Course 1 of 16

Introduction to Deep Learning

Neural networks, Keras, Training, 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.

Python for Data Science Refresher

Statistical Thinking

Supervised Learning with scikit-learn

Unsupervised Learning

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 hoursNeural networksModule 1 of 4 in Introduction to Deep Learning.

Overview and set-up
Overview and set-up — Neural networks in Introduction to Deep Learning.
Lesson
40 min
Core concepts
Core concepts — Neural networks in Introduction to Deep Learning.
Lesson · Locked
40 min
Worked example
Worked example — Neural networks in Introduction to Deep Learning.
Lesson · Locked
40 min
Hands-on practice
Hands-on practice — Neural networks in Introduction to Deep Learning.
Lesson · Locked
40 min
Common pitfalls
Common pitfalls — Neural networks in Introduction to Deep Learning.
Lesson · Locked
40 min
Module quiz: Neural networks
Check what you learned in Neural networks before moving on.
Quiz · Locked
20 min

Module 2 · 6 lessons · 3.7 hours LockedKerasModule 2 of 4 in Introduction to Deep Learning.

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

Module 3 · 6 lessons · 3.7 hours LockedTrainingModule 3 of 4 in Introduction to Deep Learning.

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

Module 4 · 7 lessons · 5.7 hours LockedRegularisationModule 4 of 4 in Introduction to Deep Learning.

Overview and set-up
Overview and set-up — Regularisation in Introduction to Deep Learning.
Lesson · Locked
40 min
Core concepts
Core concepts — Regularisation in Introduction to Deep Learning.
Lesson · Locked
40 min
Worked example
Worked example — Regularisation in Introduction to Deep Learning.
Lesson · Locked
40 min
Hands-on practice
Hands-on practice — Regularisation in Introduction to Deep Learning.
Lesson · Locked
40 min
Common pitfalls
Common pitfalls — Regularisation in Introduction to Deep Learning.
Lesson · Locked
40 min
Module quiz: Regularisation
Check what you learned in Regularisation before moving on.
Quiz · Locked
20 min
Graded project: Introduction to Deep Learning
Apply everything from Introduction to Deep Learning in one graded, portfolio-ready build.
Graded project · Locked
120 min

Applied learning project

Make the learning visible.

Use Graded project: Introduction to Deep Learning 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

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Your next best step.

Following the order of Data Scientist with Python.

See the full chain

Next lesson

Overview and set-up

Introduction to Deep Learning

40 min · Resume

Course 2 in the track

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Data collection, CNN, Evaluation, and more.

Advanced · Course · 4 weeks at 5 hrs/week

Course 3 in the track

Statistical Thinking

Distributions, Sampling, Bootstrapping, and more.

Intermediate · Course · 3 weeks at 5 hrs/week

Course 4 in the track

Data Scientist Interview Prep

Case studies, Coding rounds, Stats questions, and more.

Intermediate · Course · 3 weeks at 5 hrs/week

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