Looking to break into AI/ML/Data Science career?

Here are the resources to get you started!

Statistics & Probability

Beginner:

• Khan Academy — Statistics: https://www.youtube.com/playlist?list=PL1328115D3D8A2566
• Khan Academy — Probability: https://www.youtube.com/playlist?list=PLC58778F28211FA19
• StatQuest — Statistics: https://www.youtube.com/watch?v=qBigTkBLU6g&list=PLblh5JKOoLUK0FLuzwntyYI10UQFUhsY9

Advanced:

• Intro to probability and statistics MIT 18.05: https://ocw.mit.edu/courses/mathematics/18-05-introduction-to-probability-and-statistics-spring-2014/

SQL

Beginner:

• Datacamp: https://www.datacamp.com/tracks/sql-fundamentals
• Mode: https://mode.com/sql-tutorial/

Practice:

• Hackerrank: https://www.hackerrank.com/domains/sql
• Leetcode: https://leetcode.com/problemset/database/

Machine Learning

Beginner:

• Machine Learning by Andrew Ng: https://www.coursera.org/learn/machine-learning
• Free version of Andrew’s course is on YouTube but it has no hands on exercises: https://www.youtube.com/watch?v=jGwO_UgTS7I&list=PLoROMvodv4rMiGQp3WXShtMGgzqpfVfbU

Advanced:

• Math for Machine Learning: https://www.coursera.org/specializations/mathematics-machine-learning

Practice:

• Kaggle notebooks & competitions: https://www.kaggle.com/docs/competitions

Python

Beginner:

• Datacamp: https://www.datacamp.com/tracks/python-fundamentals

Practice:

• Kaggle notebooks & competitions: https://www.kaggle.com/docs/competitions
• Datacamp projects: https://www.datacamp.com/projects

Deep Learning

• Python (Tensorflow, PyTorch, Keras or other libraries): https://www.datacamp.com/tracks/deep-learning-in-python
• CS6910 IIT Madras: https://www.cse.iitm.ac.in/~miteshk/CS6910.html
• CS231n Stanford (CNNs for Visual Recognition): http://cs231n.stanford.edu/
• CS224n Stanford (NLP with Deep Learning): http://web.stanford.edu/class/cs224n/

Thanks for Reading!

If you like my work and want to support me…

1. The BEST way to support me is by following me on Medium.
2. For data engineering best practices, and Python tips for beginners, follow me on LinkedIn.
3. Feel free to give claps so I know how helpful this post was for you.