Free Online Course on Machine Learning Fundamentals

The University of California, San Diego is offering free online course online on Machine Learning Fundamentals. In this course applicants will understand machine learning’s role in data-driven modeling, prediction, and decision-making.

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. The course will start on January 3, 2018.

Course At A Glance

Length: 10 weeks
Effort:  8 hours pw
Subject: Machine Learning Fundamentals
Institution: University of California, San Diego and edx
Languages: English
Price: Free
Certificate Available: Yes, Add a Verified Certificate for $ 350 USD
Session: Course Starts on January 3, 2018

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Providers’ Details

The University of California, San Diego (UC San Diego) is a student-centered, research-focused, service-oriented public institution that provides opportunity for all. This young university has made its mark regionally, nationally and internationally. Named in the top 15 research universities worldwide, UC San Diego fosters a culture of collaboration that sparks discoveries, advances society and drives economic impact.

About This Course

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.

Learning Outcomes

  • 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

Instructors

Sanjoy Dasgupta

Professor of Computer Science and Engineering, UC San Diego

Requirements

The previous courses in the MicroMasters program: DSE200x and DSE210x

  • Undergraduate level education in:
  • Multivariate calculus
  • Linear algebra

How To Join This Course

  • Go to the course website link
  • Create an edX account to SignUp
  • Choose “Register Now” to get started.
  • EdX offers honor code certificates of achievement, verified certificates of achievement, and XSeries certificates of achievement. Currently, verified certificates are only available in some courses.
  • Once applicant sign up for a course and activate their account, click on the Log In button on the edx.org homepage and type in their email address and edX password. This will take them to the dashboard, with access to each of their active courses. (Before a course begins, it will be listed on their dashboard but will not yet have a “view course” option.)

Apply Now

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