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Exam Code: Google-PDE Practice exam 2022 by team
Google-PDE Professional Data Engineer on Google Cloud Platform

A Professional Data Engineer enables data-driven decision making by collecting, transforming, and publishing data. A Data Engineer should be able to design, build, operationalize, secure, and monitor data processing systems with a particular emphasis on security and compliance; scalability and efficiency; reliability and fidelity; and flexibility and portability. A Data Engineer should also be able to leverage, deploy, and continuously train pre-existing machine learning models.

The Professional Data Engineer exam assesses your ability to:
- Design data processing systems
- Build and operationalize data processing systems
- Operationalize machine learning models
- Ensure solution quality

1. Designing data processing systems
1.1 Selecting the appropriate storage technologies. Considerations include:
- Mapping storage systems to business requirements
- Data modeling
- Tradeoffs involving latency, throughput, transactions
- Distributed systems
- Schema design

1.2 Designing data pipelines. Considerations include:
- Data publishing and visualization (e.g., BigQuery)
- Batch and streaming data (e.g., Cloud Dataflow, Cloud Dataproc, Apache Beam, Apache Spark and Hadoop ecosystem, Cloud Pub/Sub, Apache Kafka)
- Online (interactive) vs. batch predictions
- Job automation and orchestration (e.g., Cloud Composer)

1.3 Designing a data processing solution. Considerations include:
- Choice of infrastructure
- System availability and fault tolerance
- Use of distributed systems
- Capacity planning
- Hybrid cloud and edge computing
- Architecture options (e.g., message brokers, message queues, middleware, service-oriented architecture, serverless functions)
- At least once, in-order, and exactly once, etc., event processing

1.4 Migrating data warehousing and data processing. Considerations include:
- Awareness of current state and how to migrate a design to a future state
- Migrating from on-premises to cloud (Data Transfer Service, Transfer Appliance, Cloud Networking)
- Validating a migration

2. Building and operationalizing data processing systems
2.1 Building and operationalizing storage systems. Considerations include:
- Effective use of managed services (Cloud Bigtable, Cloud Spanner, Cloud SQL, BigQuery, Cloud Storage, Cloud Datastore, Cloud Memorystore)
- Storage costs and performance
- Lifecycle management of data

2.2 Building and operationalizing pipelines. Considerations include:
- Data cleansing
- Batch and streaming
- Transformation
- Data acquisition and import
- Integrating with new data sources

2.3 Building and operationalizing processing infrastructure. Considerations include:
- Provisioning resources
- Monitoring pipelines
- Adjusting pipelines
- Testing and quality control

3. Operationalizing machine learning models
3.1 Leveraging pre-built ML models as a service. Considerations include:
- ML APIs (e.g., Vision API, Speech API)
- Customizing ML APIs (e.g., AutoML Vision, Auto ML text)
- Conversational experiences (e.g., Dialogflow)

3.2 Deploying an ML pipeline. Considerations include:
- Ingesting appropriate data
- Retraining of machine learning models (Cloud Machine Learning Engine, BigQuery ML, Kubeflow, Spark ML)
- Continuous evaluation

3.3 Choosing the appropriate training and serving infrastructure. Considerations include:
- Distributed vs. single machine
- Use of edge compute
- Hardware accelerators (e.g., GPU, TPU)

3.4 Measuring, monitoring, and troubleshooting machine learning models. Considerations include:
- Machine learning terminology (e.g., features, labels, models, regression, classification, recommendation, supervised and unsupervised learning, evaluation metrics)
- Impact of dependencies of machine learning models
- Common sources of error (e.g., assumptions about data)

4. Ensuring solution quality
4.1 Designing for security and compliance. Considerations include:
- Identity and access management (e.g., Cloud IAM)
- Data security (encryption, key management)
- Ensuring privacy (e.g., Data Loss Prevention API)
- Legal compliance (e.g., Health Insurance Portability and Accountability Act (HIPAA), Children's Online Privacy Protection Act (COPPA), FedRAMP, General Data Protection Regulation (GDPR))

4.2 Ensuring scalability and efficiency. Considerations include:
- Building and running test suites
- Pipeline monitoring (e.g., Stackdriver)
- Assessing, troubleshooting, and improving data representations and data processing infrastructure
- Resizing and autoscaling resources

4.3 Ensuring reliability and fidelity. Considerations include:
- Performing data preparation and quality control (e.g., Cloud Dataprep)
- Verification and monitoring
- Planning, executing, and stress testing data recovery (fault tolerance, rerunning failed jobs, performing retrospective re-analysis)
- Choosing between ACID, idempotent, eventually consistent requirements

4.4 Ensuring flexibility and portability. Considerations include:
- Mapping to current and future business requirements
- Designing for data and application portability (e.g., multi-cloud, data residency requirements)
- Data staging, cataloging, and discovery

Professional Data Engineer on Google Cloud Platform
Google Professional Practice Test
Killexams : Google Professional practice exam - BingNews Search results Killexams : Google Professional practice exam - BingNews Killexams : How the simulated world is assisting the automotive industry

Virtual reality (VR) applications are growing rapidly across sectors as diverse as entertainment, professional services and even education.

VR technology is now being extended in an innovative way to the automotive industry by London based independent creative design studio, NewTerritory.

NewTerritory has created a multi-sensory virtual reality experience which has been designed to assist the automotive industry and mitigate some of the challenges presented by semi-autonomous driving.

Using the latest in VR technology the company enables the test driver to experience a fully immersive experience, allowing the company to monitor heart rate, reactions to various stimulus and much more.

We visited the NewTerritory office in London to speak with design and creative tech director Tim Smith, to find out more about this unique technology. 

Just Auto (JA): How did you come to your role at NewTerritory?

Tim Smith (TS):  My background is in automotive technology. I’ve worked with big brands such as Ford, Volkswagen and Porsche, but also companies like Google and Apple for the last ten years.

I was always in digital and creative technology, and one of the things I started to find more recently in my career was that there was always a physical component that was necessary to complete the experience.

When I joined NewTerritory you had kind of the opposite problem where they were already designing a lot the physicality of some of these in-car or transportation experiences, but they came to the point where they needed some digital and creative technology. I was hired to bolster that side.

It feels like we can provide a complete package and for me personally in my career I can see through complete projects and make bigger differences to customers.

How did this project start?

TS: The first thing I did when I started was persuade the team, but it wasn’t difficult, they were very eager for this project. We said let’s create a project that demonstrates the power of merging the physical with the digital. The Metaverse was coming up a lot in discussion and I saw the Metaverse as an amazing testbed for testing experiences safely.

We can’t test this technology in a real car or on real roads, the laws won’t allow it, but in the Metaverse, in a virtual simulated world, we can freely test a number of experiences.

I’ve always thought the car is the only consumer electronic product that you can step into and it’s something that can traverse you through space and time. In the last few years we’ve seen the likes of Apple and Google take some of the automotive industry’s lunch, and by that I mean carsharing or even creating their own cars. There’s an opportunity here for the automotive industry to win some of that lunch back.

For me there’s no more compelling application of voice assistance than in the car; I think it’s Rolls Royce who have ‘Elena’ which is its own AI system. Other car companies have similar things. The car is an ideal application for voice assistants, and it may well be that people trust, say, ‘Elena’ more than they trust ‘Siri’ in time.

What this prototype does is create a multi-sensory experience that could curate people’s moods and their cognitive ability.

I also thought the automotive industry should stop looking at the centre console. There’s a whole vehicle in a controlled environment that can in theory, read your heart rate, see how quickly you’re blinking, what your pupil dilation is, how fast you’re breathing, and all these things can infer not just things like how tired you are, but how excitable you might be or how susceptible you might be to certain information.

What this prototype does is create a multi-sensory experience that could curate people’s moods and their cognitive ability.

What is the ‘cognition Goldilocks Zone’?

TS: I worked with University College London as a guest lecturer a couple of years ago. We were thinking about this problem around level 4 autonomy. At the time, and I’m not sure if it’s still the case, but Google and Ford had decided that they were going to completely skip level 4 because it was too difficult. Not from a technological point of view perhaps, but from the human perspective. Level 4 is pretty much fully autonomous, a robocar. Beneath that level, it’s not fully autonomous drive because there will be points in which the driver has to take over – there is still human responsibility for part of the journey.

If you imagine that the car was asking you to take over 70mph after you’ve read a book, your situational awareness is completely in the gutter and it’s difficult to take over control at that speed.

So, we were trying to understand what the cognitive load was like at that stage; it’s as if that muscle isn’t warmed up enough to be able to cognitively have the situational awareness to take over the drive. Once you know when you’re going from one context such as studying a book to driving, it’s a completely different cognitive load.

We did a number of tests around how people performed depending on different cognitive stresses.

There was one test where we asked someone to watch an episode of the TV show ‘Friends’ on an iPad, and then we would supply them the trigger to take over – we noticed that the performance for driving was terrible.

However, another interesting thing was when they were what we call ‘over-stimulated’; so there were too many billboards on the side of the road, there was music playing, the window was down, there was noise and hazards on the road. They were overstimulated by the drive and that made them equally dangerous.

We realised that you can be under-stimulated, and you can be over-stimulated, so there must be a cognition ‘Goldilocks Zone’ – an optimal level of stimulation. What we found is that we were able to do some interventions, to bump them up or down into the cognition Goldilocks Zone, and then the driving performance afterwards really improved.

The way we’re testing at the moment is very rudimentary, but it’s with heart rate so we can know what their average heart rate is. We know that if it’s a certain percentage below their average heart rate, they’re under-stimulated, if it’s a certain percentage above then they’re over-stimulated.

That’s what triggers what we call the dampen mode or the heighten mode. It’s different for each person. In practice the car will get to know your resting heart rate after a few drives so if it goes above or below, the technology knows when to kick in.

For our readers who can’t see the set-up like I can, can you explain the technology that you have here?

TS: The first thing I will start with is the control panel that’s browser based and is used to talk to several devices, physical devices. This is so we can see how it’s performing.

Then we have this whole rig, if you take the car seats away this could be a gaming experience, or a retail experience. But for this prototype, we are just testing it for the semi-autonomous context.

We’ve got two very authentic car seats (which are made from some MDF stuck onto some office chairs), we have the rig itself which is a skeleton by which we can hang a number of pieces of technology on, so over time, we can change things which may not work as well, or we want to add to.

At the top of the rig, we have got these watering dispensers, one is associated with heighten mode and one is associated with dampen mode. In the dampen mode bottle we have yuzu, which is good for focus, in heighten mode we have citrus which helps with making people more alert.

We really are multi-sensory, so we also consider taste; what we do is supply people a lollipop to put in their mouth depending on if it was the dampen mode or heighten mode. That comes from the idea that when people suck mints it helps their focus while driving.

Taste is a very difficult sense to design for, as it’s a tactile sense that requires initiation from the person, usually with their hands, which should be on the wheel. A tin of mints on the dashboard was how my granddad kept himself focussed and entertained while driving long distances – perhaps a brand needs to come along and introduce specialist driver sweets with fan mounting packaging. This is a tough one… 

Then we have what we call a multi-directional fan system, it’s basically a main fan which simulates the air conditioning in the car, then we have a side fan which simulates the open car window. 

In the seat here, we’ve got the muscle massager and another one in the headrest. They create what we’re calling HD haptic feedback, it’s a bit like the Nintendo Switch’s HD Rumble where it’s not just be on or off it can render various strengths and direction of vibration and haptic feedback. We use them to either mimic different road conditions or we use it to jolt them awake, or alert them to something.

Then we have this glove, which we call the glove of truth, you wear this glove of truth, it reads your heart rate. What it does in the first minute is it takes your average heart rate, then once the experience begins it can see if it’s dipping, or peaking, and that’s when it triggers the heighten or dampen mode.

We have a small section for temperature, this is just a heater which you can turn on and off. Then the most technical element is the VR headset, this is the latest VIVE headset, this is able to supply you an audio and visual sense of what’s going on.

In three to four years’ time what did you see the status of this technology being?

TS: All of this hardware probably already exists in cars in some form, but they don’t work in harmony. They don’t work together for this purpose – all it requires is a bit of clever code that connects the hardware.

I think it’s more this mode of thinking than the physicality of what you see here that I think will hopefully be adopted into the car.

Accessibility is a key area of focus for me. When it comes to multi-sensory experiences, I’m hoping that becomes the norm for people with different needs and disabilities.

I think if we consider experiences more on this multi-sensory level, you make sure that you’ve thought of every possible stimulus that each sense can consume. Not only do you make it a more immersive experience, and a better brand experience, but you actually make it more accessible as well.

I’ve actually done lots of testing with blind people; some of them own cars but can’t drive them, and the thing they always say is: “I just want to sit in the driver’s seat.” With driverless cars, that’s a possibility in theory.

I think the beauty of this prototype is that it’s multi-sensory, I think it’s better for brands, because they can supply much more immersive brand experiences, it’s better for the everyday consumer, because they can have more pleasant experiences. Then it’s better for accessibility, and therefore increases the size of the market as there are now more people who can appreciate it.

Tue, 26 Jul 2022 02:40:00 -0500 en-US text/html
Killexams : New Research Reveals State of Machine Translation for Website Translation

A new study on the accuracy of AI and Machine Translation (MT) software has shown the tools are more accurate at translating written text than people might think – in some cases requiring zero edits from professional linguists.

A global shortage of skilled interpreters is continuing to drive the development of AI and Machine translations, with Meta recently announcing its own AI translator tool for more than 200 languages. But there is still a reticence to use MT for marketing content because of often unproven prejudices that have built over the years in the localization industry.

The aim of the research was to debunk those common myths and prejudices. Conducted by Weglot and language consultants Nimdzi, the research evaluated and compared five of the leading Machine Translation providers – Amazon Translate, DeepL, Google Cloud, Microsoft Translator, and ModernMT.

Commenting on why they set out to perform this research, Augustin Prot, CEO at Weglot said, “We wanted to test the leading Machine Translation tools with marketing content and languages like Arabic and Chinese – which are often avoided because of the alleged lower translation quality.”

The MT tools were tested on their accuracy and reliability in translating 168 different segments containing more than 1,000 different words from American English into French, German, Spanish, Simplified Chinese, Arabic, and European Portuguese.

Reviewed by professional linguists, 85% of the 14 translations were scored as ‘Very good’ or ‘Acceptable’, with none of the Machine Translated material scored as ‘Very bad’.

Italian was the most difficult language to translate with an average acceptability score of 2.6, while German scored the highest at 3.4. The rest of the scores include Spanish (3.2), Portuguese (3), Arabic (3), French (2.9), and Simplified Chinese (2.8).

Of the 168 different word segments tested on the software, German again came out on top, with 145 sections not requiring any edits from the professional linguists after being translated, compared to Portuguese which had just 58 unedited sections.

However, the simple ampersand (&) proved to be a recurring problem for the MT tools, while there was also confusion between Brazilian and European Portuguese as well as contextual and punctuation issues.

10 out of the 14 total reviews of the quality of the translations were scored as being “positively surprised” by the two professional linguists, with the MT output of better quality than originally expected.

Prot continues, “An estimated 99% of translations globally are not done by professional human translators – simply because there’s not enough time in the world. As such, the volume of machine-translated content has skyrocketed over the past couple of years, and we only expect to see this further  as the technology develops and matures.”

Prot concludes “The data presented in this study debunks some of the persisting myths and confirms that machine translation can be deployed as an accelerator in the translation process for marketing content. Machine translation has reached a level of maturity where it now complements, rather than replaces, human linguists.”

You can access the report in full here

Sun, 31 Jul 2022 21:00:00 -0500 Weglot en-US text/html
Killexams : How to Make an Abortion Emergency Plan Right Now No result found, try new keyword!Wade, the landmark Supreme Court ruling that guaranteed the right to abortion in the U.S. on a federal level, has been overturned. Sat, 30 Jul 2022 03:00:00 -0500 en-us text/html Killexams : The Best Home Security System

Our pick

Ring Alarm Pro

The latest Ring security system has a built-in Wi-Fi 6 router, works with almost every type of add-on you can imagine, and provides internet backup (for a fee), as well as the option to add up to 24 additional hours of backup power in case of an outage.

Buying Options

*At the time of publishing, the price was $300.

Compatible with: Amazon Alexa, Works With Ring

The strength of the Ring Alarm Pro, in addition to all of the sensors and accessories it can support (including a wide variety of cameras), is that it includes a built-in Eero Wi-Fi 6 router. That means you can replace your standard router, depending on your service, or create a mesh network to Excellerate your Wi-Fi’s speed for security cameras and other smart-home devices around the house. It also creates a cellular backup web connection when your power or internet goes down (with a Ring Protect Pro plan). The easy-to-use DIY security system offers the best bang for your buck when it comes to professional monitoring ($20 per month or $200 per year). It has almost every add-on you can imagine, including a few options for door and window sensors, smoke and carbon monoxide detectors, and several types of hardwired and battery-operated doorbells and cameras. It does allow for self-monitoring, but the original Ring Alarm would be better for that (although we don’t really recommend self-monitoring anyway).

Our pick

Ring Alarm (2nd Generation)

The original Ring system is easy to use and inexpensive to set up, and has more camera add-ons than any of our other picks.

Compatible with: Amazon Alexa, Works With Ring

If you already have a mesh network or don’t want one, we recommend the original Ring Alarm. This easy-to-use DIY security system works with all the same add-ons as the Ring Alarm Pro, including the optional Ring Protect Pro monitoring plan for $20 per month. You can also use it as a self-monitored system for no extra cost, or add video storage for as little as $3 per month (although Ring just announced a $1 increase in the monthly price of the Ring Protect Basic plan beginning July 1, 2022). Unlike the Ring Alarm Pro, it doesn’t offer internet backup or work with external battery packs, but the base station provides 24 hours of battery backup, and the Pro plan includes a cellular connection.


SimpliSafe The Essentials

This SimpliSafe kit is affordable and easy to install and use. Its optional monitoring plan is slightly cheaper than that of our top pick, although it doesn’t provide video storage.

Compatible with: Amazon Alexa, Google Assistant, August Smart Locks

SimpliSafe is another easy-to-use DIY security system, with add-ons such as indoor and outdoor video cameras, a doorbell camera, a smart lock, and smoke and other sensors. Its 24/7 professional monitoring fees are competitive with those of other DIY systems, though The Essentials kit also has a self-monitoring option. Unfortunately, outside of smart speakers, the only non-SimpliSafe devices it’s compatible with are August locks. Still, for anyone who wants a reliable system that’s easy to use, works with voice-control systems, and offers a good selection of add-ons, the SimpliSafe setup is still a great option.

Also great

Abode Smart Security Kit

Abode offers more smart-home integration than any other security system we tested, which means you can tie it into smart-home devices from different manufacturers.

Compatible with: Amazon Alexa, Apple HomeKit, Google Assistant, IFTTT, Z-Wave, Zigbee

Abode is for the person who wants a security system that can integrate with smart lighting and thermostats, voice-controlled speakers, and other smart-home devices—and doesn’t mind going through the steps to create that setup. Abode supports both Zigbee- and Z-Wave–enabled devices, as well as Amazon Alexa, Apple HomeKit, Google Assistant, and IFTTT (If This Then That). That type of support comes at a price: We found Abode starter packages and most accessories to be more expensive than our other picks.

Sat, 18 Jun 2022 18:32:00 -0500 en text/html
Killexams : To Be Happier at Work, Think Flexibly about Your Job—and Yourself

In the two decades since Amy Wrzesniewski, the Michael H. Jordan Professor of Management at Yale SOM, first studied the practice of “job crafting” (in collaboration with Jane Dutton, now professor emerita at Michigan Ross), the concept has found an eager audience. Subsequent researchers as well as the popular press have concluded that embracing the practice, in which an employee intentionally alters the design of their own professional role, can boost psychological well-being, engagement, and performance on the job.

A new paper from Wrzesniewski—along with co-authors Justin Berg at the Stanford Graduate School of Business, Adam Grant at the Wharton School, and Jennifer Kurkoski and Brian Welle at Google—investigates whether these benefits can be extended even further with the adoption of what they term a “dual-growth mindset”: one that combines the job-crafting mindset with a similarly flexible approach to beliefs about the self. In other words, what might happen when people who are actively modifying fixed beliefs about their jobs invite their attitudes about themselves along for the ride ?

Wrzesniewski suspected that altering job- and self-growth mindsets in tandem would yield larger gains in happiness than tweaking either in isolation. To explain why, she offers a metaphor: Imagine two poles planted in the ground, connected by a banner. One pole represents ideas about the self (especially one’s self-perceived skills, strengths, and abilities); the other, ideas about work (and its routines, tasks, and key relationships). If we can move only one pole, possibilities for new ground are limited. But once we move both, the poles can be re-planted with far more freedom.

“If what job crafting does is lift the job pole out of the ground and allow you to move it around, then moving the self pole can introduce the possibility of bigger or more dynamic changes to the design of the work,” Wrzesniewski says.

Two experiments the researchers conducted to test this hypothesis confirmed their theorizing. The results revealed that workers who learned how to alter both their job- and self-related mindsets planned bigger changes for their job designs—and subsequently experienced long-term increases in happiness, unlike the workers who had concentrated on either mindset in isolation.

“Our work suggests that to achieve sustainable gains,” the researchers write, “it may be important for individuals to believe they can change their environments as well as themselves.”

In two separate experiments, the researchers assigned participants to one of three growth-mindset interventions: the first focused on the self, the second on the job, and the third combined the two concepts—making them the dual-growth group.

The first experiment was conducted in a Fortune 500 tech firm, where 149 employees voluntarily attended one of three two-hour “career development” workshops, each with a different intervention. Employees were randomly assigned by workshop to one of the three interventions. The workshops were held in person, and were conducted by Wrzesniewski, Berg, and Grant. The second experiment was conducted online, using text-based versions of the same workshops, and used Amazon MTurk to recruit roughly 400 full-time employees from companies across the U.S.

Both experiments sought to capture measures of how participants’ happiness changed over time—by checking just before the workshops, a few weeks after the workshops, and six months post-workshop—though they did so in different ways. In the first experiment, the researchers opted to measure happiness using ratings offered by participants’ managers and peers at work —who were “blind” to the study condition the participant was assigned to, an approach they chose in order to circumvent the confounding effect of participants anticipating what researchers expected to observe in these measures and revising their scores accordingly.

In the second experiment, however, the researchers used a slightly different approach. “The subjective experience of happiness is also important,” they write, and so, in the second experiment, they asked participants to report on their own feelings before the workshops, four weeks afterward, and then six months later. In this experiment, the researchers also asked employees to answer questions about their self- and job-growth mindsets (to gauge their rigidity or flexibility) at each of these intervals.

In both experiments, study participants were asked to complete an exercise in which they graphically represented their attributes and skills and/or their jobs as a flexible set of building blocks. In the job-growth workshop, for example, they were asked to create a “before” diagram where they mapped the tasks and relationships that occupied their current work lives onto blocks of three sizes, depending on the time and energy they required. In an “after” diagram, they could introduce brand-new task blocks, drop task blocks, or increase or decrease the size of an existing block. To quantify the scope of the changes participants were planning for themselves, the researchers coded participants’ before-and-after diagrams, giving scores based on the degree of changes planned by participants.

The dual-growth mindset workshops, the researchers found, boosted happiness most over the long term. And there was an additional benefit: the dual-growth condition also appeared to yield the stickiest mindset change over time. In other words, participants who had been assigned to this condition were the most likely to continue exhibiting flexibility in the way they thought about the malleability of their own abilities and skills and/or their jobs.

What’s more, the researchers found that the size and ambition of changes people planned for themselves and their jobs were tied to their sustained happiness gains six months later. This indicates to Wrzesniewski that the dual-growth mindset proved stickier and yielded longer-term happiness because of the size of the steps it enabled people to tackle to bring change to their lives.

“The nature of the changes people in the dual-growth mindset group were planning were just different,” Wrzesniewski says. “That’s what we believe explains the longer-term benefits. It seems to be that mindset drives happiness through what you’re able to do because of the mindset.”

Wrzesniewski believes these findings are especially relevant to today’s workers, in large part because of the way the pandemic has transformed workplaces and, for many, where their work happens.

“Because of the pandemic, more people are working remotely now, and part of what that does is automatically loosen a lot of the strong scripts and cues that surround people in the job, what the routines are, and so on,” Wrzesniewski says. “That becomes a really rich opportunity for job crafting.”

Tue, 26 Jul 2022 05:34:00 -0500 en text/html
Killexams : Cracking scholarships for international master’s degree

Obtaining a scholarship in a globally ranked top 100 university for a master's program is a dream come true for many students, and to many, a matter of enigma. While it is an incredibly challenging feat, it is quite feasible with careful and smart planning.

Do I have the right profile? Is my CGPA good enough? Do I need more work experience? Is it possible for a fresh graduate to land a major scholarship? Here's a step-by-step guide that answers all your burning questions and then some.

How to select the programs 

Smart use of Google, Youtube, spreadsheets, and asking the right people is usually the best way to begin the process. Start by searching for the best sites to curate scholarship information, and then include and organise them in a spreadsheet with their deadlines attached.

Two helpful websites to do this are and 

If you want to select the right program, you have to ask the following questions to yourself: 

Do the subjects taught resonate with my passion?
Do I have a clear idea about the career prospects of this program?
Do I see myself liking that career prospect?
Is the program looking for students having my personality and goals?

If all the answers match, shortlist the program and curate them in a spreadsheet. During my own application process, preparing the spreadsheet and updating it with information helped me stay focused all throughout. A smart and organised spreadsheet also helps you feel less overwhelmed. Youtube is another useful resource for looking for potential scholarships. 

The motivation letter: What is the secret sauce?

The motivation letter is the platform for you to market yourself as the ideal candidate. It should be concise, coherent and convincing. Many waste time on the language, forgetting that it is not a literary piece but a professional letter to sell your case. Thinking of it as a pitch for marketing my suitability helped me write a good motivation letter. 

What worked in my case is the thorough research that I had done on every program, the syllabus structure and what qualities they are seeking in the ideal candidate.

Does CGPA matter a lot? 

To be honest, it does. However, it is important to remember that the graduate school admission committee judges you as an entire package, where CGPA is one of the many important factors.

The judgement criteria consist of various categories, and in most master's admission, your academic result bears 40% weight. The statement of purpose, your overall experience, and interview performance carry the remaining 60% of the marks. 

So, having a decent CGPA is definitely a notable advantage. Although there are certain scholarships in the Netherlands which solely focus on the CGPA or the ranking in class, CGPA is not always the only criteria the scholarship committees look for in a candidate. The litmus test of checking this is to find if there is an interview in the selection process. If there is an interview, then CGPA will not be the only determining factor.

Having a CGPA of around 3.5 is usually considered safe. It is very difficult to obtain a scholarship with a CGPA lower than that. In such cases, you need to build an extraordinary profile that is not dependent on your undergraduate test scores.

How to get the best marks in the interview 

The interview plays a crucial role in the scholarship selection process. There are some prestigious scholarships like the IDEX scholarship at the University of Paris-Saclay, where it is not possible to apply for scholarships individually. In these cases, the jury preselects the scholarship recipient by assessing their overall profile. In the selection process, the interview plays a crucial role.

Truth to be told, not knowing the answer to a question is not much of a problem. Having the humility to accept a lack of knowledge is considered a good practice. However, it is appreciated if you are bold enough to approach the answers that you know at least partially. A perfect blend of humility and boldness helps create a good impression.

The key factor that played in my success at the University of Helsinki interview was my thorough preparation. There are some common questions that are asked in nearly all the interviews, and I had prepared a succinct note about most of those questions. This helped me stay ahead of the competition while delivering coherent and organised answers during the interview.

My experience

I received a 100% scholarship for my MSc in Genetics and Molecular Biosciences from the University of Helsinki, whose GMB programme ranks 67th in the world according to QS WUR.

I completed my Bachelor of Science in Genetic Engineering and Biotechnology from the University of Dhaka with a CGPA of 3.60/4 in December 2021. It was a daunting task to be hopeful for a major scholarship being a fresh graduate with an above-average result. 

When it came to receiving major government-sponsored and international scholarships, what truly helped were my correct choice of programs, organised motivation letters and the ability to perform at my best during the interviews.

Final words

The scholarship hunting process is a rocky road full of setbacks and obstacles. The key to success is your grit and not being demotivated by rejection letters. Having the mindset of needing to get only one scholarship and moving on after each rejection helps tap into the potential success. 

It is certainly a long road, but a very fulfilling one at the end of it. If the going gets tough, remember to keep the right mindset and strategise each step to guarantee success in your next endeavour.

Thu, 04 Aug 2022 15:26:00 -0500 en text/html
Killexams : I used this device to track my metabolism for a month — here’s what happened

If you’ve ever heard someone say, “I just have a slow metabolism,” chances are they don’t actually know that for sure. And really, it may not be “slow” per se, but rather—to cop Lumen’s terminology — inflexible.

Created by twin sisters and Ironman triathletes, Merav and Michal Mor, both of whom have PhDs in Physiology (total underachievers, right?), Lumen emanated from the Mors’ desire to help people reach their nutrition, performance, and/or weight loss goals by rejiggering their metabolisms. The premise is that if you know at key moments if you’re burning mostly carbohydrates or fat (or a combo platter of both), you can determine what your body needs to function optimally—aka “personalized nutrition.”