Program name: Machine Learning using Python

Duration: 12 Weeks

Intended audience: Engineers, Software and IT Professionals, Data Analysts, IT operations, Architects, Technical Managers, Professionals interested in learning Machine Learning

After completing this  programme, participants will be able to:

1. Apply basic and advanced statistical concepts used for data science
2. Apply different methods to import, pre-process and explore data such as importing data from
3. different formats, cleaning data, and summarizing data, dimension reduction and defining correlations
4. Solve classification & function approximation problems using advanced machine learning techniques
5. Design complex algorithms such as deep neural networks for use cases such as image recognition'

Components of the course: 

1. Online live discussions addressing the participants’ doubts will be held at regular intervals
2. Participants can post their queries on a forum
3. Each module will have an assignment that will need to be completed
4. Quizzes will be held at regular intervals
5. Final exam: The participants will be assessed through a combination of command-based Python questions,
6. theoretical, interpretation aspects of the course and solving practical capstone case study using Python

This introductory course will provide insights into the exciting world of Sports Analytics. Participants will be introduced to data science concepts through case studies. Cricket Analytics has revolutionized how we understand the game. From player performance assessment to strategic decision-making on the field, analytics plays a pivotal role.

Our course is designed to introduce you to the fundamentals of cricket analytics, empowering you with the knowledge and skills to uncover hidden patterns, make informed predictions, and contribute to the evolving landscape of this sport.

Offered jointly with IITM Pravartak

Course Objectives:

1. Introduce participants to the fundamentals of sports analytics.
2. Introduce the basics of Python programming.
3. Provide a comprehensive overview of the foundational concepts of data science.
4. Present data visualization techniques.
5. Introduce participants to real-life applications of data science in the field of cricket – using a case study approach.

Learning Outcomes:

1. Introduction to Cricket Analytics:
1. Explore the evolution of cricket analytics and its impact on the game strategies and outcomes.
2. Data Collection and Preparation:
1. Understand that data is collected through various sources.
2. Understand the volume, variety and veracity of sports data.
3. Learn how to source, clean, and organize cricket-related data for analysis.
3. Performance Metrics: 
1. Dive into the key performance indicators used to assess players and teams, such as batting averages, strike rates, BASRA index...
4. Advanced Analysis:
1. Explore advanced topics like visualizing complex cricket data.

Why Enrol?

1. Expert Instructors: 
1. Learn from IITM faculty and industry experts, ensuring you get the best.
2. Earn a Credible Certificate:
1.  Receive an esteemed certificate, showcasing your expertise in cricket analytics, upon completion

Delivery Methodology:

Online live lectures + supplementary video lectures delivered by IITM faculty and industry experts. The program will be primarily taught through a combination of lectures, case studies and assignments. All students can get their doubts clarified through the forum designed for this purpose. Two assignments will be shared. Final marks will be calculated from all the assignments and final examinations (Final Marks = Assignment marks + Final marks). To be eligible for a certificate, one must submit the assignments and complete the final exam of the course.

Program Duration:

32 hours taught over 8 weekends. Online classes will be held on Saturdays and Sundays in the mornings.

This curriculum is developed to help participants appreciate data visualization and creative storytelling using Tableau.

Program name: Data Visualization using Tableau

Duration: 10 hours

Intended audience: MSc. / BSc / Research Scholars

Pre-requisites: Basic knowledge in datasets

After completing this programme, participants will be able to:

1. Compute basic statistical measures from data
2. Conduct exploratory data analysis on the data
3. Draw inferences from analysis
4. Present preliminary results and inferences from analysis
5. Understand Tableau UI components and various ways to establish data connection from a single source or multiple sources
6. Clean data, explore various charts, features and techniques used for visualization
7. Create advanced plots, build Dashboards and Stories within Tableau
8. Perform calculations using Level Of Detail expressions

Components of the course:

1. Interactive live online hands-on sessions using case study approach
2. Participants can post their queries on a forum
3. Each module will have an assignment that will need to be completed
4. Final exam will be conducted by GITAA at the end of the course
5. Certificates will be provided to participants on successful completion of final exam