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.
Prerequisites
- Experience in development or data analytics
Courses
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.