Yiga AI

Course 2 of 16

Project: Crop Disease Detection from Images

Data collection, CNN, Evaluation, and more.

Yiga AI

Advanced en

Advanced · Course · 4 weeks at 5 hrs/week

Duration
4 weeks
Effort
5 hrs/week
Lessons
24
Hands-on exercises
24
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 · 29 lessons · 19 hours · 1 graded project

1160 minutes of guided lesson time.

Sign in and enrol to unlock every lesson. The first lesson is open as a preview.

Module 1 · 7 lessons · 4.3 hoursData collectionModule 1 of 4 in Project: Crop Disease Detection from Images.

  1. Overview and set-up

    Overview and set-up — Data collection in Project: Crop Disease Detection from Images.

    Lesson

    40 min

  2. Core concepts

    Core concepts — Data collection in Project: Crop Disease Detection from Images.

    Lesson · Locked

    40 min

  3. Worked example

    Worked example — Data collection in Project: Crop Disease Detection from Images.

    Lesson · Locked

    40 min

  4. Hands-on practice

    Hands-on practice — Data collection in Project: Crop Disease Detection from Images.

    Lesson · Locked

    40 min

  5. Common pitfalls

    Common pitfalls — Data collection in Project: Crop Disease Detection from Images.

    Lesson · Locked

    40 min

  6. Applying it at work

    Applying it at work — Data collection in Project: Crop Disease Detection from Images.

    Lesson · Locked

    40 min

  7. Module quiz: Data collection

    Check what you learned in Data collection before moving on.

    Quiz · Locked

    20 min
Module 2 · 7 lessons · 4.3 hours LockedCNNModule 2 of 4 in Project: Crop Disease Detection from Images.

  1. Overview and set-up

    Overview and set-up — CNN in Project: Crop Disease Detection from Images.

    Lesson · Locked

    40 min

  2. Core concepts

    Core concepts — CNN in Project: Crop Disease Detection from Images.

    Lesson · Locked

    40 min

  3. Worked example

    Worked example — CNN in Project: Crop Disease Detection from Images.

    Lesson · Locked

    40 min

  4. Hands-on practice

    Hands-on practice — CNN in Project: Crop Disease Detection from Images.

    Lesson · Locked

    40 min

  5. Common pitfalls

    Common pitfalls — CNN in Project: Crop Disease Detection from Images.

    Lesson · Locked

    40 min

  6. Applying it at work

    Applying it at work — CNN in Project: Crop Disease Detection from Images.

    Lesson · Locked

    40 min

  7. Module quiz: CNN

    Check what you learned in CNN before moving on.

    Quiz · Locked

    20 min
Module 3 · 7 lessons · 4.3 hours LockedEvaluationModule 3 of 4 in Project: Crop Disease Detection from Images.

  1. Overview and set-up

    Overview and set-up — Evaluation in Project: Crop Disease Detection from Images.

    Lesson · Locked

    40 min

  2. Core concepts

    Core concepts — Evaluation in Project: Crop Disease Detection from Images.

    Lesson · Locked

    40 min

  3. Worked example

    Worked example — Evaluation in Project: Crop Disease Detection from Images.

    Lesson · Locked

    40 min

  4. Hands-on practice

    Hands-on practice — Evaluation in Project: Crop Disease Detection from Images.

    Lesson · Locked

    40 min

  5. Common pitfalls

    Common pitfalls — Evaluation in Project: Crop Disease Detection from Images.

    Lesson · Locked

    40 min

  6. Applying it at work

    Applying it at work — Evaluation in Project: Crop Disease Detection from Images.

    Lesson · Locked

    40 min

  7. Module quiz: Evaluation

    Check what you learned in Evaluation before moving on.

    Quiz · Locked

    20 min
Module 4 · 8 lessons · 6.3 hours LockedMobile demoModule 4 of 4 in Project: Crop Disease Detection from Images.

  1. Overview and set-up

    Overview and set-up — Mobile demo in Project: Crop Disease Detection from Images.

    Lesson · Locked

    40 min

  2. Core concepts

    Core concepts — Mobile demo in Project: Crop Disease Detection from Images.

    Lesson · Locked

    40 min

  3. Worked example

    Worked example — Mobile demo in Project: Crop Disease Detection from Images.

    Lesson · Locked

    40 min

  4. Hands-on practice

    Hands-on practice — Mobile demo in Project: Crop Disease Detection from Images.

    Lesson · Locked

    40 min

  5. Common pitfalls

    Common pitfalls — Mobile demo in Project: Crop Disease Detection from Images.

    Lesson · Locked

    40 min

  6. Applying it at work

    Applying it at work — Mobile demo in Project: Crop Disease Detection from Images.

    Lesson · Locked

    40 min

  7. Module quiz: Mobile demo

    Check what you learned in Mobile demo before moving on.

    Quiz · Locked

    20 min

  8. Graded project: Project: Crop Disease Detection from Images

    Apply everything from Project: Crop Disease Detection from Images in one graded, portfolio-ready build.

    Graded project · Locked

    120 min

Applied learning project

Make the learning visible.

Use Graded project: Project: Crop Disease Detection from Images 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
Mariam K., Software & cloud

Your instructor

Mariam K.

Software & cloud

Helps new developers build reliable products through clear explanations and guided practice.

Diana Nsiiza, Yiga learner

“I use what I learned in my work now, not in some distant future project.”

Diana Nsiiza

Data analyst, Entebbe

Continue with

Your next best step.

Following the order of Data Scientist with Python.

See the full chain

Next lesson

Overview and set-up

Project: Crop Disease Detection from Images

40 min · Resume

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

Course 5 in the track

Unsupervised Learning

K-means, Hierarchical, PCA, and more.

Intermediate · Course · 3 weeks at 5 hrs/week

Learner reviews

What learners say.

Write a review

Sign in to share your experience with this course.

Sign in to review

Loading reviews…

Previous courseIntroduction to Deep LearningNext courseStatistical Thinking

Keep going

Other courses in this track.

View full track
Statistical Thinking cover illustration
Data

16 lessons · 14h · Intermediate

Statistical Thinking

Distributions, Sampling, Bootstrapping, and more.

Yiga Plus