Chevron Left
Back to Wearable Technologies and Sports Analytics

Learner Reviews & Feedback for Wearable Technologies and Sports Analytics by University of Michigan

4.5
stars
38 ratings

About the Course

Sports analytics now include massive datasets from athletes and teams that quantify both training and competition efforts. Wearable technology devices are being worn by athletes everyday and provide considerable opportunities for an in-depth look at the stress and recovery of athletes across entire seasons. The capturing of these large datasets has led to new hypotheses and strategies regarding injury prevention as well as detailed feedback for athletes to try and optimize training and recovery. This course is an introduction to wearable technology devices and their use in training and competition as part of the larger field of sport sciences. It includes an introduction to the physiological principles that are relevant to exercise training and sport performance and how wearable devices can be used to help characterize both training and performance. It includes access to some large sport team datasets and uses programming in python to explore concepts related to training, recovery and performance....

Top reviews

SM

Nov 24, 2021

Love this course, love the content, love the assignments and Peter is great at explaining the terms and concepts

RA

Oct 12, 2024

Suitable course materials, good quizzes and perfect teaching style by professor Peter Brodary

Filter by:

1 - 8 of 8 Reviews for Wearable Technologies and Sports Analytics

By JOSE E L E

•

Jun 12, 2023

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 !!!

By Deepak R E

•

Jul 6, 2023

Excellent introductory course on wearables. Makes us think and apply the knowledge gained from the lectures into practical use. Lecturer was good and I was able understand him clearly. This course needs Python and Pandas skills to be at intermediate level. The reading materials provided were also useful. A small problem I faced was with Week 5 lab -- notebooks which explained the concepts in the lab sessions in the previous weeks, was without any explanation for the last week. I'm still not sure why Z-Score metric was used as performance metric. Hopefully they add more context and explanation for future candidates. Despite the small annoyance, I highly recommend the course. Apply for the financial aid you need it and get certified!

By Nuwaira A

•

Oct 11, 2023

This course is relevant and essential for students and professionals looking to understand how technology impacts the field of sports science. t's likely to be valuable for students and professionals in this field. I wasn't interested in sports science, I joined the course, because it also focus on wearable technology. I want to understanding how these devices work, and their performance analysis. I learn the fundamental related to wearable technology and physiological principles.

By Sean M

•

Nov 25, 2021

Love this course, love the content, love the assignments and Peter is great at explaining the terms and concepts

By REMAS F H A

•

Oct 13, 2024

Suitable course materials, good quizzes and perfect teaching style by professor Peter Brodary

By Moulay A E T

•

Jul 30, 2023

thanks

By Romain C

•

Jul 31, 2022

good !

By Costanza Z

•

Oct 7, 2024

Very interesting. I found the articles and exercises very useful. I would have appreciated some machine learning algorithms