How To Prepare For A Data Science Training Course


How To Prepare For A Data Science Training Course

You have decided to start a data science training program. Maybe it's a bootcamp, maybe it's a fellowship, maybe it's an apprenticeship, or maybe it's a professional degree like a masters program. In either case, you are ready to to make the most out of the situation. The only thing left to do is to prepare for the program so that you can achieve your eventual goal of getting a data science job.

You're investing in your future and you want to get a return from it

Because you are investing your time and/or money into the experience, you want to make sure you are as prepared as you can be so that you can learn, build, and understand as much data science as possible. However, you're are worried and not sure about where to focus your time. You're not sure if you should just rest and relax, or whether you should start doing some readings, or whether you should start learning new data-science-related programming languages and libraries. After all, because the goal is to get a data science job at the end of the bootcamp, you want to make sure you set yourself as best as you can.

What if you knew how to do the right preparation to set you up physically, emotionally, and mentally?

If you knew exactly how to best prepare, you could simply do the preparation without too much though and be light years ahead of your class mates as well as other potential job candidates you would be competing against for the data science job you want.

By construction, most data science training programs will last anywhere from a few weeks to a few years. So regardless of how long the program is, you would want to make sure that as you neared the end of the program, you'd be in top physical, emotional, and mental condition so that you can go through the arduous process of data science job interviews.

Of course, you'd have your data science portfolio ready to showcase in addition to any new materials you may have learned, but in addition to that you'd be fully prepared for the grueling process of interviewing for your dream data science job.

Great news: You can prepare correctly to achieve success

To prepare for your data science training course, you'll have to work backwards. So we can write a series of steps that you'll take from today to your getting a data science job offer.

  1. Prepare for the data science training course
  2. Start the data science training course
  3. Build your knowledge, portfolio, and projects
  4. Sent out resumes / apply for data science jobs
  5. Get and do data science interviews
  6. Accept data science job offer

Work backwards to figure out where to start

We start with step #6 - "Accept data science job offer". To be prepared for this step you should already know roughly what companies you would and wouldn't want to work for, you'd want to know if there are people you'd like to work with at the company, what compensation range you would be comfortable with, what work place hours and culture you'd be happy with, and what team you would be working for.

Next, we look at step #5 - "Get and do data science interviews". To be prepared for this step, you should have an idea of what types of roles you would be suited for (junior data scientist, data scientist, senior data scientist, or other), what types of knowledge will be tested in the data science interviews, what types of knowledge will not be tested in the interviews, how the process works, and if there are any alumni from your data science program that can help you navigate the waters.

Next, we look at step #4 - "Sent out resumes / apply for data science jobs". To be prepared for this step, you should have an idea of what a data scientists resume looks like and what details to provide, where data science jobs are listed, what types of companies you would be interested in working with, what types of companies do informational interviews, what types of companies have good to great data science teams, what are common data science job applicant requirements, what are common data science job applicant nice-to-haves, what the process looks like, and what experiences alumni from your data science program have had when they did this step.

Next, we look at step #3 - "Build your knowledge, portfolio, and projects". To be prepared for this step, you should take an accurate assessment of your knowledge, you should figure out what types of data interest you, what types of techniques you want to learn more about, what the actual curriculum of the data science program covers, what the curriculum of the program doesn't cover, what advice alumni of your program would give you if they were going through the program again, and what previous successful alumni have done during this phase of the program.

Next, we look at step #2 - "Start the data science training course". To be prepared for this step, you should have done the preparation prior to the program and have a set schedule and routine that will make you the most alert and engaged during the time you spend at the program. Additionally, you want to be ready to network and exchange ideas with your classmates. If you have a plan going in about what you need to learn, what you want out of the program, and what you want your experience to be like, then you can share it with the program teachers and coordinators to make sure they help you get the most out of the program.

Next, we look at step #1 - "Prepare for the data science training course". Whew. So we made it to the first step. What we can do here is take all of the previous steps and what you should do, what you should learn, and what you should figure out and make it into a list you can work through slowly.

List of questions to ask yourself and your data science program

To properly prepare for your data science training program, here's the list of questions you should think about and try to get answered before you start your program. That way, you'll be very well prepared to get the most out of the program and eventually get a data science job and have a data science career.
The questions:

  1. What do I want out of the program?
  2. What constitutes success for having gone through the program?
  3. Who are going to be my potential classmates?
  4. What do I want to learn from my potential classmates?
  5. Who are going to be my teachers / guides / program coordinators?
  6. What do I want to learn from my teachers / guides / program coordinators?
  7. What do I want my schedule to look like (weekdays and weekends)?
  8. What does the curriculum and syllabus look like?
  9. Do I need to learn more about any particular topic?
  10. Are there any topics / themes that are missing from what I want to learn about?
  11. Are there any topics that I already feel comfortable with?
  12. What types of data interest me?
  13. What types of data problems interest me?
  14. What types of techniques do I want to learn more about?
  15. What advice would alumni of my data science program give if they were starting again?
  16. What have successful alumni done at this stage of the program (starting the program)?
  17. What do I want my data science resume to look like?
  18. What details do people put in their data science resumes?
  19. How do alumni of the program list their education experience?
  20. What types of data science jobs am I interested in?
  21. What types of data science groups am I interested in?
  22. What types of data science problems as I interested in?
  23. What are common data science job applicant requirements?
  24. What are common data science job applicant nice-to-haves?
  25. What types of companies are currently hiring data scientists?
  26. What does the data science job application process look like?
  27. What does the data science interview process look like?
  28. What do I need to do to prepare for data science job interviews?
  29. What types of data science roles would I be suited for? (junior data scientist, data scientist, senior data scientist, other)?
  30. What types of data science knowledge do I think will be tested in interviews?
  31. Where have previous program alumni interviewed?
  32. What types of companies would I want to work with?
  33. What types of companies would I not want to work with?
  34. What types of compensation range would I be comfortable with?
  35. What type of culture would I like to work in?
  36. What type of team would I like to work with?
  37. What stage of company would I like to work with?

The next step

That's a good amount of thinking you should do. Don't despair however, most of these questions are either thinking exercises that will help you to get to know yourself better, or they can be answered by the faculty / program coordinates of your data science program.

To that end, start with the first question "What do I want out of the program?" and slowly work through them. Thinking about them as you go through your everyday life will be helpful as you can really put some thought and reflection into the answers.

Some time from now as you've gone through these questions and have started writing down the answers, you'll feel relieved because you will have a plan and the right preparation to set you up physically, emotionally, and mentally to tackle the challenge of going through a data science program. You'll be light years ahead of your class mates and when it comes time to apply, interview, and accept a data science job, you'll be incredibly prepared to achieve your goals.

To that end, good luck and start thinking about "What do I want out of the program?"!


Do you want to become a data scientist faster than you think possible?
Get started today =>
Free 5 Day Email Step-by-step Instructional Course for getting started in data science


You might also enjoy these data science articles because you are terrific:

Sign up to receive the Data Science Weekly Newsletter every Thursday

Easy to unsubscribe. No spam — we keep your email safe and do not share it.