I’ve started my transition in data science, and machine learning/artificial intelligence. There are many available resources available but I felt Jose Portilla’s Udemy Python for Data Science was a great overall starter. Course link here.
Python for Data Science
There is roughly 25 sections. Although the first 4 are more about set up (assuming no python background). Here are the things I enjoyed:
- The overall ‘introduction’ to Python and Data. Jose pretty much goes into each core area, such as numpy, pandas, matplot, seaborn and then jumps into machine learning (I honestly did not expect this part).
- The ‘Notebooks‘ – in Python for Data Science, Jose arranges notebooks for you to do exercises. I really like this part of it as it reinforces the lectures. This was also in his other course (Python bootcamp).
- Always reminding us to go through the data, explore it, and figure out why we are doing it.
- The start to finish of each project. The format of each topic generally boils down to a lecture (understanding) and then some exercises and then a problem set from start to finish. I normally use a blank notebook for each new topic and follow along with him.
- My GITHUB link for this course is here.
Reminder for those thinking of taking it!
This is an overview, and although there is a crash course for Python, I think a little bit of knowledge is good. Although Python for Data Science covers a lot of topics in machine learning (neural nets, deep learning, NLP) it doesn’t go deeply into them. If you are looking for that, I’d suggest a different course.
I think those pushing it, could finish the course in a less than a month – even a fortnight. A great entry point to Data science and although I do not plan to take the R studio equivalent, I highly recommend it!