TM
21 de jul. de 2020
A great primer on linear regression with labs that help to establish understanding and a project that is focused enough not to be overwhelming, and allows the learner to play around with the concepts
PK
23 de may. de 2017
Very good course taught by Dr. Mine who is as always a very good teacher. The videos are very eloquent and easy to understand. Highly recommend it if you are looking for a basic refresher course.
por Bruno R S
•20 de ene. de 2018
One of the most useful of the series, can be valuable as a standalone course on Regression and Correlation. It is also very accessible.
por Deepak S
•11 de ene. de 2021
Very helpful for beginners and those refreshing their statistical skills alive. Thank you for this course and problem statements.
por David W
•6 de jun. de 2017
The Professor is a clear communicator and has a flair for finding interesting and engaging examples to illustrate the concepts.
por Amarendra S
•23 de abr. de 2020
Excellent course, wonderfully organised and in-depth yet simplistic explanation technique makes understanding regression easy.
por Shao Y ( H
•27 de nov. de 2017
Nice course. Comparing this course with the second and fourth ones in the specialization, this is a rather light-weighted one.
por Andrea P
•21 de mar. de 2018
Very interesting course and well taught!! Advice to everybody also if you have not much previous experience with regression.
por Pedro M
•22 de nov. de 2018
Great course! as a suggestion I Believe Duke should publish new courses on other prediction tools (like SVM, for example)
por ASLI B A
•14 de jul. de 2022
As a medical student, I found the course highly enlightening. With R practice, every week's course was taught me well.
por Lakshmi m
•19 de may. de 2018
Great learning experience 😊 learnt how to Build efficient models by keeping in mind so many statistical techniques
por artur a d p
•16 de abr. de 2022
I really recomend this course! It was very important to my carreer evaluating buildings prices (real state appraisal).
por Aditya G
•28 de may. de 2020
This Module/course was very good. I have learnt many concepts which will be helpful while learning machine learning.
por Gaurav J
•18 de oct. de 2020
It covers all the basics of linear regression and creates a strong base for studying logistic, poisson regression.
por Daniel C J
•7 de ene. de 2019
A great intro to linear regression, both from theoretical and practical point of view. Really enjoyed the course!
por Lilian O
•10 de may. de 2018
The course has enabled me to grasp the concepts on linear regression and how to conduct a statistical analysis.
por Nishit P
•22 de ene. de 2017
Excellent course and content for the beginners. I certainly learned a lot from this course. a Big Thank You!!!
por Elaina K
•21 de jun. de 2022
Good overview of LR and MLR - strong on basic principles, assumptions and a relatively simple applications.
por Arun I
•17 de ago. de 2017
Loved the course; content, exercises and the final assignment we very good. Loved the instructor's energy!!
por VICTOR A I L
•5 de ago. de 2021
It is a very friendly course and requires you to learn and understand the methods, I highly recommend it
por Michael S
•14 de feb. de 2021
Very good course that teaches you the theory behind regression analysis and how to implement is using R.
por Kevin L
•15 de jul. de 2017
Good, detailed course on linear regression and how to perform statistic inference on the coefficients.
por PRIYANKA D
•8 de ene. de 2019
Exceptionally helpful for beginners due to perfect combination of theoretical and practical sessions.
por Jennifer K
•20 de nov. de 2017
This was a very straightforward and thorough class with clear material that was logically structured.
por Abdallah N
•21 de jun. de 2021
Excellent course and excellent teaching. Lots of techniques to learn for regression and modeling.
por Gor S
•23 de mar. de 2020
The course is very beneficial both in terms of learning regression modeling and R programming.
por Juan R
•14 de abr. de 2021
I loved the course, and I am loving the specialization. I have acquired important knowledge.