Harvard University · edX
Introduction to Data Science with Python
4.3174 ratingsLearn the concepts and techniques that make up the foundation of data science and machine learning.
University of California, Santa Cruz via Coursera
Bayesian Statistics: Mixture Models
4.563 ratings at CourseraOverview
Bayesian Statistics: Mixture Models introduces you to an important class of statistical models. The course is organized in five modules, each of which contains lecture videos, short quizzes, background reading, discussion prompts, and one or more peer-reviewed assignments. Statistics is best learned by doing it, not just watching a video, so the course is structured to help you learn through application.
Some exercises require the use of R, a freely-available statistical software package. A brief tutorial is provided, but we encourage you to take advantage of the many other resources online for learning R if you are interested.
This is an intermediate-level course, and it was designed to be the third in UC Santa Cruz's series on Bayesian statistics, after Herbie Lee's "Bayesian Statistics: From Concept to Data Analysis" and Matthew Heiner's "Bayesian Statistics: Techniques and Models." To succeed in the course, you should have some knowledge of and comfort with calculus-based probability, principles of maximum-likelihood estimation, and Bayesian estimation.
Syllabus 5
- Basic concepts on Mixture Models 4.5 hours
This module defines mixture models, discusses its properties, and develops the likelihood function for a random sample from a mixture model that will be the basis for statistical learning.
- Maximum likelihood estimation for Mixture Models 3.5 hours
- Bayesian estimation for Mixture Models 3.5 hours
- Applications of Mixture Models 5 hours
- Practical considerations 5 hours
Advantages and disadvantages
Advantages
- Structured courses with graded quizzes, assignments and deadlines you can reset.
- A shareable certificate from the university or company when you pay.
- Financial aid is often approved for students in India (apply 15 days before you need it).
- From University of California, Santa Cruz, a well-regarded name.
- Self-paced: start any time.
- A clear syllabus (5 parts) you can see before you start.
Disadvantages
- Paid after a 7-day free trial (Coursera Plus or per course).
- Some courses can be audited for free, but graded work and certificates need payment.
Some points apply to every course of this kind; see how we rank.
This course is paid. Here is how to take it for free
- Free trials: You can start a 7-day free trial for many individual courses, Specializations, or a Coursera Plus subscription to test full course features. Cancel before the seventh day if you do not want to be charged.
- Financial aid: If you cannot afford the fee for a certificate, you can apply for financial aid through the link on the course home page by filling out an application about your background and goals.
Taught by
- Abel RodriguezProfessor, Applied Mathematics and Statistics
University of California, Santa Cruz is in Tier 2: excellent universities and the companies that build the technology of our institution ranking (80/100).
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