a combined study guide is available for $59.95). The Open Group also maintains a list of accredited training course providers and a calendar of training events.|
Zachman Certified – Enterprise Architect
Founded in 1990, Zachman International promotes education and research for enterprise architecture and the Zachman Framework. Rather than being a traditional process or methodology, the Zachman Framework is more accurately referred to as an “ontology.” Ontologies differ from a traditional methodology or process in that, rather than focusing on the process or implementation, they focus on the properties, types and interrelationships of entities that exist within a particular domain. The Zachman Framework ontology focuses on the structure, or definition, of the object and the enterprise. Developed by John Zachman, this framework sets a standard for enterprise architecture ontology.
Zachman International currently offers four enterprise architect credentials:
Zachman credentials are valid for three years. To maintain these credentials, candidates must earn continuing education credits (referred to as EADUs). The total number of EADUs required varies by certification level.
|Certification name||Enterprise Architect Associate Certification (Level 1)
Enterprise Architect Practitioner Certification (Level 2)
Enterprise Architect Professional Certification (Level 3)
Enterprise Architect Educator Certification (Level 4)
|Prerequisites and required courses||Level 1 Associate: Four-day Modeling Workshop ($3,499)
Level 2 Practitioner: None
Level 3 Professional: None
Level 4 Educator: Review all materials related to The Zachman Framework; Level 3 Professional recommended
|Number of exams||Level 1 Associate: One exam
Level 2 Practitioner: No exam; case studies and referee review required
Level 3 Professional: No exam; case studies and referee review required
Level 4 Educator: None; must develop and submit curriculum and course materials for review and validation
|Certification fees||Level 1 Associate: exam fee included as part of required course
Level 2 Practitioner: None, included as part of Level 1 required course
Level 3 Professional: Not available
Level 4 Educator: Not available
|Self-study materials||Live classroom and distance learning opportunities are available. Zachman also offers webcasts, a glossary, the Zachman Framework for Enterprise Architecture and reference articles.|
Beyond the top 5: More enterprise architect certifications
The Red Hat Certified Architect (RHCA) is a great credential, especially for professionals working with Red Hat Enterprise Linux.
The Project Management Professional (PMP) certification from PMI continues to appear in many enterprise architect job descriptions. Although the PMP is not an enterprise architect certification per se, many employers look for this particular combination of skills.
Outside of our top five vendor-neutral enterprise architect certifications (which focus on more general, heterogeneous views of IT systems and solutions), there are plenty of architect-level certifications from a broad range of vendors and sponsors, most of which are vendor-specific.
The table below identifies those vendors and sponsors, names their architect-level credentials, and provides links to more information on those offerings. Choosing one or more of these certifications for research and possible pursuit will depend on where you work or where you’d like to work.
<td”>EMC Cloud Architect Expert (EMCCAe) <td”>GoCertify </td”></td”>
|Sponsor||Enterprise architect certification||More information|
|BCS||BCS Practitioner Certificate in Enterprise and Solutions Architecture||BCS homepage|
|Cisco||Cisco Certified Architect (CCAr)||CCAr homepage|
|Enterprise Architecture Center of Excellence (EACOE)||EACOE Enterprise Architect
EACOE Senior Enterprise Architect
EACOE Distinguished Enterprise Architect EACOE Enterprise Architect Fellow
|EACOE Architect homepage|
|FEAC Institute||Certified Enterprise Architect (CEA) Black Belt
Associate Certified Enterprise Architect (ACEA) Green Belt
|FEAC CEA homepage|
|Hitachi Vantara||Hitachi Architect (three tracks: Infrastructure, Data Protection, and Pentaho Solutions)
Hitachi Architect Specialist (two tracks: Infrastructure and Converged)
|Training & Certification homepage|
|IASA||Certified IT Architect – Foundation (CITA-F)
Certified IT Architect – Associate (CITA-A)
Certified IT Architect – Specialist (CITA-S)
Certified IT Architect – Professional (CITA-P)
|National Instruments||Certified LabVIEW Architect (CLA)||CLA homepage|
|Nokia||Nokia Service Routing Architect (SRA)||SRA homepage|
|Oracle||Oracle Certified Master, Java EE Enterprise Architect Certified Master||Java EE homepage|
|Red Hat||Red Hat Certified Architect (RHCA)||RHCA homepage|
|SOA (Arcitura)||Certified SOA Architect||SOA Architect homepage|
These architect credentials typically represent pinnacle certifications within the programs to which they belong, functioning as high-value capstones to those programs in many cases. The group of individuals who attain such credentials is often quite small but comes with tight sponsor relationships, high levels of sponsor support and information delivery, and stratospheric salaries and professional kudos.
Often, such certifications provide deliberately difficult and challenging targets for a small, highly select group of IT professionals. Earning one or more of these certifications is generally the culmination of a decade or more of professional growth, high levels of effort, and considerable expense. No wonder, then, that architect certifications are highly regarded by IT pros and highly valued by their employers.
Enterprise architect credentials will often be dictated by choices that your employer (or industry sector, in the case of government or DoD-related work environments) have already made independent of your own efforts. Likewise, most of the vendor-specific architecture credentials make sense based on what’s deployed in your work environment or in a job you’d like to occupy.
Though there are lots of potential choices IT pros could make, the actual number they can or should make will be influenced by their circumstances.
Today at the Open Hardware Summit in Portland, Alicia Gibb and Michael Weinberg of the Open Source Hardware Association (OSHWA) launched the Open Source Hardware Certification program. It’s live, and you can certify your own hardware as Open Hardware right now.
Open Source Hardware can’t be defined without first discussing open source software. At its very core, open source software is just a copyright hack, enabled by a worldwide universal computer network. The rise of open source software is tied to the increasing ease of distributing said software, either through BBSes, Usenet, and the web. Likewise, Open Source Hardware is tied to the ease of distributing, modifying, and building hardware.
In the 1980s, there were no services that could deliver a custom circuit board to anywhere on the planet for a dollar per square inch. When open software began, CNC machines were expensive tools, now you can build a very good machine for just a week’s wages. We are currently living at the dawn of Open Source Hardware, enabled by the creation of Open Source design tools that have themselves been used to create physical tools. Inexpensive 3D printers, open source oscilloscopes, circuit board plotters, and the entire hackerspace movement are as revolutionary as the Internet. These devices and the Internet are the foundations for Open Hardware and software, respectively. The objections to why hardware is incompatible with Open Source no longer apply and small-scale manufacturing techniques are only going to get better.
Open source is a moral imperative in the truest Kantian sense of the word. It is a good unto itself. Of course, this means open source is also mind-numbingly prescriptivist. Holy scrolls have defined dozens of different open source licenses. The relevant license for Open Source Hardware has already been laid out to define the freedoms and responsibilities of all Open Source Hardware creators. Open Source Hardware is a tangible thing, from a laptop to a lampshade, whose design is available so anyone can make, modify, distribute, and sell that thing. Native documentation is required, and software required to run this thing must be based on an OSI-approved license.
The definition of Open Source Hardware has been around for a few years now, and since then the community has flourished, there’s a great gear logo, and you can buy real, functional hardware that bills itself as Open Source Hardware. It’s become a selling point, and this has become a problem.
Many hardware creators don’t adhere to the definition of Open Source Hardware. In some cases, the design files simply aren’t available. If they are, they could be unmodifiable. The software used to create these design files could cost thousands of dollars per seat. This is the problem the movement faces — Open Source Hardware must have a certification program. Unlike open source software, where the source is almost proof enough that a piece of software complies with an open source license, hardware does not have such obvious assurances.
All software is closed by default. Anything written is covered by copyright, and the developers of open source software choose to license their works under an open source license. Open source software, then, is a copyright hack, enabled because all software is closed by default.
Hardware, on the other hand, is open by default. If you build a device to automatically inject epinephrine intramuscularly, you must go out of your way to patent your device. Only a patent will provide you the ability to license your work, and before that patent is published anyone can make their own epinephrine pen. If you build something with an FPGA, the code that programs the FPGA is covered by copyright, but an arbitrary circuit that uses that FPGA isn’t. Any generic piece of Open Source Hardware could be covered under patents, trademarks, and a dozen licenses. Therefore, an Open Source Hardware license is impractical. This is why OSHWA is not releasing an Open Source Hardware license, and instead creating an Open Source Hardware certification program. No Open Source Hardware license could cover every edge case, and a certification is ultimately the only solution.
At last year’s Open Hardware Summit, OSHWA formally announced the creation of the Open Hardware Certification program. Now, this program is live, and the certification database will growing very, very quickly. At its heart, the Open Source Hardware Certification program is pretty simple — create hardware that complies with the community definition of Open Source Hardware.
The theoretical basis for the need of an Open Source Hardware license is the fact that anyone is able to manufacture hardware. Of course, there are limits to technology and no one has a 14nm silicon fab line in their garage. This is a problem for any piece of Open Source Hardware, and the technical capability for anyone to recreate integrated circuits and other high technologies is the sole source of the traditional objections to any open hardware license. Garage-based fabrication is always improving, though, but closed hardware in the form of NDA’d chips will remain a problem for years to come.
The clearest example of the problem with closed-source chips is bunnie’s Novena laptop. This laptop is designed as both a hacker’s laptop and an artifact of Open Hardware. Although most of the chips used in the Novena are available without signing NDAs, open source, and blob-free 3D graphics acceleration was unavailable when the laptop launched. This non-open graphics problem will be fixed with open source drivers, but it does illustrate the problem of Open Source Hardware. Even though chips might be available, there might be binary blobs required for full functionality. You can build an Open Hardware chip in VHDL, but it’s not really open if you have to use closed-source FPGA dev tools.
OSHWA’s solution to this problem is simply asking for hardware creators to act in good faith. The certification program won’t knock points off for using closed source binary blobs if that’s the only way of doing something. Open Source Hardware is just slightly more aware of the pace of technical progress, and what is closed today may be open tomorrow. Building a piece of Open Source Hardware isn’t an all or nothing proposal; just provide your best effort to make it open, and technology or reverse engineers will probably make it more open in the future.
Of course, with any certification program, there must be some effort given to enforcement. If an Open Hardware project is certified under the program but does not meet the guidelines of the certification program, fines may be levied against the project creators. Again, good faith of the project creator is assumed, and a project found not in compliance with the certification program will be given 90 days to either fix the problem or remove the project from the certification program. After 90 days, there’s a 120-day period of public shaming, and after that small fines of $500 per month. The worst offender will get a fine of up to $10,000 per month, but that would require years of non-compliance, and it’s very doubtful any conflict with OSHWA will ever reach that stage. It should be noted these fines have a legal basis in the trademark of the OSHW certification logo, and if you don’t use the OSHW logo or certify your project, there’s nothing OSHWA can do.
The old Open Source Hardware ‘gear’ logo — unquestionably a better logo — will still remain in use, and no one is going will look down on you for using it. Using the trademarked OSHW logo, though, is the only way any certification program can be enforced.
Of course, the Open Source Hardware Certification program has been more than two years in the making, and that’s time enough for a few people to start having very strong opinions about it. A few years ago, Saar Drimer of Boldport said he won’t be using the Open Source Hardware logo on his boards. This is despite the fact that he loves Open Source Hardware, has written open source PCB design software, and offers a 20% discount on open source contract work. His reason is simple: adding a logo brings baggage, and building Open Source Hardware is not mutually exclusive with putting a logo on a board. Dave Jones is a big supporter of Open Hardware, but he realizes the famous gear logo is becoming meaningless through abuse.
You need only look back on the last twenty or thirty years of the world of Open Source Software to get a sense of where Saar and Dave are coming from; Stallman does not believe in a moral imperative to Open Hardware, whereas most everyone in attendance of today’s Open Hardware Summit does. Gnome versus KDE is nothing compared to the religious war we potentially face between various Open Hardware philosophies. The Open Source Hardware community is relearning what the open source software community learned twenty years ago. We can only hope to learn from their missteps.
But Open Source Hardware has a much bigger obstacle to adoption than politicking and empire building. Open source software is a simple concept — you have a (copy) right to whatever software, music, words, or boat hull designs you create. You can, therefore, provide others the right to use, study, share, and modify that work. Physical objects and artifacts do not have copyright, they have patents. Patent law in the United States is atrocious, and just because you were the first to create a useful invention doesn’t mean a patent would be invalidated. This is the greatest challenge to anything developed as Open Source Hardware. The only solution to this is prior art and patent inspectors that know where to look.
The Open Source Hardware Certification program is going to take a while to unravel. OSHWA doesn’t believe this certification program will be a repository used by patent inspectors looking for prior art. The legal basis for the certification is literally built upon every piece of intellectual property law. It is, perhaps, an answer to the most complex legal questions ever: what is property, what is intellectual property and can the concept of physical things be given away.
No one has an answer to these questions, or at least an answer that can be summed up in one-page FAQ. The Open Source Hardware Certification program is an attempt to answer these questions, and so far it’s the best attempt yet.
None of this matters unless the community gets behind it, and if another competing Open Source Hardware certification or license pops up, the community may very well migrate to that. Judging from the last thirty years of open source software license drama, we can only hope that the community figures this out the first time, and we hope this certification program is a rousing success.
The global digital ad market is expected to hit more than $209 billion by 2027. In fact, this rapid growth has meant that market research analysts and marketing specialists are among the country’s top 20 most sought-after employees, commanding an average salary just shy of $64,000, according to the Bureau of Labor Statistics.
In this article, we explain what digital marketers do and list the top digital marketing training providers whose courses may provide your career with a boost.
Digital marketers develop online marketing strategies for their clients to raise brand awareness and generate sales. They analyze data from previous campaigns to see what’s working well. This, in turn, helps them better understand how to maximize conversion rates (when a website visitor buys something, subscribes to a newsletter and so on).
Marketers rely heavily on social media platforms, such as Facebook and Twitter, to do their jobs, but they also make use of email and text message campaigns. In addition, marketers analyze web metrics and should be well versed in search engine optimization techniques and tools.
But digital marketing isn’t always about bringing in new customers or business; it’s also about connecting with the ones you already have. You use the same channels, such as social media, to stay in touch and keep customers current on what your company can do for them.
Many companies want to get the best result both online and offline and look for ways to blend the best of both. This is called an omnichannel marketing strategy.
The Meta Blueprint Certification program offers seven certifications for three different levels of proficiency.
The exams for these certifications cost between $99 and $150 each, but the training itself is free. Before taking them, however, you may want to take these free courses if you’re new to marketing on Meta’s platforms.
>> Learn More: Best Facebook Marketing Strategies: The Latest Tips
There are nine Google Ads certificates you can earn.
To take any Google exam means first signing up for the Google Partners program, which also lets you register for free training. From there, you can certify as an individual. The Google Ads certification is good for one year.
Geographic targeting of your Google ads is one of our 14 ways to improve your local marketing strategy.
The social media and platform company with the catchy name — Hootsuite — offers eight certifications. The Hootsuite Social Marketing certification covers core concepts related to social media marketing. Other certifications include Hootsuite Social Selling, Hootsuite Advanced Social Advertising, Hootsuite Advanced Social Media Strategy and a few specialty credentials.
Hootsuite encourages candidates to take a series of free online courses before they sit for the Social Marketing exam, which costs $199. The credential doesn’t expire. The certifications teach both beginner and advanced marketing skills for those who plan to advertise on social media sites. The self-paced lessons are done online with a 60-question examination given at the end of the course.
In our review of HubSpot, we found it to be the best CRM software for small businesses because of its all-around functionality. It’s great for coordinating inbound marketing and sales, and the company offers a bunch of training and certifications through HubSpot Academy. The HubSpot Content Marketing Certification recognizes professionals who create and promote content for the purpose of bringing in new customers. The associated course covers tips and best practices for building a content library of valuable assets. Other certifications include HubSpot Inbound Marketing Certification, HubSpot Email Marketing Certification and HubSpot Sales Software Certification.
To earn the HubSpot Content Marketing Certification, take the associated online course and then the exam. It’s all free. For details, see the FAQs.
The American Marketing Association Professional Certified Marketer (PCM) program takes a more formal approach to its certifications than other featured companies in this article. The organization created a body of knowledge for the PCM Digital Management certification, which includes subjects on planning, branding, pricing, public relations, social media and more.
A related credential through the American Marketing Association (AMA) is the Professional Certification in Digital Marketing. Sold in association with the Digital Marketing Institute, the course usually costs $2,060. Check to see when they have a sale on, because that price can go down to $1,442. A limited number of students are taken on at a time.
The following table lists top digital marketing certifications and the number of open positions on a single day that call for the certification specifically or experience with the technology. This isn’t a scientific analysis in which every job description is examined, but an overall glance at search numbers.
Open positions on SimplyHired, per day
Open positions on Indeed, per day
Hootsuite Social Marketing
HubSpot Content Marketing
PCM Digital Management
* includes searches for “Facebook Blueprint,” “Facebook Certified,” “Meta Ads” and “Meta Certified”
** includes searches for “Google Ads” and “Google AdWords”
The Adobe Qualified program offers four levels of training covering subjects such as web page creation and management, digital experience building, and how to analyze digital data and audience behaviors. The Get Started page shows you everything you need to know about becoming Adobe Certified.
Salesforce marketing certifications — specifically, the Salesforce Certified Marketing Cloud Consultant and Salesforce Certified Marketing Cloud Email Specialist course — may appeal to professionals who use Salesforce for marketing campaigns.
If you want to learn more about digital marketing on Twitter, check out Twitter Flight School offerings. Twitter doesn’t offer certifications at this time, but you can take free courses and earn badges for your efforts.
The Content Marketing Institute offers six courses to those who want to advance their skills in the field of content marketing. subjects covered include planning, audience, conversion and metrics. Once you’re finished with the self-paced lessons and all the quizzes, you will receive your certificate of completion. Enrollment costs $995 per student.
Market Motive offers another potential certification that you might want as part of beefing up your digital marketing credentials. Their platform has 10 courses currently, including a Masters in Digital Marketing as well as Complete Google Ads Professional. There are also courses in SEO, web analytics, content marketing, mobile marketing, pay-per-click and more. Prices range from $25 to $3,500 and include 180-day access.
Another option to consider is the Digital Marketing Institute. They offer the Professional Certification in Digital Marketing in partnership with the AMA, mentioned earlier in this article, and a comprehensive Certified Digital Marketing Expert at postgraduate level for $4,500-$6,500. They offer 19 courses in total, 13 of which are short courses at $445 on subjects like content marketing, social media marketing and e-commerce.
SMBs often benefit most from social media. The problem is that few owners have the time to learn the skills. Getting a qualification could be a stepping stone to starting your own social media marketing agency.
Mark Fairlie contributed to this article.
What first began as an agricultural research project at North Carolina State University eventually grew into a full-fledged software and services company by 1976. SAS has gone on to develop a solid customer base in the banking and pharmaceutical industries as well as in academia and at numerous agencies at all levels of government. Today, SAS is a leader in business analytics, data warehousing and data mining.
SAS has been recognized as one of the best places to work by organizations like Fortune and the Great Place to Work Institute. Coming in at No. 37, SAS made its 21st appearance in Fortune’s list of 100 best companies to work for in 2017 and No. 23 in Fortune’s list of top 100 best workplaces for millennials in 2018. Indeed, the company’s low turnover rate (4 percent in 2016) is an indicator of its commitment to its employees and, indirectly, to its customers as well.
Of the top 100 Fortune Global 500 companies, 96 are SAS customers. SAS customers span the globe with more than 83,000 instances installed in 144 countries.
SAS has awarded more than 100,000 certifications since the program’s introduction in 1999, according to Brightcove. Today, the SAS Global Certification Program offers 23 credentials across seven categories:
SAS certifications, along with required exams and costs, are described in more detail in the following sections. Although experience levels aren’t specifically indicated for each certification, a good rule of thumb is a minimum of eight months of experience on the base SAS system for Base Programmers and two to three years of relevant, hands-on experience for all other certifications before candidates tackle their respective exams.
All exams are administered by Pearson VUE or through a SAS-sponsored certification exam session (typically in conjunction with a training course). SAS also offers online proctored exams for all certification credentials through their partnership with Pearson VUE. Note that all certifications covered below are based on SAS 9.4.
Foundation Tools credentials aim at SAS professionals whose workdays revolve around writing and managing SAS programs. The company currently offers three Foundation Tools certifications:
|Certification||Required Exam(s)||Exam Cost*|
|SAS Certified Base Programmer for SAS 9||SAS Base Programming for SAS 9 exam (A00-211)||$180|
|SAS Certified Advanced Programmer for SAS 9||SAS Advanced Programming for SAS 9 exam (A00-212)
Must possess SAS Certified Base Programmer for SAS 9 credential
|SAS Certified Clinical Trials Programmer Using SAS 9||Clinical Trials Programming Using SAS 9 exam (A00-280)
Clinical Trials Programming Using SAS 9 – Accelerated Version exam (A00-281)
Requires the SAS Certified Base Programmer for SAS 9 credential
|$180 each exam|
* SAS offers a 50 percent discount on the cost of all exams to instructors, students, faculty and staff at schools and higher education institutions as well as to SAS employees. See the SAS FAQs for details.
The Advanced Analytics credentials are designed for SAS professionals who gather, manipulate and analyze big data using SAS tools, run reports and make business recommendations based on complex models. The certifications in this category include:
|Certification||Required Exam(s)||Exam Cost|
|SAS Certified Data Scientist Using SAS 9||No exam is required. Credential is awarded to candidates who possess the following two certifications:
SAS Certified Big Data Professional Using SAS 9 (2 exams, $180 each, $360 total)
SAS Certified Advanced Analytics Professional Using SAS 9 (3 exams, $610 total)
|SAS Certified Advanced Analytics Professional Using SAS 9||Predictive Modeling Using SAS Enterprise Miner 13 (Candidates with SAS Certified Predictive Modeler Using SAS Enterprise Miner 7, 13 or 14 do not need to take this exam.), $250
SAS Advanced Predictive Modeling (A00-225), $180
SAS Text Analytics, Time Series, Experimentation and Optimization (A00-226), $180
|SAS Certified Predictive Modeler Using SAS Enterprise Miner 14||Predictive Modeling using SAS Enterprise Miner 14 exam||$250|
|SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling||SAS Statistical Business Analysis Using SAS 9: Regression and Modeling exam (A00-240)||$180|
The Business Intelligence and Analytics credentials are designed for IT professionals who create interfaces and reports for SAS 9 or who use SAS Visual Analytics routinely. For the following certifications, there are no credential prerequisites required to take these exams, though a thorough knowledge of a number of related skills and techniques is required. The three certifications in this category are:
|Certification||Required Exam(s)||Exam Cost|
|SAS Certified BI Content Developer for SAS 9||SAS BI Content Development for SAS 9 exam (A00-270)||$180|
|SAS Certified Visual Business Analyst: Exploration and Design Using SAS Visual Analytics||SAS Visual Analytics 7.4 Exploration and Design exam (A00-277)||$180|
|SAS Certified Visual Modeler Using SAS Visual Statistics 7.4||SAS Interactive Model Building and Exploration Using SAS Visual Statistics 7.4 exam (A00-272)||$180|
Professionals whose workdays (or career aspirations) revolve more around managing data and platforms rather than deep statistics, analysis and modeling will gravitate to data management credentials. For the following certifications, there are no credential prerequisites required to take these exams, though a thorough knowledge of a number of related skills and techniques is required. The three certifications in this category are:
|Certification||Required Exam(s)||Exam Cost|
|SAS Certified Big Data Professional Using SAS 9||SAS Big Data Preparation, Statistics, and Visual Exploration exam (A00-220)
SAS Big Data Programming and Loading exam (A00-221)
|$180 each, $360 total|
|SAS Certified Data Integration Developer for SAS 9||SAS Data Integration Development for SAS 9 exam (A00-260)||$180|
|SAS Certified Data Quality Steward for SAS 9||SAS Data Quality using DataFlux Data Management Studio exam (A00-262)||$180|
The administration category has a single credential – the SAS Certified Platform Administrator for SAS 9 – designed for professionals responsible for supporting the SAS Business Analytics platform from installation through day-to-day maintenance. Candidates must know how to set up folders, manage user accounts, monitor system performance, apply security techniques, perform backups and complete other administrative tasks. The certification exam features 70 multiple-choice questions, a 110-minute time limit, and candidates must answer at least 70 percent of the questions correctly to pass the exam.
|Certification||Required Exam(s)||Exam Cost|
|SAS Certified Platform Administrator for SAS 9||SAS Platform Administration for SAS 9 exam (A00-250)||$180|
SAS JMP is data analysis and visualization software that allows users to explore, mine and share data analyses in a graphical format. The JMP credential includes two exams:
Both of these certification exams feature 50 to 60 multiple-choice and short-answer questions, a 150-minute time limit, and candidates must achieve a score of at least 725 points from the possible point range of 200 to 1,000 points. Find out more about scaled scores via the exam FAQ.
|Certification||Required Exam(s)||Exam Cost|
|JMP Certified Specialist: JMP Scripting Using JMP 14||JMP Scripting Using JMP 14 exam (A00-908)||$180|
|JMP Certified Specialist: Design and Analysis of Experiments Using JMP 14||Design and Analysis of Experiments Using JMP 14 (A00-909)||$180|
SAS offers credential programs for certified SAS resellers, VARs, and consultants though its partner program. There are six partner credentials available to SAS partners:
Access to the Partner credentialing portal is restricted to authorized SAS partners only. As a result, some details of the partner exam process are hidden from public view. If you work for a SAS partner, ask your company SAS liaison or your SAS sales team for more details about partner certifications.
SAS offers links to SAS classroom and eLearning courses, demo exam questions and full practice exams. Refer to the exam Preparation tab for each certification on the SAS Certification website. Candidates can purchase certification packages that include training courses, preparation materials and exam vouchers with typical discounts of 35 to 40 percent.
SAS training can be pricey, depending on factors such as delivery method and class length.
Individual courses range from lows around $1,100 to highs of $4,000. Candidates should be sure to check out the SAS Discounts web page for information on current discount programs, best value deals, veteran’s discounts and more before enrolling.
The SAS Training and Books webpage provides links to certification prep books, training courses, eLearning opportunities (SAS onDemand) and the SAS Global Academic Program. SAS also offers demo exam questions and training software may be accessed through the SAS University Edition.
Many colleges and universities, such as Philadelphia University, Florida State University and the University of Missouri, to name just a few, also offer SAS certificate programs to their undergraduate and graduate students. If you’re in (or thinking of going to) getting SAS certified as part of your degree program, it pays to check out your SAS certification options before choosing an institution of higher learning.
Ed is a 30-year-plus veteran of the computing industry, who has worked as a programmer, a technical manager, a classroom instructor, a network consultant and a technical evangelist for companies that include Burroughs, Schlumberger, Novell, IBM/Tivoli and NetQoS. He has written for numerous publications, including Tom’s IT Pro, and is the author of more than 100 computing books on information security, web markup languages and development tools, and Windows operating systems.
Earl is also a 30-year veteran of the computer industry, who worked in IT training, marketing, technical evangelism and market analysis in the areas of networking and systems technology and management. Ed and Earl met in the late 1980s when Ed hired Earl as a trainer at an Austin-area networking company that’s now part of HP. The two of them have written numerous books together on NetWare, Windows Server and other topics. Earl is also a regular writer for the computer trade press with many e-books, white papers and articles to his credit.
It’s true that the post-pandemic workforce has probably changed forever. According to accurate stats, 35% of the current workforce is still working remotely full-time and a significant chunk of employees are working a hybrid schedule. As we know, this is presenting all sorts of challenges to HR leaders who are working hard to engage an increasingly disjointed workforce.
However, one place where employees are open to more in-person interaction is at the gym — specifically, the corporate gym. At HealthFitness, we’ve seen an uptick in the number of our clients’ employees actively using personal and group training since the pandemic starting waning. And — here’s the surprising part — most of that is happening in-person at corporate fitness centers across the country. Eighty-six percent, to be exact (on the flip side just 5% of those personal and group training sessions are held virtual-only).
What’s more, employees are participating in an increasing number of these personal or group training sessions. Seventy-seven percent of our corporate client employees are signing up for 4 to 8 personal or group training sessions per month! That’s a big commitment — but employees are making it. And again, they’re largely doing it in-person.
The New Jersey Performing Arts Center (NJPAC), a non-profit multidisciplinary performing arts center and one of the nation's largest arts education providers, announces new fall classes at the Colton Institute for Research and Training in the Arts.
The Colton Institute for Training and Research in the Arts supports programs championing the whole child. Arts training, mentorship from working artists, career counseling, and a talent program that pays NJPAC Arts Education students and alums for performances across New Jersey are some of the initiatives advanced by the $10 million catalytic gift from Judy and Stewart Colton.
The 2023/24 schedule offers various classes on Saturdays ranging from Beginner Band, Hip Hop Arts & Culture, Acting, Musical Theater, and, new this year, Music Composition and Arranging. This class welcomes aspiring composers ages 14-19 who demonstrate promise and dedication early in their creative development. The program focuses on the fundamentals of composition through instruction, group activities and styles, the performance of students' works, and interaction with the Teaching Artist, Saxophonist, and Composer Lance Bryant. It prepares students for the next stage of their artistic journey just for $100 each semester. Students registered in TD Jazz for Teens are part of this class at no charge.
The Colton Institute increased NJPAC's arts education offerings. It advances its services for students — many of whom come from economically disadvantaged circumstances — including mentorship and field training, ultimately creating a pathway for college and career opportunities in the performing arts, whether onstage or behind the scenes working in entertainment in a corporate setting. To Register for a class, visit Click Here or send an email to firstname.lastname@example.org
Oct 7 – May 11 (break from Dec 23 – Jan 20)
10AM – 2PM
Arts High School, Newark
The Band Together program is designed to complement school band programs and students with an interest in learning a band instrument. Students meet every Saturday and have instruction in instrumental technique and music theory plus the opportunity to participate in an ensemble. In addition to a focus on traditional band literature, the program shares resources from the TD Jazz for Teens program to introduce jazz to students at every level of instruction.
Ages: 9 – 18
Tuition: $75 per year including instrument rental
Fall Semester: Oct 7 – Dec 16
Spring Semester: Jan 27 – May 18
10AM – 5PM (schedules vary based on placement)
Center for Arts Education, NJPAC
TD Jazz for Teens is a comprehensive and sequential jazz education program that develops well-rounded young performers through access to life-changing experiences. Students receive top-notch musical training and study with world-class working artists in courses including technique, theory and composition. The curriculum also includes rehearsals in large and small ensembles, private instruction, master classes with world-class musicians and GRAMMY Award-winning artists Christian McBride and Stefon Harris; vocal instruction and ensemble with jazz artist Jackie Jones; and a new composition and arranging class with saxophonist Lance Bryant. Students will have opportunities for artistic exchanges and performances within the community in addition to college and career exploration. Through participation in this hallmark program, students become more than musicians — they grow into exceptional people with confidence to take on the world.
Ages: 12 – 18
Tuition: $650 per semester; $1,100 for full year
The submission deadline for fall video auditions is Sun, Sep 24, by 11:59 PM.
For the spring semester, the deadline is Sat, Dec 9, by 11:59PM.
Includes Music Composition and Arranging class at 11am in Fall and Spring.
Fall Semester: Oct 7 – Dec 16
Spring Semester: Jan 27 – May 10
Tuition: $100 (for JFT enrolled students, this program is included)
Center for Arts Education, NJPAC
Music Composition and Arranging explores the art of music composition using the foundations of Western musical notation. This class welcomes aspiring composers ages 14-19 who demonstrate promise and dedication at early stages of their creative development. Through instruction, group activities and classes, performance of students' works, and interaction with Teaching Artist, Saxophonist and Composer Lance Bryant the program focuses on the fundamentals of composition and prepares students for the next stage of their artistic journey. Applicants are encouraged to explore all genres of music in their compositions. Applicants should be familiar with Western musical notation and should possess basic competency on an instrument, including voice. Students registered for Jazz for Teens do not need to register for this. This class is included in the program and based on their theory placement test.
Fall Semester: Oct 7 – Dec 16
Spring Semester: Jan 27 – May 11
10AM – 3PM
Center for Arts Education, NJPAC
Hip hop is an art that inspires everyone to be themselves and in Hip Hop Arts & Culture students learn ways to express their style, point of view and imagination! Hands-on experience and guidance from talented Teaching Artists are at the core of the program. Students develop emcee skills and learn how to express lyrical ideas through the mic. They practice sound selection and sampling by using technology to produce beats and learn dance choreography with an eye on the celebration of the 50th anniversary of hip hop. No previous experience required.
Ages: 10 – 18
Tuition: $500 per semester
Fall Semester: Oct 7 – Dec 16
10AM – 12PM
Center for Arts Education, NJPAC
Learn the magic behind staging a musical production! This program immerses students in song, dance and musical theater history in addition to the collaborative experience of writing an original script. Uncover the secrets of acting, learn about vocal technique and get moving with original choreography. Students and teaching artists work together to build skills and gain confidence.
Ages: 9 – 18
Spring Semester: Jan 27 – May 9
10AM – 3PM
Center for Arts Education, NJPAC
Learn the magic behind staging a musical production and then spotlight what you learn with a live performance before family and friends. This program immerses students in song, dance and scripted drama topped off by some musical theater history. Uncover the secrets of acting, learn about vocal technique and get moving with original choreography. This program is collaborative with students and teaching artists working together to end the semester with excitement — by staging a licensed show.
Ages: 9 – 18
Fall Semester: Oct 7 – Dec 16
1 – 3PM
Center for Arts Education, NJPAC
The only requirements for this course are the tools of body, voice and imagination. Students of all skill levels develop acting skills by working collaboratively with teaching artists on exploring scenes and writing and unpacking monologues. Students experience acting, movement, voice and more. Acting also builds a community and friends, parents and guardians come together on Family Day to celebrate what their students have learned. All levels are welcome to learn and explore. For the fall semester, Acting students can also register for the morning Musical Theater program.
Ages: 9 – 18
Spring Semester: Jan 27 – May 10
10AM – 3PM
Center for Arts Education, NJPAC
The only requirements for this course are the tools of body, voice and imagination. Students of all skill levels develop acting skills by working collaboratively with teaching artists on exploring scenes and unpacking and creating monologues. The thrilling culmination is an original production performed live on an NJPAC stage. All levels are welcome to learn and explore.
Ages: 9 – 18
There's more to explore! Participants have access to free add-on experiences.
In the Mix is a student-driven program where participants across disciplines collaborate and produce art with a purpose. With the support of teaching artists, students learn how to use their art to engage their communities in social justice activism. Make friends, make art and make a difference!
A mentor can make a world of difference! This virtual experience is free to registered students and alumni of NJPAC Arts Education training programs. Meet weekly with a professional artist to learn the fundamentals of a new art form or hone a craft, students direct the course of study. Be creative, be unstoppable!
This conversation series is for teens, alumni and emerging artists looking to pursue a career in the arts and entertainment industries. Professional creators working behind the scenes in music production, dance, theater and performance share their experiences and provide resources for attendees to jumpstart their careers.
These offerings are open to all parents, guardians and caregivers of students enrolled in Arts Training programs.
The Colton Institute for Research and Training: The Colton Institute for Training and Research in the Arts supports programs championing the whole child. Arts training, mentorship from working artists, career counseling, and a talent program that pays NJPAC Arts Education students and alums for performances across New Jersey are some of the initiatives advanced by the $10 million catalytic gift from Judy and Stewart Colton that supports arts education programming and research into new arts training techniques. The Colton Institute enables the Arts Center's continued growth as a national leader in advancing 21st-century arts education. NJPAC's dedication to arts education began more than 25 years ago — before the opening of the Arts Center's campus in 1997. It offers over 3,000 arts education classes, residencies, and workshops each season, reaching more than 100,000 students and families. To Register or for more information, visit Click Here.
Certainty and uncertainty play a big role in life.
It is said that the only true certainty consists of deaths and taxes. Michael Crichton, the famous writer, said that he was certain there is too much certainty in the world. Legendary poet Robert Burns indicated that there is no such uncertainty as a sure thing.
One thing about both certainty and uncertainty is that we seem to crave and relish certainty, while we tend to agonize over and strive to convert uncertainty into certainty if we can do so. As Carl von Clausewitz, the lauded military strategist professed: “Although our intellect always longs for clarity and certainty, our nature often finds uncertainty fascinating.”
All of these machinations over certainty and uncertainty turn out to be a big matter for those that wish to fruitfully make use of today’s generative AI such as ChatGPT, Bard, and so on.
In today’s column, I am continuing my ongoing special series about advances in prompt engineering, doing so this time with a particular focus on the crucial and often unexposed course concerning generative AI and the controversial matter of expressing certainty versus uncertainty in the essays and outputs being emitted by the AI. This course is likely something you might not have contemplated before. I assure you that it is a lot more important than the coverage or attention it has received to date.
Allow me to explain.
As background, realize that being able to write productive and effective prompts when using generative AI is paramount. A lousy prompt tends to generate lousy results out of generative AI. A wisely composed prompt can lead to stellar results out of generative AI. Knowing the vital keystones of prompt engineering is a prudent means to get your biggest bang for the buck when employing generative AI.
One issue that few realize exists until taking a reflective moment to ponder it is that most generative AI apps tend to exhibit an aura of immense certainty. You enter your prompt and typically get a generated essay or interactive dialogue that portrays the generative AI as nearly all-knowing. The sense that you get is that the generative AI is altogether confident in what it has to say. We subliminally fall into the mental trap of assuming that the answers and responses from generative AI are correct, apt, and above reproach.
The essays and interactive dialogue come across this way for two major reasons.
First, generative AI produces responses that often exude a semblance of certainty. If you ask whether Jack and Jill fell down the hill, you might get a reply by generative AI that says yes, they definitely did so. There isn’t any kind of qualification or hedging in the answer by the AI app. A human that is asked the same question might quality their response, such as saying that if you are referring to the famous nursery rhyme, indeed they fell down a hill. But if you are thinking of some other Jack and Jill, maybe they didn’t fall down a hill.
Second, as humans, we are conditioned to assume that if we don’t explicitly see suggestions of uncertainty, we tend to lean into the certainty camp. Suppose you are talking with someone, and they tell you that it is raining outside. All else being equal, you probably believe them and that it is a certainty that rain is in fact falling. Only if the person says they believe that it is raining (the word “believe” becomes a signal of less than certain), or they declare it might be raining (the word “might” is a strong signal of uncertainty), do you begin to consider the certainty versus uncertainty of what has been stated.
Generative AI typically does not include the signals and wording that would tip you toward thinking of how certain or uncertain a given response is. To clarify, I am not saying that generative AI will never provide such indications. It will do so depending upon various circumstances, including and especially the nature of the prompt that you have entered.
If you explicitly indicate in your prompt that you want the generative AI to emit a certainty or uncertainty qualification then you will almost certainly get such an indication. On the other hand, if your prompt only tangentially implies the need for an indication of certainty or uncertainty, you might get an output from the AI app that mentions the certainty considerations or you might not.
A rule of thumb is that generative AI is like a box of chocolates, namely that you never know for sure what the generative AI is going to produce or generate.
Another handy-dandy rule of thumb is that unless you bring up certainty or uncertainty in your prompt, the chances of having the generative AI by default include some indication of the certainty about a response is a wild throw of the dice.
Why does this matter to you?
Anyone using generative AI has got to awaken to the fact that often the response by the AI is going to be essentially a guess or approximation, even if the AI doesn’t directly state this condition when generating a reply. Your tendency to anthropomorphize the AI lulls you into thinking that the AI is giving you the correct answer. You assume that the answer has nearly absolute certainty. Only if perchance the reply state that there is some uncertainty underlying the response will you be mentally sparked into realizing that the reply ought to be given a concerted second glance.
Of course, there are limits to this implied assumption of certainty.
Imagine you ask the generative AI whether the sun will come up tomorrow. Suppose that the generated response is that the sun will not come up tomorrow. This is stated by the AI in a matter-of-fact manner, unequivocally, and appears to be an absolutely certain assertion. I suppose you might pack your bags and get ready for the world as we know it to somehow spin off into space. I doubt though that many of us would blindly accept the implied certainty of the AI response. Our commonsense kicks into gear at the seemingly preposterous claim that the sun won’t rise. We would undoubtedly ask the AI about this, and the odds are that the AI might sheepishly emit an indication that it was wrong about that whole thing of the sun not coming up tomorrow.
Here’s a remedy of a sort.
Had you asked the generative AI at the get-go to proffer an indication of certainty or uncertainty, at least you would have gotten some added wording to go along with the assertion about the sun. The additional wording might be helpful to you and keep your head in the game, causing you to mindfully assess whether the generative AI is on the up and up (you see, sometimes, generative AI is said to incur AI hallucinations, which I have examined at the link here, encompassing the AI making things up entirely).
Furthermore, and this is a mind bender, the very act of asking or telling the generative AI to include a certainty or uncertainty will often spur the generative AI to be less off-the-cuff and produce more well-devised results (for those of you that know about the use of prompting techniques such as chain-of-thought, that I’ve covered at the link here, research tends to suggest that these methods will prod the computational pattern-matching toward better results).
I trust that you are beginning to see where I am taking you on this journey about the latest in prompt engineering. A practical and highly prized technique of prompting involves stoking the generative AI toward including some indication about the certainty or uncertainty of the responses that are being emitted. You will be a lot better off by seeing wording or indications within the responses that clue you to the certainty or uncertainty involved. The idea is to turn something that right now is often omitted, hidden, or otherwise neglected, and make sure that it gets clearly onto the table and out in the open.
So that you can properly and appropriately devise prompts that stir the AI into providing certainty and uncertainty indications, I will provide you with useful ways to get this to happen. You are urged to try out the approaches and add them to your prompt engineering skillset. You’ll be happier and more informed if you do so.
Before I dive into the crux of this exciting approach, let’s make sure we are all on the same page when it comes to the keystones of prompt engineering and generative AI.
Prompt Engineering Is A Cornerstone For Generative AI
As a quick backgrounder, prompt engineering or also referred to as prompt design is a rapidly evolving realm and is vital to effectively and efficiently using generative AI or the use of large language models (LLMs). Anyone using generative AI such as the widely and wildly popular ChatGPT by AI maker OpenAI, or akin AI such as GPT-4 (OpenAI), Bard (Google), Claude 2 (Anthropic), etc. ought to be paying close attention to the latest innovations for crafting viable and pragmatic prompts.
For those of you interested in prompt engineering or prompt design, I’ve been doing an ongoing series of insightful looks at the latest in this expanding and evolving realm, including this coverage:
Anyone stridently interested in prompt engineering and improving their results when using generative AI ought to be familiar with those notable techniques.
Moving on, here’s a bold statement that pretty much has become a veritable golden rule these days:
If you provide a prompt that is poorly composed, the odds are that the generative AI will wander all over the map and you won’t get anything demonstrative related to your inquiry. Being demonstrably specific can be advantageous, but even that can confound or otherwise fail to get you the results you are seeking. A wide variety of cheat sheets and training courses for suitable ways to compose and utilize prompts has been rapidly entering the marketplace to try and help people leverage generative AI soundly. In addition, add-ons to generative AI have been devised to aid you when trying to come up with prudent prompts, see my coverage at the link here.
AI Ethics and AI Law also stridently enter into the prompt engineering domain. For example, whatever prompt you opt to compose can directly or inadvertently elicit or foster the potential of generative AI to produce essays and interactions that imbue untoward biases, errors, falsehoods, glitches, and even so-called AI hallucinations (I do not favor the catchphrase of AI hallucinations, though it has admittedly tremendous stickiness in the media; here’s my take on AI hallucinations at the link here).
There is also a marked chance that we will ultimately see lawmakers come to the fore on these matters, possibly devising and putting in place new laws or regulations to try and scope and curtail misuses of generative AI. Regarding prompt engineering, there are likely going to be heated debates over putting boundaries around the kinds of prompts you can use. This might include requiring AI makers to filter and prevent certain presumed inappropriate or unsuitable prompts, a cringe-worthy issue for some that borders on free speech considerations. For my ongoing coverage of these types of AI Ethics and AI Law issues, see the link here and the link here, just to name a few.
With the above as an overarching perspective, we are ready to jump into today’s discussion.
Foundations Of Certainty Versus Uncertainty
We will ease our way into the arena of certainty and uncertainty, doing so by first examining how humans convey certainty and uncertainty to each other. After we cover that aspect, we can then consider how a human interacting with generative AI is likely to act and react related to how the AI does or does not express certainty or uncertainty.
It is useful to first explore how humans do this when interacting with fellow humans. When we use generative AI, we tend to carry over our preexisting assumptions and habits about certainty that have been dutifully learned or naturally acquired throughout our lives on a human-to-human interaction basis.
I cover the matter in this way with a bit of erstwhile caution because I don’t want anyone to be led down the path of anthropomorphizing AI. In current times, AI is not sentient and should not be equated to the sentience of humans. I will do my best to make that same alert when we get into certain aspects of the generative AI details that might seem overly sentient-like.
Thanks for keeping a level head on these weighty matters.
Let’s begin with the notion that certainty or uncertainty can be in the mind of a person and it separately can exist as an expression communicated by a person:
Here’s what I mean.
You ask someone whether Humpty Dumpty fell off a wall. The person in their mind believes that Humpty Dumpty did indeed fall off of a wall. They are certain of this. Thus, the person then speaks to you and tells you that Humpty Dumpty did fall off a wall. They express this unequivocally. No doubt about it, poor old Humpty Dumpty fell off a wall.
Notice that the implicit sense of certainty matches the explicit or expressed sense of certainty.
Suppose that the same person was asked this very same question by a child. The person might worry that it will be unduly disturbing to the child if an absolute confirmation of Humpty Dumpty falling is conveyed to the child. The child might be dismayed at this revelation.
In this case, the implicit (in the mind of the person) is that Humpty Dumpty did fall. But, when telling the child, the person decides to sprinkle in a semblance of uncertainty, hoping this will soften the distress of the child to the upsetting discovery that Humpty Dumpty fell.
They answer this way: “Humpty Dumpty might have fallen, but I’ll tell you more when you get a bit older.”
Observe closely that the wording includes “might” which reduces the implied level of certainty. The door to uncertainty has been opened. Just a nudge. The implicit sense of certainty has not been precisely aligned with the explicit or expressed sense of certainty. Why did the person do this? You could suggest they were trying to be kind or polite. Some might take a dim view and argue that the person was misleading or maybe lying in their expressed answer. Anyway, that’s something we will come back around to momentarily.
An analytic person might have said this to the child: “There is a 50% chance that Humpty Dumpty fell, ergo there is also a 50% chance that Humpty Dumpty didn’t fall.” Admittedly, the child might not quite comprehend this. The gist though is that this introduces an even grander sense that the answer embodies uncertainty.
Imagine that a parent is standing there and they don’t like the answer that was given by the analytic person. The parent turns to the child and says this: “It is 100% the case that Humpty Dumpty fell.” Notice that this answer carries explicitly again an indication of certainty and does to the highest degree.
We can have these four kinds of categorical situations:
I’ve covered the first two categories in my discussion above. The third category is rather self-explanatory of someone in their mind believing that something is uncertain and they explicitly say so. The fourth category you’ve undoubtedly seen occur, whereby someone has uncertainty about something in their mind but nonetheless expresses that the matter is certain. We’ll use the child setting again. A child is worried that their dog ate bad food. The parent is uncertain of the fate of the dog. Despite this mental semblance, they reassure the child and tell them that they are certain the dog will be perfectly fine.
There is a lot of human behavioral research on how we conceive and communicate certainty and uncertainty.
For example, a research study entitled “The Role Of Certainty (And Uncertainty) In Attitudes And Persuasion” by Zakary Tormala, which appeared in Science Direct, 2016 indicates this about certainty and uncertainty related to human attitudes and persuasion (selected excerpts):
You could suggest that certainty propels us toward being more certain and more outwardly expressive of a matter at hand. The thing is, an abundance or overabundance of certainty can at times not be engaging. Research seems to say that a dose of uncertainty can cause greater engagement by others, presumably intrigued and wanting to aid in filling in the pieces of the puzzle.
I’ve also mentioned earlier in this discussion that the wording that we use can convey or explicitly communicate whether we want to impart a semblance of certainty or uncertainty to others. If you use words like “might” or “maybe” this can be a strident signal that there is uncertainty in the midst of things. The same can be said for using probabilities or percentages, such as stating that something is an 80% chance of happening and therefore a 20% chance of not happening.
Researchers in the realm of linguistic semantics have long examined the words that we use related to certainty and uncertainty. In a research study entitled “Strategic Use of (Un)certainty Expressions”, authored by Alexandra Lorson, Chris Cummins, and Hannah Rohde, that appeared in the Frontiers in Communication, March 2021, the paper indicates this:
All in all, I’ve now covered some of the essentials about the nature of humans and the ways in which we think of and communicate about certainty and uncertainty. I’m betting that you are eager to see how this comes to the fore when using generative AI.
Fasten your seatbelts, we are going to leap into the world of certainty and uncertainty entailing the use of generative AI and the generated outputs thereof.
Generative AI And Certainty Versus Uncertainty
The usual default by generative AI apps is to express any generated results in a somewhat certainty-oriented worded way. The wording might be rather subliminally worded to not mention anything about the certainty of what is being expressed. You are left to your own devices to interpret the generated result as being of a presumed certainty concoction.
You might ask whether the muffin man lived on Drury Lane. The reply by generative AI could be that Yes, the muffin man lived on Drury Lane. That’s the extent of the answer. You are likely to conclude that this is an answer of a full-on certainty magnitude. There is nothing in the answer that suggests or notes otherwise. The omission of uncertainty draws you toward an assumption of certainty.
Here’s an AI insider secret that might be surprising.
The AI maker of the generative AI app can pretty much set up the AI to be more explicit about the certainty or uncertainty of the generated results. They often don’t aim to do so. It could be that the AI maker is blissfully unaware that they have data-trained their generative AI in a manner that tends toward generating essays and interactions that omit any explicit indication about the certainty or uncertainty of the answers presented.
Another possibility is that the AI maker realizes that they have established the generative AI to appear to be certain most of the time, and the AI maker is happy with this. If users of the generative AI were to continually be bombarded with the generated results identifying all kinds of uncertainties, they might find this to be unappetizing. You would wonder what all this fuss over a simple answer. Just say yes or no, one might be thinking. Don’t waste time with oddities and exceptions.
In addition, if the wording was largely embedded with uncertainty cues, you might start to become suspicious of the generative AI as not being on the ball altogether. Your consternation might cause you to drift over to some other generative AI app that doesn’t spout out all those irritating uncertainties. An AI maker doesn’t want to lose their users due to the exposure of certainties and uncertainties that might rattle the confidence of their users.
There is also the claim that if people want to see certainties and uncertainties, they can always get this to happen of their own volition. People can simply provide prompts or otherwise instruct the generative AI to mention any certainties or uncertainties associated with the results being generated. Choose your own path, as they say. This allows the AI makers to be off-the-hook about why they aren’t by default ensuring that the generative AI always states certainties and uncertainties.
On top of that, generative AI will at times provide certainties and uncertainties without needing to be prompted to do so. If you ask a question or engage in subjects involving open questions, the odds are that the generative AI will include wording that showcases the lack of certainty underlying the matter. In that manner, it isn’t as though generative AI never offers uncertainties. There are notable odds that during any everyday interactive conversation with generative AI, you will receive phrasing that suggests or outrightly identifies uncertainties.
Some in the AI Ethics sphere have argued that the default for generative AI is that it should be set up to always add wording that alerts to uncertainties and overtly avoid emitting wording that implies absolute certainty. The logic for this is straightforward. People are readily misled when they see results that appear to be of a certainty wording. By seeding uncertainties intentionally, when warranted, people would be less lulled into always believing whatever generative AI emits. They would be accustomed to always being alerted that the results can be of an uncertain nature.
That debate continues to rage on.
For now, let’s consider how you can steer generative AI toward emitting certainty and uncertainty signals due to using suitable prompting strategies.
Getting Certainty And Uncertainty On The Table
You decide that you would like to have generative AI go ahead and let you know about certainties and uncertainties regarding the answers being produced.
There are five fundamental ways that this is conventionally done:
Let’s briefly explore those core approaches, one at a time.
(1) In general
As part of your prompt, you could try to ensure that the certainty/uncertainty will be conveyed by saying something like this:
This is a rather broad instruction.
It is unclear in what manner the AI will end up indicating any certainty/uncertainty elements. This is your blandest overarching line to get the generative AI into a mode of encompassing the certainty/uncertainty undercurrents. You might want to consider the other four approaches if you want to be more specific in how the AI will respond.
(2) Wording throughout
As part of your prompt, you can be relatively specific by getting the generative AI to include certainty/uncertainty indications throughout the wording that is emitted.
Do so by saying something like this in your prompt:
Notice that you are directing the generative AI to have some aplomb as to blending the certainty/uncertainty indications.
(3) At the start or end
You might want to have the certainties/uncertainties called out rather than blended into the overall generated response.
This makes sense. Sometimes you want to see the qualifications as their own distinctive indication. Seeing them throughout the response might be harder to discern what the concerns are or could be distracting to the ambiance of the response.
You can say something like this in your prompt:
(4) By special phrasing
Another route involves getting the generative AI to use phrases as an indicator of the certainties/uncertainties. This can be done via a prompt that uses a show-me strategy or a tell-me strategy, see my discussion about those prompting approaches at the link here.
In a tell-me, you instruct the generative AI:
In a show-me, you provide examples (if just one example it is known as a one-shot, while if using several examples it is known as a few-shot):
(5) By numeric scale
One of the most obvious ways to get the certainties/uncertainties out in the open is to require generative AI to produce such matters via a numeric scale. This might consist of probabilities or percentages. Use whatever numeric scale that you believe befits the circumstances.
Some might like to use a scoring scale of 0 to 1, conventionally arising when seeking probabilities. Some prefer to use percentages, such as the generative AI might indicate that a particular claim is 90% sure and 10% unsure. And so on.
Say something like this in your prompt:
Each of the above prompting examples should be honed to the particular generative AI app that you are using. Some generative AI apps will respond well to such wording, others might not. Experiment with your generative AI app until you land on wording about identifying certainties that seem to work well for you.
Reaching For The Moon When Prompting For Uncertainties
I’ve got a question for you.
Did mankind land on the moon?
I dare say that most people would say that yes, mankind has landed on the moon. This would seemingly be proven by the historic Apollo 11 mission and various other subsequent landings on the moon. Seems like an exceedingly straightforward question with an inarguable straightforward answer.
You likely are aware that some people believe that we didn’t land on the moon. Perhaps it was all a hoax. All kinds of theories have been brought up insisting that we never landed on the moon.
What do you think generative AI would say in response to that same question regarding whether mankind has landed on the moon?
Let’s find out.
I opted to use ChatGPT.
If you decide to do the same for this question, keep in mind that your results might differ since a probabilistic algorithm within the AI is used to devise the responses. Each response generated by generative AI will usually differ from any other response. The difference might be minor and inconsequential, but nonetheless, the wording will likely slightly differ or more so differ.
My prompt entered into ChatGPT is this:
The response from ChatGPT is this:
I want you to closely read and read again that response from ChatGPT.
Please do so, I’ll wait a moment.
You hopefully observed that there wasn’t anything uncertain about the assertion that mankind has landed on the moon. The wording is very affirmative. There is no wording that waffles or suggests anything other than complete certainty.
I will try the question again and this time bring into the prompt by “general prompt” that spurs the AI to consider telling about any uncertainties that might exist.
My prompt entered into ChatGPT is this:
The response from ChatGPT is this:
Notice that we got quite an elaboration that goes far beyond the first answer.
If you had only gotten the first answer, you would be completely unaware of the certainty/uncertainty about whether or not we landed on the moon (unless, perchance, you knew of it beforehand). I realize that some of you might be exhorting that the uncertainty isn’t real and can be utterly ignored. My point is not whether the truth is one or the other (I believe we did land on the moon, see my coverage at the link here), and instead that simply a normal query would not likely reveal the controversy over the certainty factor.
As a final step in this brief example, I’ll ask ChatGPT to include a numeric score. Plus, I will instruct ChatGPT to include the score at the start of the response. This then covers two more of my above demo prompting strategies for garnering certainty/uncertainty. For a bonus, I also asked ChatGPT to explain how it arrived at the certainty/uncertainty.
Here’s what I entered as my prompt into ChatGPT:
The response by ChatGPT was this:
You can plainly see that ChatGPT has given the uncertainty a score of 10 which on my provided scale is the least amount of uncertainty. An explanation is included about how the score was determined.
Some of you might find the scale that I used to be somewhat confusing. An uncertainty level of 10 on the scale that I defined means that there is essentially no uncertainty. I purposely wrote the prompt in that manner because I wanted to show you that you need to be thinking about how your scale will look once it is put into use by the generative AI. It could be that a scale of 0 to 10 would have been better, along with stating that a 0 means no uncertainty while a 10 means the utmost uncertainty. People would indubitably find that easier to understand and digest.
Devise whatever scale you think is most conducive to your generative AI efforts and be contemplating how the results will be further utilized.
Mighty Important Caveats And Considerations
You might recall that I had earlier stated that humans have an implicit semblance of certainty/uncertainty, and separately can convey or explicitly communicate a semblance of certainty/uncertainty. I want to bring that back into focus.
Keep in mind that today’s generative AI is not sentient. Thus, if someone refers to what is implicitly or internally going on within generative AI, it is all a matter of mathematics and computational pattern matching, which I explain at the link here.
Okay, so when generative AI emits a response that Jack and Jill fell down the hill with a 90% certainty level, what does that mean? It could be that the mathematical and computational pattern-matching was able to calculate this degree of certainty. But it could also mean that the generative AI pulled the number out of thin air.
A rule of thumb is that you cannot believe the stated certainty of generative AI and do not fall for a double whammy. The double-whammy is that when you don’t ask for certainties the wording is going to possibly imply certainty (first of the whammies), while by asking for a certainty you might get a totally concocted one that leads you to believe that the certainty expressed is somehow magically accurate and apt (ouch, the double whammy).
There is a bit of irony there. The act of asking for a certainty indication can get you one, lulling you into believing even more so the generative AI, when the reality is that the certainty indication is contrived and has no substance behind it.
Be very careful.
One means to cope with this involves adding into your prompt that you want the generative AI to explain how it came up with the certainties and uncertainties. Ask what the basis for those is. This might boost your confidence in the showcased certainties.
I don’t want to be the bearer of bad news but the explanations might also be contrived. Think of it this way. You wanted certainties and so the generative AI complied. You also want explanations. The explanations might be generated by the AI mainly to appease your request, and not due to the explanations solidly having anything to do with how the certainties were derived.
Perhaps you can discern why some AI makers generally avoid getting into the morass or abyss associated with showcasing certainties. They could be accused of being excessively misleading. People might go around quoting that this generative AI or that generative said that this or that is a 95% chance of happening. Such a claim could be utterly bogus and the generative AI came up with certainties in a manner that has little or no viable justification.
Keep your wits about you in exercising the certainties prompting approach.
Let’s do a wrap-up.
You would be wise to use the activation of identifying generative AI certainties when it is presumably most suitable to your situation at hand. Doing so might be appropriate for a given knotty question or complex dialogue that you are opting to have with generative AI, rather than doing so all of the time. This is a prompting strategy or tactic that can be leveraged or invoked on a particular prompt (on a case-by-case basis).
For those of you that adore seeing the certainties, you could put into your custom instructions that you want the certainties to be identified all of the time, including doing so on a conversation-at-a-time basis or that they should perennially be displayed in whatever conversation you have with generative AI. For my discussion about how to set your own preferred defaults (known as custom instructions in ChatGPT), see the link here.
Your eyes ought to be wide open when you opt to get the certainties laid out. Do not necessarily believe what you see. Also, if you share the generated results with others, you should feel duty-bound to forewarn them too that the certainties are not ironclad and should be interpreted with a big grain of salt.
I am certain that if you decide to invoke certainties in generative AI, you will most certainly endeavor to use this prompting strategy suitably and with great certainty. The uncertainty lies in how well the generative AI will do at certainties, of which you must remain ever vigilant as to the uncertainty therein.
That’s certainly worth remembering.