Voltar para Bayesian Statistics: From Concept to Data Analysis

estrelas

2,957 classificações

This course introduces the Bayesian approach to statistics, starting with the concept of probability and moving to the analysis of data. We will learn about the philosophy of the Bayesian approach as well as how to implement it for common types of data. We will compare the Bayesian approach to the more commonly-taught Frequentist approach, and see some of the benefits of the Bayesian approach. In particular, the Bayesian approach allows for better accounting of uncertainty, results that have more intuitive and interpretable meaning, and more explicit statements of assumptions. This course combines lecture videos, computer demonstrations, readings, exercises, and discussion boards to create an active learning experience. For computing, you have the choice of using Microsoft Excel or the open-source, freely available statistical package R, with equivalent content for both options. The lectures provide some of the basic mathematical development as well as explanations of philosophy and interpretation. Completion of this course will give you an understanding of the concepts of the Bayesian approach, understanding the key differences between Bayesian and Frequentist approaches, and the ability to do basic data analyses....

GS

31 de ago de 2017

Good intro to Bayesian Statistics. Covers the basic concepts. Workload is reasonable and quizzes/exercises are helpful. Could include more exercises and additional backgroung/future reading materials.

JB

16 de out de 2020

An excellent course with some good hands on exercises in both R and excel. Not for the faint of heart mathematically speaking, assumes a competent understanding of statistics and probability going in

Filtrar por:

por Sinkovics K

•1 de mai de 2020

This is a wonderful course in Statistics that I would highly recommend to everyone who wants to take a learning path into the world of Bayesian inference and refresh their knowledge of numerous statistics concepts involved. The lectures provide excellent in-detail explanations, and additional reading material fill in the gaps if some of the concepts or derivations weren't shown in the lecture in full.

por Michał K

•24 de out de 2017

Excellent course. For such broad discipline I'm sure it was difficult to choose most important material to fit 4-week course, yet professor did it perfectly. I'd love to see this course in Python, but I guess I can't have everything ;) I'd also love see some examples of using probabilistic programming packages, like Stan or PyMC3 in more real-life problems - I would give 6/5 stars for it!

por Paulina S

•10 de mar de 2017

This is my first course on Coursera and I am delighted by the construction, how it was led by the instructor and what I learned. Quizzez are great, I spent on some quite a bit of time, but I feel they really checked if I understand the concepts and calculations. The questions during the video are also an excellent idea to check if you follow. All in all I am very happy I took this course!

por Kostya T

•3 de ago de 2019

I really enjoyed this course, the videos are fairly short with focus on exercises and there is a nice narrative throughout the course. Sometimes I needed to watch videos again because explanations were too fast for me to follow in real time, but I definitely enjoyed presentation style of Prof. Herbert Lee. Will be following the course up with "Techniques and Models" to learn about MCMC.

por Alberto S

•29 de jun de 2017

Followed the course in order to fill a gap I had in statistics knowledge, as I'm very interested in machine learning - deep learning, and always came upon things as MLE without really knowing well what they were talking all about. Really a very good course to get an understanding! Well explained, though maybe you'll need to brush up your Algebra and Calculus a bit to be able to follow...

por MaoJie T

•19 de nov de 2019

It's a fantastic course, which guides me to know what is Bayesian statistics. Before joining this course, I try my best to learn Bayesian Statistics but it's failed. However, I really grasped some key points and knowledge of Bayesian Statistics and I will join the following course about Bayesian Statistics to get more. Thanks for the professor. I am appreciated for it.

por Matteo V

•26 de jun de 2017

Great course that introduces the fundamentals of Bayesian Statistics. Useful for becoming familiar enough with the ideas to use in basic analysis provided you have some experience with frequentist statistical methods. For my studies, this course allowed me access to the Bayesian statistical material that is often encountered in phylogenetic analysis in bioinformatics.

por Ian M

•16 de ago de 2019

I think this was a very helpful course, for me personally I learn better with "real" examples, so i think if there were more of those earlier on, that would have been more helpful. I also use Python, and would prefer to use Python, so it would be nice if there were instructions on that in addition to R/Excel. Spent a lot of time translating between R and Python.

por Shubham A

•11 de nov de 2017

I strongly recommend this course to those who are interested in learning theoretical concepts that build Machine Learning statistics especially Bayesian. The course content was well organized and the professor presented the concepts in a very engaging way. Relevant and appropriate examples and in-video quizzes were very helpful in understanding the theory.

por Aditya M

•3 de fev de 2020

A great course to learn not only Bayesian Statistics, but covers statistics in general to a great degree. The best part is the exercise, which are almost perfect to learn the course material. After doing tens of MOOCs everywhere, I find this course unique in terms of pushing students to apply the concepts. I loved this course and enjoyed learning with it.

por Suleyman K

•11 de fev de 2020

This is one of the best online courses I took. This is coming from an ex-Professor who taught 13 years. The material basic and is brief, but to the point and very well organized and presented. Having some background in statistics helps as some important details are skimped. In a such a short time, I learned well the concept of about Bayesian statistics.

por Ron A

•12 de abr de 2017

Excellent course. Professor Lee did a first-rate job of giving the intuition for Bayesian methods and building the foundations for further study of the topic. The course is short and to the point, but that is a feature and not a bug. It will prepare you to take further courses in Bayesian statistics or to study the topic on your own. Highly recommended.

por Lynn

•24 de jul de 2020

I really enjoyed this course!

Lectures were clear and given at a good pace. Thank you for the effort at putting in comments for all the questions on the quizzes. This really cemented my understanding and this has been the first time I have really gotten through Bayes theorem, which has been my downfall in previous statistics classes.

Good job Dr Lee!

por Dennis L W

•17 de set de 2016

Out of 15 online courses I have taken over the last 3 years, this is the best. Professor Lee presents rather difficult material in a clear, detailed, style. The lesson quizzes are remarkably useful; it seems real care has been taken in aligning the questions with the key points in the lectures, and in furthering one's understanding of the same.

por Mark S

•8 de fev de 2017

I found this course to be really useful. It did progress through the math a bit quickly for my liking, but it was paced very appropriately and the discussion forums were helpful. Excellent examples are contained and I loved how both R and Excel modules were leveraged. Looking forward to seeing more Bayesian courses on Coursera in the future.

por Haozhe ( X

•24 de abr de 2020

Great course for intro to Bayesian. Before deciding to learn bayesian, I expect to choose a course which could explain concept in a simple way but, at the same time, having enough practice. This course matches my need. After taking this course, I would recommend it to anyone who want to learn some bayesian for further machine learning studies.

por David D

•27 de fev de 2019

Really loved this course. I am relatively new to Statistics but very familiar with the rest of the mathematical tools used in this class (Integration, sets, etc). After finishing the class, I was immediately able to apply Bayesian Inference to my job. Things were explained well, and made sense after re-watching once or twice. Excellent course!

por Huy P T

•9 de jul de 2022

A very challenging course. Week 1 was relatively easy. However, starting from week 2, the material was exceedingly hard. I almost gave up but then decided to take a break and come back to it.

It took me a total of 50 hours to complete the course. The main challenge was the mental shift from frequentist (taught in school) to Bayesian paradigm.

por Polano M

•11 de mar de 2018

Great introduction to Bayesian Statistics.

Prof. Lee uses the right approach with a theoretical introduction that helps to graps the concepts with a right balance of math and intuition. This was my first exposure to the bayesian approach to statistics and after this course I want to learn more, both on the pratical and the theoretical side.

por TERENCE Y

•19 de set de 2017

An excellent introduction to Bayesian Analysis with some practical examples and applications. The lessons serve as a solid foundation towards understanding the philosophical underpinnings of the Bayesian approach to decision analysis under uncertainty. Thanks to Prof Herbert Lee for making the easy to understand without sacrificing rigour.

por John C B

•22 de jul de 2021

I really enjoyed this course. I thought the concepts were well explained, with a good balance of mathematical formalism and practical insight. I already had a strong background in probability and statistics, and I realize the course would be harder for those who do not--however, even then, I think the challenge is well worth the effort.

por Brandon H

•6 de mar de 2018

This is a great course! Much better (and cheaper) than the course I took in grad school. Full of practical knowledge, and isn't too overwhelming on the mathematics/statistical theory. It's just right. Good for anyone interested in Bayesian statistics, though some background with probability distributions may help climb the learning curve.

por Andres F

•11 de jul de 2022

Excellent course.

It provides a strong basis for understanding the topics and many examples to see applications.

The topics are introduced gradually, and the quizzes are well organized to provide a step-by-step understanding.

I particularly enjoyed the conceptual and intuitive discussions of all major topics provided by the instructor.

por Natasha

•27 de dez de 2016

I really enjoyed this course. The lectures were short and clearly explained, and particularly highlighted why Bayesian statistics is different and what is useful about it. I would have like a bit more walk-through on some of the derivations in weeks 3 and 4. More R exercises and further resource recommendations would have been useful.

por Galley D

•11 de set de 2017

Outstanding course to understand Bayesian statistics. Teacher is very pedagogical and the course delivery with equations written on the transparent board make everything easy to follow.

As an area for development, I would have like more information on Bayesian linear regression in week 4, through background lecture or dedicated video.

- Analista de dados do Google
- Gestão de projetos no Google
- Design de UX no Google
- Suporte de TI do Google
- Ciência de dados da IBM
- Analista de dados da IBM
- Análise de dados da IBM com Excel e R
- Analista de Cibersegurança da IBM
- Engenharia de dados da IBM
- Desenvolvedor de nuvem full stack – IBM
- Marketing em mídias sociais do Facebook
- Análise de marketing do Facebook
- Representante de desenvolvimento de vendas da Salesforce
- Operações de vendas da Salesforce
- Contabilidade da Intuit
- Preparação para a Certificação em Google Cloud: Cloud Architect
- Preparação para a Certificação em Google Cloud: Cloud Data Engineer
- Inicie sua carreira
- Prepare-se para uma Certificação
- Amplie suas qualificações profissionais

- cursos gratuitos
- Aprenda um idioma
- pythonpython
- Java
- web designweb design
- SQL
- Cursos grátis
- Microsoft Excel
- Gestão de projetos
- Segurança cibernéticaSegurança Cibernética
- Recursos humanos
- Cursos gratuitos de ciência de dados
- falar inglês
- Redação de conteúdo
- Desenvolvimento Web completoDesenvolvimento Web Completo
- Inteligência artificial
- Programação em C
- Habilidades de comunicação
- Blockchain
- Veja todos os cursos

- Competências para equipes de ciência de dados
- Tomada de Decisões Baseada em Dados
- Habilidades de engenharia de software
- Habilidades Pessoais para Equipes de Engenharia
- Habilidades Administrativas
- Habilidades de marketing
- Habilidades para Equipes de Vendas
- Habilidades de Gerente de Produto
- Habilidades Financeiras
- Cursos de ciência de dados populares no Reino Unido
- Beliebte Technologiekurse in Deutschland
- Certificações populares de segurança cibernética
- Certificações populares de TI
- Certificações populares de SQL
- Guia de carreira de gerente de marketing
- Guia de carreira de gerente de projeto
- Habilidades de programação em Python
- Guia de carreira de desenvolvedor Web
- Competências de análise de dados
- Habilidades para designers de UX

- Certificados MasterTrack®
- Certificados profissionais
- Certificados universitários
- Graduações em negócios e MBA
- Graduações em Ciência de Dados
- Graduações em Ciência da Computação
- Graduações em análise de dados
- Graduações em Saúde Pública
- Graduações em ciências sociais
- Graduações em gestão
- Graduações nas melhores universidades europeias
- Mestrados
- Bacharelados
- Graduações com uma trajetória de desempenho
- Cursos em Ciências (BSc)
- O que é uma licenciatura?
- Quanto tempo leva um mestrado?
- Um MBA on-line vale a pena?
- 7 maneiras de pagar pela pós-graduação
- Ver todos os certificados