02 · Curriculum
What's in the course.
- Understanding MLOps - Intuition47m
- MLFlow and Weights & Biases - Hands-on Tutorial19m
- Data Versioning through Git and GitFlow - Intuition20m
Intermediate
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, and operationalis…
- 2+
- enrolled
- 3 hrs
- of instruction
- 11
- lectures
- 4
- modules
Taught by Sachin Tripathi01 · What you'll be able to do
Five things you can ship afterwards.
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.
Implement experiment tracking workflows
Implement experiment tracking workflows.
Compare and analyse model
Compare and analyse model runs.
Apply model versioning
Apply model versioning and registry practices.
Design reproducible ML pipelines
Design reproducible ML pipelines.
Evaluate trade-offs between MLOps
Evaluate trade-offs between MLOps platforms.
03 · Instructors
Taught by the people who built it.
Sachin Tripathi
All courses by Sachin04 · Is it for you?
Who it's for, and what to bring.
Built for
- Anyone with basic understanding of Python syntax and an inquisitiveness to be updated with the latest developments in AI.
Bring with you
- 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 · FAQ
Before you enrol.
Each of the 4 modules is a recorded live session, with slide deck and handouts, readings from that session. Watch at your own pace.
$49.00
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Ready to start?
$49, or free with Premium membership.