Created by:  University of California, Santa Cruz

  • Matthew Heiner

    Taught by:  Matthew Heiner, Doctoral Student

    Applied Mathematics and Statistics
LevelIntermediate
Commitment5 weeks of study, 4-6 hours/week.
Language
English
How To PassPass all graded assignments to complete the course.
User Ratings
4.8 stars
Average User Rating 4.8See what learners said
Syllabus

FAQs
How It Works
Trabajo del curso
Trabajo del curso

Cada curso es como un libro de texto interactivo, con videos pregrabados, cuestionarios y proyectos.

Ayuda de tus compañeros
Ayuda de tus compañeros

Conéctate con miles de estudiantes y debate ideas y materiales del curso, y obtén ayuda para dominar los conceptos.

Certificados
Certificados

Obtén reconocimiento oficial por tu trabajo y comparte tu éxito con amigos, compañeros y empleadores.

Creators
University of California, Santa Cruz
UC Santa Cruz is an outstanding public research university with a deep commitment to undergraduate education. It’s a place that connects people and programs in unexpected ways while providing unparalleled opportunities for students to learn through hands-on experience.
Pricing
Comprar cursoAuditar
Accede a los materiales del curso

Available

Available

Accede a los materiales con calificación

Available

Not available

Recibe una calificación final

Available

Not available

Obtén un Certificado de curso para compartir

Available

Not available

Ratings and Reviews
Rated 4.8 out of 5 of 43 ratings

I thoroughly enjoyed participating in this course, and I do think that I learned a fair number of skills of real conceptual and practical value. Thanks to the instructors' team for their dedicated efforts.

This course is a great start for everyone who wants to dive into Bayesian Statistics. Very clear and helpful.

Excellent course, with deep explanation of difficult topics in Bayesian statistics and Marcov chain applications. Good quizzes and enough time to complete them. Recommend to all interested in probability theory.

This course was fantastic. It combined detailed learning materials with frequent and comprehensive assessments. While managing to cover everything from the basics of MCMC through to the use of a number of different bayesian models. My only issue with the course was that the learning materials encouraged copy-pasting code and often didn't properly explain the choice of priors and other details about the chosen models.