Getting started with a ‘Technology’
Yesterday, during snack time, I was scrolling through the Medium homepage to read some articles in the cafeteria. I came across this article Use Kaggle to start (and guide) your ML/ Data Science journey — Why and How which caught my eye, as this is what I am looking from last several months, to how to learn ML and Data Science. I tried to go through multiple courses on getting started with Machine Learning, but no success, there was a lot of theory and lots of Mathematics (which needs a revision). I am not denying that we should not learn Mathematics behind it, but it was killing the excitement after hearing 100s of unknown/forgotten terminologies. To start learning something new, there have to be practical projects — say a mini project (which is fun) instead of going through theory (which is boring).
Some of the main reasons I started liking Kaggle or freeCodeCamp is because:
- (if you have time) Reading a document and practically implementing then and there is better than watching videos and solving MCQs. This kind of learning is best for self-paced learners. Also, while watching videos we may miss some point which the author is trying to focus, which we can’t miss while reading (you get it, right?).
- The way the course is designed are for dummies like me. The course starts with a design that people don’t know anything. Thanks to the authors.
- No software/IDE installation required, all the implementation/writing of code is on the web browser => Learn from anywhere.
I have started with the Python course in Kaggle. I have never majorly worked with Python earlier except writing basic ETL scripts in AWS Glue for Proofs-of-Concept.
As a self-paced learner, I am loving it.
Happy Learning!
