03 — Curriculum
Course content
4 sections · 11 lectures
ADaSci Academy
Production-Grade MLOPs Primer
This 3-hour intensive course provides a hands-on introduction to modern MLOps practices using MLflow, Weights and Biases, and CometML. Participants will learn how to track experiments, manage model versions, compare runs…
4,094+ enrolled
3 hours
Intermediate
01 — Overview
About this course
This 3-hour intensive course provides a hands-on introduction to modern MLOps practices using MLflow, Weights and Biases, and CometML. Participants will learn how to track experiments, manage model versions, compare runs, and operationalise machine learning workflows using industry-grade tooling. By the end of the session, learners will be able to implement reproducible, production-aligned ML experimentation pipelines with structured governance and observability.
02 — Outcomes
What you'll learn
✓
Implement experiment tracking workflows✓
Compare and analyse model runs✓
Apply model versioning and registry practices✓
Design reproducible ML pipelines✓
Evaluate trade-offs between MLOps platforms04 — Prerequisites
Requirements
- Modern machine learning pipeline depends not just on modelling, but on operational discipline. Tools like MLflow, Weights & Biases, and CometML enable structured experimentation, governance, and lifecycle control. These are very critical for production-grade AI systems. Through this course the participants will gain practical exposure to industry-standard experimentation frameworks, reducing the gap between research notebooks and deployable systems. For students and professionals alike, this course builds foundational MLOps competence, a core requirement for scalable, reproducible, and enterprise-ready machine learning workflows.
05 — Audience
Who should take this course
- Anyone with basic understanding of Python syntax and an inquisitiveness to be updated with the latest developments in AI.
$49.00
Member Pricing
FREE with Premium
50% off with General
Duration3h
LevelIntermediate
CertificateYes
$49.00