SS
Really great and informative course, loved the material and the assignments!
Sports analytics has emerged as a field of research with increasing popularity propelled, in part, by the real-world success illustrated by the best-selling book and motion picture, Moneyball. Analysis of team and player performance data has continued to revolutionize the sports industry on the field, court, and ice as well as in living rooms among fantasy sports players and online sports gambling. Drawing from real data sets in Major League Baseball (MLB), the National Basketball Association (NBA), the National Hockey League (NHL), the English Premier League (EPL-soccer), and the Indian Premier League (IPL-cricket), you’ll learn how to construct predictive models to anticipate team and player performance. You’ll also replicate the success of Moneyball using real statistical models, use the Linear Probability Model (LPM) to anticipate categorical outcomes variables in sports contests, explore how teams collect and organize an athlete’s performance data with wearable technologies, and how to apply machine learning in a sports analytics context. This introduction to the field of sports analytics is designed for sports managers, coaches, physical therapists, as well as sports fans who want to understand the science behind athlete performance and game prediction. New Python programmers and data analysts who are looking for a fun and practical way to apply their Python, statistics, or predictive modeling skills will enjoy exploring courses in this series.
SS
Really great and informative course, loved the material and the assignments!
AB
Excellent course, really enjoyed it even as someone who doesn't follow baseball
WV
Very interesting course, even though some of the data prep is kind of weird it's nice to see things done a bit differently
RA
Suitable course materials, good quizzes and perfect teaching style by professor Peter Brodary
KL
Provide solid foundation for beginning supervised ML
AM
Complete and accessible course for everybody who wants to experience how statistics and econometrics can be used in sports contexts.
MH
An excellent way to develop Python skills to interesting topics.
BB
I found the material from weeks 2 and 4 very interesting!
SM
Love this course, love the content, love the assignments and Peter is great at explaining the terms and concepts
AM
Well-structured notebook, resourceful, applicable to real-world projects, clear and entertaining teaching. Highly satisfied. One of the best modules in the entire specialization.
AB
Fantastic introduction to Python, engaging and I enjoyed that lots of different sports were discussed.
JB
I learned a lot about baseball and the Python language. Thank you for the great course.
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This course does a very poor job of actually teaching the concepts presented in it. There is a lot of "copy/paste" instruction, with almost no explanation of what is being done or why, at either the technical level (i.e. why are calling this function or method) or a the theoretical level (i.e. why a visualization or data interaction is useful). It does touch on a many basic foundation for interacting with data (which is the only reason I'm not giving it 1 star), but from an actual instruction perspective, this the worst courses I have finished on Coursera.
Experience in Python is needed.
Great course! The lectures focus on the hands-on application of analytics techniques; with slides of theory and math kept to a minimum. The quizzes are of easy to moderate difficulty, and help reinforce the concepts learnt in the lecture. The material of the course will be of interest to anyone who enjoys extracting insights from data, even if you aren't much of a sports fan. I’m excited for the next course in the specialization!
The course content was intriguing. However, it definitely needs updating. There are times where assignment instructions are incomplete, or there are discrepancies between what is shown in the lecture and what is in the notebooks. There are also times where what is in the assignment quizzes doesn't match up with the actual data in the assignment notebooks.
I didn't get a lot out of some of the weeks, as it felt like the instructor was just reading word for word what was written in the notebooks, not adding any additional commentary or explanation. Furthermore, I wish they would have dove deeper into some of the statistics and math behind some of the concepts they showed. They would introduce a concept a lot of times, but not explain what it meant or how it related to other concepts we had learned.
Overall it was a good course. It covers the basic of Sports Analytics and it has a lot of good examples and datasets.
Directions are not clear when working on programing assignments and quizzes.
IN GENERAL TERMS I LIKE IT ALL, WITH THE EXCEPT THAT I COULD NOT FINISH THE SPECIALIZED PROGRAM BECAUSE I DID NOT UNDERSTAND THE QUESTIONS OF COURSE NUMBER 5, THE TEACHER ASKS THINGS THAT HE DOESN'T EXPLAIN, AND WHAT IT EXPLAINES DOES NOT DO IT WITH CLARITY !!!
I AM NOT AN EXPERT IN PYTHON, BUT LITTLE BY LITTLE I WAS LEARNING SOMETHING NEW, BUT COURSE NUMBER 5 SEEMED IMPOSSIBLE.
I AM AN EXPERT IN ANALYZING SPORTS STATISTICS, AND I TAKEN THE SPECIALIZED PROGRAM BECAUSE I WANTED TO LEARN NEW THINGS THAT WILL HELP ME IN MY JOB; AND IN COURSE 4 I LEARNED MANY NEW AND VERY INTERESTING THINGS; BUT I COULDN'T FINISH THE SPECIALIZATION BECAUSE COURSE NUMBER 5 IS ANTI-PEDAGOGICAL
IF YOU ARE NOT AN EXPERT IN PYTHON I DO NOT RECOMMEND THIS COURSE !!!
Me parece un excelente curso para un primer vistazo sobre como analizar el rendimiento tanto individual como de equipo en deportes, me pareció muy interesante mezclar habilidades de ciencia de los datos junto con mis gustos por los deportes.
An excellent way to get hands-on experience exploring sports data in Python/R
Great material and well paced for people working. One instructor is a bit green though.
The course is moderately interesting from Module 1 to Module 5, but it is not entirely clear who the target audience of the course may be. The course presumes some existing knowledge of Python programming, statistical methods, and the sports included in the course. However, it is not entirely clear to me what learners already equipped with this knowledge are supposed to benefit from this course. In the course, it is demonstrated how these statistical methods can be applied to some selected sports in Python (R is also supported to some moderate extent), but learners who already know Python, statistical methods, and the sports will probably already be able to do this by themselves. If the course is supposed to provide that little extra push that is required to put these all together, it's fine, but you will not actually learn any of these categories, only how to apply them in a very specific context. OK, so then we reach Module 6, where all this collapses in a thunderous rumble. The amount of omissions, glitches, oversights, discrepancies, and pure nonsense in Module 6 is just way too much to even start listing and makes one think what is put out to customers as the final product is in fact some sort of vague first draft of the module, waiting to be further developed and reviewed by an army of content developers. Very disheartening, and one doesn't quite understand why Coursera or the UoM would voluntarily put out such rubbish only to embarrass themselves, when they strictly speaking do not really have to do so. Really, why? It's a mystery! For the moderately engaging and useful content of the first five modules, I am giving this course 2 stars, but the amount of damage Module 6 has visited upon the perceived quality of this course and the reputation of Coursera and the UoM is so devastating that any further benevolence is just simply out of the question. Ah yes, and it would have been great to have a lecturer in statistics who can pronounce the word "statistics" once I am charged for the lectures! Thank you for reading my review.
O curso é incrível, e nas duas últimas semanas dificulta bastante. É necessário muito foco desde o início para que o processo de aprendizagem seja mais fluído. Vale muito a pena fazer.
Great course. Although this course focuses on sports analysis, the analyzing process I learned from it can apply to any other areas of analysis.
Complete and accessible course for everybody who wants to experience how statistics and econometrics can be used in sports contexts.
Best course to interact with data representation programming and libraries, especially for the great sports fan.
Excellent course! All of a sudden, I understand statistical concepts I struggled to grasp in undergrad.
Fantastic introduction to Python, engaging and I enjoyed that lots of different sports were discussed.
I've never been more excited of doing a regression model in my life! Amazing content.
This course was amazing I learned a lot of new things by doing this course .
Thorough and with lots of practice to help retain information.