Machine Learning by UC San Diego

UC San Diego: Understand fundamentals of machine learning and it’s role in data-driven modeling, prediction, and decision-making.

What is the Machine Learning course at UC San Diego like?

Do you want to build systems that learn from experience? Or exploit data to create simple predictive models of the world?

In this course, part of the Data Science MicroMasters program, you will learn a variety of supervised and unsupervised learning algorithms, and the theory behind those algorithms.

Using real-world case studies, you will learn how to classify images, identify salient topics in a corpus of documents, partition people according to personality profiles, and automatically capture the semantic structure of words and use it to categorize documents.

Armed with the knowledge from this course, you will be able to analyze many different types of data and to build descriptive and predictive models.

All programming examples and assignments will be in Python, using Jupyter notebooks.

What you’ll learn

Classification, regression, and conditional probability estimation
Generative and discriminative models
Linear models and extensions to nonlinearity using kernel methods
Ensemble methods: boosting, bagging, random forests
Representation learning: clustering, dimensionality reduction, autoencoders, deep nets

Meet the instructor

Professor Sanjay Dasgupta

Professor Computer Science and Engineering

University of California San Diego

At Azent, we have a strong commitment to education and career development. We are passionate about bringing global education to the doorsteps of students all over India.