Alright, so after reading TONS and TONS of #100DaysOfCode tweets and Alvaro Trigo liking a major chunk of them, I decided it was finally time I took up this challenge. But it’s not like this would be the first time I would be coding for 100 days consecutively. It would rather be my first time logging in the days’ work.

Now I know why this challenge is going to be fruitful for me. On a lot of days, it feels like I’ve coded enough for the day (and by code I mean sometimes even just solving GFG), but when I start analysing I woudn’t have done much. Logging in the details gives you a fair idea of how much substantial coding you did. Not saying that:

Length of your log ∝ how much you have learnt

but if you end up writing something like:

#Day X : Learnt javascript.

and if you REALLY did, then you’ve absolutely nailed it.

Conclusion: Analysing your productivity at the end of the day should come naturally to us, and it doesn’t to me :P , so all in all its a great challenge for me to take up.

But knowing the kind of distracted person I am, I needed a well-formed path that would keep me on track and ensure I was learning what’s relevant.

Solution: A course!

Hence I selected this Udemy course : Python for Data Science and Machine Learning. Its got 143 modules in total and I’m hoping to finish this within the 100 days. I might also do some additional this-and-that coding. Let’s beginnnnn! (Italicized numbers == module numbers)

#Day 1

  1. 1-4 were introductory. Watched them at 3x speed.
  2. 5-6 were about Jupyter notebooks and virtual environment. Installed Jupyter and I absolutely love it.
  3. 7-14 was a 4-part Python crash course. I knew python beforehand so I watched them at 4x speed xD. Completed the corresponding exercise.
  4. 15-16 were introductory to NumPy.

#Day 2

  1. 17-22 were about NumPy arrays, indexing, and their operations.
  2. Completed the NumPy exercise.
  3. Coded questions off the Amazon section of GFG.

#Day 3

  1. 23-26 were about Pandas introduction, series, and dataframes.
  2. Gave a contest on GFG.

#Day 4

  1. 27-28 completed dataframes basics.
  2. 29 talked about filling missing values in dataframes.
  3. Coded medium level GFG questions.

#Day 5

  1. 30-36 had merging, joining, concatenating, groupby, reading csv/html/excel/SQL.
  2. Completed Pandas Excercise 1.
  3. I’ve been learning Prolog for AI.

#Day 6

  1. 37-38 Completed Pandas exercise 2.
  2. 39-41 Introduction to matplotlib.
  3. Parsing C file using regex in Java.

#Day 7

  1. 42-45 Completed matplotlib with exercises.
  2. 46-47 Started Seaborn which is built on top of matplotlib.

#Day 8

  1. 48-52 Finished all types of plots(Distribution, regression, etc).

#Day 9

#Day 10