Machine Learning algorithms
Artificial Intelligence algorithms
Information Retrieval algorithms
Deep Learning algorithms
Quantum Computing algorithms
Computer Vision algorithms
Natural Language Processing algorithms
Requirements
- Understanding of Calculus and Linear Algebra will help better understand most of the concepts discussed here. But you can look for helpful resources alongside studying this course.
Description
This course focuses on the theoretical aspects of the field of Data Science and Machine Learning. It helps the students to quickly gain an in-depth overview of different algorithmic techniques used in various domains and applications. This course features external links to further enhance the experience and reinforce the concepts acquired. It also provides easy explanations of popular and useful research papers that are driving this field forward.
Who this course is for:
- Aspiring and Professional Data Scientists and Machine Learning Engineers.
- Students pursuing their PhD and looking for a refresher course.