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Quick Facts

Medium Of Instructions	Mode Of Learning	Mode Of Delivery
English	Self Study	Video and Text Based

Course Overview

Introduction to Machine Learning in Sports Analytics is an intermediate-level online course provided by Coursera which is one of the leading online course providers. The online certification programme will guide the learners on how to use machine learning in sports analytics. Offered by Coursera, Introduction to Machine Learning in Sports Analytics Certification Course is the last course in the Sports Performance Analytics Specialization offered by the University of Michigan.

Introduction to Machine Learning in Sports Analytics Certification Syllabus will discuss the machine learning techniques, the prediction of athletic outcomes with machine learning, and many more. Introduction to Machine Learning in Sports Analytics Certification by Coursera can be taken by learners who have familiarity with Python.

The Highlights

Provided by Coursera
Offered by the University of Michigan
Self-Paced Learning Option
100% Online Course
Intermediate level course
Around 13 Hours to Complete
Flexible Deadlines
Shareable Certificate
Financial Aid Available

Programme Offerings

English videos with multiple subtitles
Shareable Certificate
Financial aid available
Shareable Certificates
Self-Paced Learning Option
Course Videos & Readings
practice quizzes
Graded Assignments with peer feedback
graded Quizzes with feedback

Courses and Certificate Fees

Certificate Availability	Certificate Providing Authority
yes	UM–Ann ArborCoursera

The learners can join the online programme either in the audit mode or by paying the fee. The Introduction to Machine Learning in Sports Analytics Certification Fee is decided based on the number of months the candidates want to stay on the programme and learn. The month-wise fee structure prescribed by Coursera is given in the table below:

Introduction to Machine Learning in Sports Analytics Fee Structure

Duration	Amount in INR
1 Month	INR 3,177

What you will learn

Machine learning

By the end of the Introduction to Machine Learning in Sports Analytics Training, the candidates will understand:

Application of ML algorithms to foresee the outcomes of the sport.
Machine learning algorithms
Support vector machines (SVM)
Decision trees
Random forest
Linear and logistic regression

Who it is for

Data AnalystMachine Learning Engineer

Introduction to Machine Learning in Sports Analytics Classes is highly recommended for professionals like ML Engineer, Data Analyst and many more.

Admission Details

Step 1 -Browse the official URL

https://www.coursera.org/learn/machine-learning-sports-analytics

Step 2 -Start learning the online programme ‘Introduction to Machine Learning in Sports Analytics’ by choosing the option ‘Enroll’.

The Syllabus

Videos

Introduction
What is Machine Learning?
The Machine Learning Workflow
Our First Model: NHL Game Outcomes
Building the Logistic Regression Model
Considerations in Deploying The Model
Wrap Up

Readings

Help Us Learn More About You
Course Syllabus
Assignment 1 Programming Solution

Practice Exercise

Assignment 1

Videos

Introduction to Support Vector Machines (SVMs)
Polynomial Support Vector Machines
Cross Validation
A Real World SVM Model: Boxing Punch Classification

Readings

(Optional) - An evaluation of wearable inertial sensor configuration and supervised machine learning models for automatic punch classification in boxing
Assignment 2 Programming Solution

Practice Exercise

Assignment 2

Videos

Decision Trees
A Multiclass Tree Approach
Model Trees
Tuning and Inspecting Model Trees

Readings

Assignment 3 Programming Solution
UM Master of Applied Data Science (optional)

Practice Exercise

Assignment 3

Videos

Ensembles
Additional Machine Learning Concepts
Baseball Hall of Fame Prediction
Baseball Hall of Fame Demonstration Part 1
Baseball Hall of Fame Demonstration Part 2

Readings

Free Deepnote Notebook Service
Putting Your Skills to the Test!
Post Course Survey

Practice Exercise

Assignment 4

Instructors

UM–Ann Arbor Frequently Asked Questions (FAQ's)

1: What are the enrollment options for the learners to pursue the Introduction to Machine Learning in Sports Analytics online course?

he online certification programme can be pursued by the learner in two different enrolment methods; they are audit mode and enrolling by paying the fee prescribed by Coursera.

2: Who is the developer of the Introduction to Machine Learning in Sports Analytics online certification supervising the online programme?

The online course is developed and presented by Christopher Brooks, the assistant professor at the School of Information.

3: Does Coursera provide financial aid for the learners who struggle to meet the fee specified by Coursera?

Yes, Coursera offers the learners facing difficulty in making the payment of the fee financial aid based on their financial background.

4: How many hours must the candidates need to cover the course?

The course can be completed by the students within about 13 hours. However, the learners can take the course as per their time and convenience as it is designed in a flexible nature.

5: Does Coursera offer the learners certification after the completion of the course?

Coursera will award the learners with a shareable certificate only if they enrolled by paying the fee.