Video course · 15 chapters · 181 min · certificate
MLOps Course – Build Machine Learning Production Grade Projects
Build production-grade ML with MLOps and ZenML: MLOps fundamentals, ZenML basics, a customer-satisfaction project on the Olist dataset, pipeline steps for ingestion, cleaning, training and evaluation, the dashboard, MLflow experiment tracking, a deployment pipeline and a Streamlit app.
What you'll learn
- Explain MLOps principles
- Use ZenML steps and pipelines
- Ingest, clean and train in a pipeline
- Track experiments
- Build a deployment pipeline
- Serve predictions in Streamlit
Chapters
15 chapters · 181:02-
1:28
01Intro Members
Intro
DevOps for ML.
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31:26
02Fundamentals Members
MLOps fundamentals
Terminology.
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12:37
03ZenML Members
ZenML fundamentals
Steps and pipelines.
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3:30
04Project Members
Customer satisfaction project
Olist dataset.
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6:00
05Setup Members
Installing libraries
Fix errors.
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13:05
06Blueprint Members
Blueprint of steps
ingest_data.py.
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5:40
07Dashboard Members
ZenML dashboard
Visual runs.
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1:15
08Steps Members
Implementing steps
Clean, ingest, evaluate.
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18:40
09Cleaning Members
Data cleaning
Strategy pattern.
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7:28
10Model Members
Model development
Training.
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7:27
11Evaluation Members
Evaluation
Metrics.
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5:52
12Run Members
Running the pipeline
Caching.
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16:34
13Tracking Members
Experiment tracker
MLflow.
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47:06
14Deploy Members
Deployment pipeline
Continuous deployment.
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2:54
15App Members
Streamlit app
Serve predictions.
Jobs this course suits
Our AI checked this course against 500 jobs; these get the most out of it. Each job links to its learning path.