Learning Path for ‘Machine Learning’

Here is our learning path for becoming proficient in Machine Learning.

(See all our learning paths here)

Register here for instructor-guided-self-learning series.


  • Experience in development or data analytics


Starting point: Software Engineers / Data Analysts

1 – Python Basics

Introduces Python language programming.  Python is a very dominant language for Machine Learning programming.
course outline (2-day version)

2 – Data Analytics with Python

Learn the basics of data analytics using Numpy, Pandas, and visualization libraries.
Course outline (2-day version)

3 – Machine Learning Essentials with Python

Learn Machine Learning basics and algorithms and apply them using Python’s sci-kit package.
Course outline (3 days)

4 – Deep Learning with Tensorflow

Learn how to build advanced algorithms in deep learning for classification and image recognition with Tensorflow 2.
Course outline (3 days)

5 – Team Project

We highly recommend doing an end-to-end machine learning project using everything we learned.

Congratulations: Now you are a Machine Learning practitioner.

Advanced Track

Continue on to more specialized tracks

6 – AI for Computer Vision and Image Analysis

Learn cutting edge algorithms to deal with images
Course outline

7 – AI for Natural Language Processing (NLP)

Learn cutting edge algorithms to analyze text.
Course outline

Download ‘ML Learning Path’ in PDF

Congratulations: Now you are an Advanced Machine Learning practitioner.