A Foundation For Machine Learning and Data Science

This course is designed by an industry expert who has over 2 decades of IT industry experience including 1. 5 decades of project/ program management experience, and over a decade of experience in independent study and research in the fields of Machine Learning and Data Science. The course will equip students with a solid understanding of the theory and practical skills necessary to learn machine learning models and data science.

When building a high-performing ML model, it's not just about how many algorithms you know; instead, it's about how well you use what you already know. Throughout the course, I have used appealing visualization and animations to explain the concepts so that you understand them without any ambiguity. This course contains 9 sections: 1.

Introduction to Machine Learning 2. Anaconda - An Overview & Installation 3. JupyterLab - An Overview 4.

Python - An Overview 5. Linear Algebra - An Overview 6. Statistics - An Overview 7.