Mark Tenenholtz
Mark Tenenholtz

@marktenenholtz

10 Tweets 6 reads Feb 11, 2022
When you learn data science, thereโ€™s no replacement for project-based learning.
Courses and blogs are fantastic resources, and you should take advantage of them.
But if you ever want knowledge to stick, you have to apply it.
Here are the 5 steps to project-based learning ๐Ÿงต
The internet is bursting at the seams with introductory content on machine learning.
Bootcamps, blogs, online courses, you name it. These are great sources of exposure.
However, that's all they are -- exposure.
You will never truly understand the material until you apply it.
It's incredible how much access we have to ML learning material, but it comes with a *huge* responsibility that is implicit in the contract between the creator and the learner.
That contract dictates that the creator is distilling their knowledge for their consumption.
However, to appreciate their knowledge, you'll need to follow the same steps they took to acquire it:
Application.
So, how do we approach application?
1. Pick a couple of skills to develop
The key here is to keep it manageable. Don't bite off more than you can chew.
These can be anything, but try to be as specific as possible.
"Machine learning" is not a specific skill.
"Regression with linear models" is much better.
2. Come up with a project to test those skills
Just pick something, anything! I promise, you aren't curing cancer.
Find something that will require you to apply the skills you want to learn and will capture your interest
3. Work until you get stuck
Inevitably, you will get stuck. That's a part of the learning process.
If you don't get stuck anywhere along the way or at least hit a bumpy part, you didn't challenge yourself enough.
The ideal project should make you think, but not stress you out.
4. Seek out help
This is the moment where it is perfect to dip into the well of the internet courses we spoke of before.
Everything you learn will now be reinforced 100x more because you have the gift of context.
Use the internet as a means to achieve your end, not as the end.
5. Repeat steps 3+4 until completion
The most important part of the project is to complete it.
80% of the learning usually happens in the last 20%.
It's easy to get lost in your work along the way, and this forces you to contextualize everything you've accomplished.
Before you know it, project-based learning will become a natural part of your process.
You'll find that you develop much deeper, more nuanced understanding of everything you learn.
If this helped you out, follow me @marktenenholtz for more high-signal content!

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