Degree Level Course

Machine Learning Operations (MLOps)

This course aims to give students a comprehensive understanding of Machine Learning Operations (MLOps). MLOps is a paradigm to deploy and maintain machine learning models in production environments reliably and efficiently. The course will cover various aspects of MLOps, including model development, model deployment, monitoring, and optimization. Students will gain hands-on experience with popular MLOps tools and frameworks, enabling them to manage machine learning workflows effectively to deliver robust and scalable ML solutions.

Taught by Rangarajan Vasudevan

Code BSDA5014

Credits 4 Credits

Type Unspecified

Prerequisites

BSCS1002 BSCS2008

12-Week Roadmap

Course Structure & Syllabus

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For details of standard term assessment timelines and exam structures, visit our Academics page.

WEEK 1

Introduction to MLOps: Overview of MLOps and its significance: Key challenges in deploying and managing ML models in production, Comparison of traditional software development, DevOps and MLOps, Key components of MLOps, MLOps workflow, Landscape of MLOps tools and technologies.

WEEK 2

ML Pipelines & Data Management: Overview of data engineering tools and practices, Data management for ML models, ML pipeline automation. DVC overview.

WEEK 3

Data Management - Part 2 : Feature Stores. Motivation, role in ML and Generative AI applications, benefits for MLOps. Feast overview.

WEEK 4

CI/CD for ML Models: Use of version control systems like Git for model development, automated testing & validation, model delivery strategies

Reading List

Prescribed Books & References

Building Machine Learning Powered Applications: Going from Idea to Product - Emmanuel Ameisen - O’Reilly publication
Reliable Machine Learning: Applying SRE Principles to ML in Production - Chen, Murphy, Parisa - O’Reilly publication
Machine Learning Engineering in Action - Ben Wilson - O’Reilly publication
Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems - Martin Kleppmann - O’Reilly publication

Faculty & Experts

About the Instructors

Rangarajan Vasudevan

Co-Founder & Chief Data Officer , Lentra.ai

Rangarajan Vasudevan is the Co-Founder & CDO of Lentra.ai, India’s fastest growing lending cloud. He did “big data” & “data science” before it was fashionable, building data-native applications across industries and geographies over 15+ years.

Ranga joined Lentra by way of an acquisition in June 2022 of his company TheDataTeam, creators of Cadenz.ai customer intelligence platform. Prior to founding TheDataTeam, Ranga served as Director, Big Data with Teradata Corporation’s international business unit. Ranga joined Teradata via the acquisition of Aster Data Systems, where he was a founding engineer and co-invented a company-defining, patented, pattern recognition algorithm. He is a recipient of both the Distinguished Engineer (R&D) and Consulting Excellence awards while at Teradata.

Ranga has degrees in Computer Science from the University of Michigan and IIT Madras.

Other Courses by Instructor:

BSDA5001 • Introduction to Big Data

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