Data Science Resources – Basics

There are plenty of great Data Science Resources available on the internet, free and paid. However, it can be overwhelming while deciding what resources to refer while preparing for placements. We have listed out resources that helped us in getting internships and placements.

R/ Python

Note: Don’t get into the debate of R vs. Python. Pick one and be awesome at that. Mastering one will allow you to master many.

Free Certified

  1. Kaggle Courses (Python)
  2. UpGrad (Python)

Paid

  1. DataCamp – Data Scientist in Python
  2. DataCamp – Data Scientist in R

Machine Learning

Free Book

  1. An Introduction to Statistical Learning: With Applications in R – James et al.

Free Course

  1. MIT Open Learning Library – 6.036 Introduction to Machine Learning (Python)

Free Certified

  1. Kaggle – Machine Learning in Python

Paid

  1. DataCamp – Machine Learning Scientist with Python
  2. DataCamp – Machine Learning Scientist with R

Projects

  1. Data Analysis Guide 2.0 in R
  2. Data Analysis Guide 2.0 in Python
  3. Comparative Study of Classification Techniques on Credit Defaults by Shreyashi et al.
  4. Forecasting of a Time Series (Stock Market) Data by Shreyashi et al.
  5. Kaggle
  6. Paid – DataCamp Projects

SQL

Book

  1. SQL in 10 Minutes a Day, Sams Teach Yourself by Ben Forta

Tableau/ PowerBI (Coming Soon)

  1. Free Training Videos by Tableau

.

For any query, suggestion or feedback about Data Science resources, please reach out to us on LinkedIn.

If you can contribute by talking about your interview experience, it will definitely create an impact. Please fill this form to help students get a perspective about the interview structure and questions.

You can read other articles here.

Cheers and Best!