With so many R Statistics & Machine Learning courses around, why enroll for this ?
Regression analysis is one of the central aspects of both statistical and machine learning based analysis. This course will teach you regression analysis for both statistical data analysis and machine learning in R in a practical hands–on manner. It explores the relevant concepts in a practical manner from basic to expert level. This course can help you achieve better grades, give you new analysis tools for your academic career, implement your knowledge in a work setting or make business forecasting related decisions. All of this while exploring the wisdom of an Oxford and Cambridge educated researcher.
My name is MINERVA SINGH and I am an Oxford University MPhil (Geography and Environment) graduate. I recently finished a PhD at Cambridge University (Tropical Ecology and Conservation). I have several years of experience in analyzing real life data from different sources using data science related techniques and producing publications for international peer reviewed journals. This course is based on my years of regression modelling experience and implementing different regression models on real life data. Most statistics and machine learning courses and books only touch upon the basic aspects of regression analysis. This does not teach the students about all the different regression analysis techniques they can apply to their own data in both academic and business setting, resulting in inaccurate modelling. My course will change this. You will go all the way from implementing and inferring simple OLS (ordinary least square) regression models to dealing with issues of multicollinearity in regression to machine learning based regression models.
Instructor Details
Courses : 17
Specification: Regression Analysis for Statistics & Machine Learning in R
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24 reviews for Regression Analysis for Statistics & Machine Learning in R
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Price | $11.99 |
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Provider | |
Duration | 7.5 hours |
Year | 2020 |
Level | All |
Language | English |
Certificate | Yes |
Quizzes | No |
$94.99 $11.99
Ty Werbicki –
Good introduction to navigating R for someone who is new. Very superficial in terms of harnessing each algo used.
Rat Din –
She covered machine learning algorithms very perfectly. I am glad I chose this course over the other available courses.
Amitaf Bacchon –
The instructor answer properly for your all requirements. Overall useful and a good start for a beginner
Raja Badsha –
I learnt more advanced techniques from the course. All the coding text in the course is clear and readable.
Nosto Chele –
The overall course design is great because it is a great experience for me.
Jensi Kerat –
I think this course is pretty good. It gave me more confidence to work with R through a lot of practice. Thank you!
Haifeng Wu –
Half of the contents were little basic for me and the instructor’s illustration was not as fluent, even had to correct some of the previous videos. And all the data sets used in this course were over simplified compared to real world examples. Hope this can be improved in the future
Anya Rao –
Very detailed material on regression techniques in R
Anil Kumar Pandey –
Very knowledgeable and useful program for me.
Indranil Mukherjee –
The course was indeed helpful
Gulizar –
l need some advance information
Himadree Chakrabarty –
superb teacher learning a lot
sushma Pandey –
Informative and knowledgeable program for me
Ronald Gik –
perfect for my purpose.
Claudia Macrone –
This was excellent information! I love the instructor and learned a ton!
Greta Wong –
It devotes too much time to OLS but I like the introduction to other ML models too
Ariel Sell s Gras –
Me est clarificando aspectos del tema que ten a en nebulosa.
Melani Yossi –
Excellent course & the topics covered here are not available in any other course on Udemy or outside.
Srinivas Bikkina –
To the point lecture and very clear.
Steven A. Melnyk –
As an instructor, I find the speed too slow; in addition, the instructor reads the overheads not what I expected in such a course. Finally, this course seems to be pieced together. For example, in section 3 Difference between Statistical and Machine Learning, the instructor refers to the completion of a past session there was no past session dealing with the issues raised!
Swarali Shridhar Joshi –
good
Bethaney Scott –
The content was great but the delivery was sometimes a bit off.
Shiv Pandey –
Good to learn with a superior knowledge of trainer
Ashwani –
Outstanding course