How to learn data science step by step for free??

How to learn data science step by step for free??

Deal Subedar

Could someone please provide guidelines on how to study data science STEP BY STEP for free on internet in less amount of time (maybe 4 months)

Please don’t provide unnecessary course links. I need step by step guidance. I am not from computer science bakground (from mechanical background so learning maths and statistics again is no big deal for me)

Also can we learn data science quickly by reverse engineering like studying few parts before and studying other parts while working on projects?

4 Dimers
Deal Subedar


Deal Lieutenant

even am seeking same. have bookmarked few webiste but dont know their credibility. will share links tomorrow, once remind me late afternoon if possible

Deal Captain

From whatever little I know I shall post a reply in the morning. On mobile now, shall type from my laptop later

To start off, @Tera_Jija has given some great source, follow that! To set a path here goes

Data Science (DS) can be implemented in any programming language but people mostly choose Python or R because of the sheer number of packages available to make life easy. Every algorithm or every routine task has a package already made for ready use, you just have to put efforts to know the logic behind the algorithm for your understanding as implementation hardly takes 4 to 5 steps.

Most of my steps will be revolving around Python as that is what I have learnt.

1. Learn a programming language – preferably Python or R
2. Learn a Data extraction package, Pandas is the one in Python. Once you learn Pandas you will be able to store/retrieve data from any source and then do data manipulation as well on the retrieved data.
3. Mathematical package. Data is most times handles in multidimensional matrix/arrays and mathematical operations performed. Python has a package called Numpy that’s just as essential as Pandas. Learn this.
4. Visualisation packages. You then have to analyse the patterns in data and relation between data. This can be done using some visualisation packages. Most basic one is Matplotlib package and then you can push to Seaborn, Plotly and Cufflinks.
Once you are done with the above packages you have enough skill to attack DS now.

You can start off with the following steps which are essential before implementing any algorithm in DS.
1. Exploratory Data Analysis
2. Feature Engineering
3. Feature Selection

After this, you can start learning and practicing various algorithms in DS
1. Linera Regression
2. Multiple linear regression
3. Logistic regression
4. Decision trees
5. Random Forest
6. Gradient Boost
7. XG Boost
8. Hierarchical clustering
9. K means clustering
10. DB Scan clustering

Then Ensemble approach to combine multiple techniques

This is a path you can follow till the machine learning part. I cannot guide further for deep learning and natural language processing as I myself just started off with it and will take time to talk about it.

As far as free content goes, youtube has some brilliant free content. If you are aware of a path and what to study it’s easy to get material from thereon. Just search for the package/topic name on youtube and you get tons of reliable material.

cc: @siddudeagarwal

Deal Cadet

Check – out Krish Naik’s vlog on youtube.
I am also a Chemical Engineer and studying DS by reverse engineering only. I started with lockdown starting.

This guide seems pretty good.

Step by step guide for How to Learn Data Science (DS) For Free
1. Python
Corey Schafer (My Choice)
2. Machine Learning with Maths, Statistics and Linear Algebra
Andrew NG applied AI

Krish Naik


Statquest with Josh Starmer

Natural Language Processing


3. Deep Learning
Andrew Ng

Krish Naik

Data Science Projects

Blogs that are freely Available

Feature Engineering Playlist

Feature Selection Playlist