Course 1 of 12

MLOps Fundamentals

Experiment tracking (MLflow), Pipelines, Versioning, and more.

Yiga AI

Intermediate en

Intermediate · Course · 4 weeks at 5 hrs/week

Duration: 4 weeks
Effort: 5 hrs/week
Lessons: 20
Hands-on exercises: 20
Projects: 1
Language: en

What you’ll learn

Skills you can put to work.

Machine Learning Foundations

Deep Learning with PyTorch

Computer Vision

NLP with Transformers

Syllabus

Every module, step by step.

4 modules · 25 lessons · 17 hours · 1 graded project

1000 minutes of guided lesson time.

Module 1 · 6 lessons · 3.7 hoursExperiment tracking (MLflow)Module 1 of 4 in MLOps Fundamentals.

Overview and set-up
Overview and set-up — Experiment tracking (MLflow) in MLOps Fundamentals.
Lesson
40 min
Core concepts
Core concepts — Experiment tracking (MLflow) in MLOps Fundamentals.
Lesson · Locked
40 min
Worked example
Worked example — Experiment tracking (MLflow) in MLOps Fundamentals.
Lesson · Locked
40 min
Hands-on practice
Hands-on practice — Experiment tracking (MLflow) in MLOps Fundamentals.
Lesson · Locked
40 min
Common pitfalls
Common pitfalls — Experiment tracking (MLflow) in MLOps Fundamentals.
Lesson · Locked
40 min
Module quiz: Experiment tracking (MLflow)
Check what you learned in Experiment tracking (MLflow) before moving on.
Quiz · Locked
20 min

Module 2 · 6 lessons · 3.7 hours LockedPipelinesModule 2 of 4 in MLOps Fundamentals.

Overview and set-up
Overview and set-up — Pipelines in MLOps Fundamentals.
Lesson · Locked
40 min
Core concepts
Core concepts — Pipelines in MLOps Fundamentals.
Lesson · Locked
40 min
Worked example
Worked example — Pipelines in MLOps Fundamentals.
Lesson · Locked
40 min
Hands-on practice
Hands-on practice — Pipelines in MLOps Fundamentals.
Lesson · Locked
40 min
Common pitfalls
Common pitfalls — Pipelines in MLOps Fundamentals.
Lesson · Locked
40 min
Module quiz: Pipelines
Check what you learned in Pipelines before moving on.
Quiz · Locked
20 min

Module 3 · 6 lessons · 3.7 hours LockedVersioningModule 3 of 4 in MLOps Fundamentals.

Overview and set-up
Overview and set-up — Versioning in MLOps Fundamentals.
Lesson · Locked
40 min
Core concepts
Core concepts — Versioning in MLOps Fundamentals.
Lesson · Locked
40 min
Worked example
Worked example — Versioning in MLOps Fundamentals.
Lesson · Locked
40 min
Hands-on practice
Hands-on practice — Versioning in MLOps Fundamentals.
Lesson · Locked
40 min
Common pitfalls
Common pitfalls — Versioning in MLOps Fundamentals.
Lesson · Locked
40 min
Module quiz: Versioning
Check what you learned in Versioning before moving on.
Quiz · Locked
20 min

Module 4 · 7 lessons · 5.7 hours LockedCI/CD for MLModule 4 of 4 in MLOps Fundamentals.

Overview and set-up
Overview and set-up — CI/CD for ML in MLOps Fundamentals.
Lesson · Locked
40 min
Core concepts
Core concepts — CI/CD for ML in MLOps Fundamentals.
Lesson · Locked
40 min
Worked example
Worked example — CI/CD for ML in MLOps Fundamentals.
Lesson · Locked
40 min
Hands-on practice
Hands-on practice — CI/CD for ML in MLOps Fundamentals.
Lesson · Locked
40 min
Common pitfalls
Common pitfalls — CI/CD for ML in MLOps Fundamentals.
Lesson · Locked
40 min
Module quiz: CI/CD for ML
Check what you learned in CI/CD for ML before moving on.
Quiz · Locked
20 min
Graded project: MLOps Fundamentals
Apply everything from MLOps Fundamentals in one graded, portfolio-ready build.
Graded project · Locked
120 min

Applied learning project

Make the learning visible.

Use Graded project: MLOps Fundamentals to apply this course to a practical challenge. You’ll finish with a clear solution and the reasoning behind your choices.

Apply the course’s core skillMake and explain practical decisionsCreate evidence you can share

Your instructor

Daniel O.

Data & analytics

Turns real African data problems into practical lessons learners can apply immediately.

“The course content made machine learning understandable, and the practice kept me moving.”
Brian Okello
Software developer, Kampala

Continue with

Your next best step.

Following the order of Machine Learning Engineer.

See the full chain

Next lesson

Overview and set-up

MLOps Fundamentals

40 min · Resume

Course 2 in the track

NLP with Transformers

Attention, BERT, Fine-tuning, and more.

Intermediate · Course · 4 weeks at 5 hrs/week

Course 3 in the track

Project: Fraud Detection System End-to-End

Data, Model, Deployment, and more.

Advanced · Course · 4 weeks at 5 hrs/week

Course 4 in the track

Reinforcement Learning Intro

Agents & environments, Q-learning, Policy gradients, and more.

Advanced · Course · 3 weeks at 5 hrs/week

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