Yiga AI

Course 17 of 17

Exploratory Data Analysis

Distributions, Correlations, Segmentation, and more.

Yiga AI

Intermediate en

Intermediate · Course · 3 weeks at 5 hrs/week

Duration
3 weeks
Effort
5 hrs/week
Lessons
16
Hands-on exercises
16
Projects
1
Language
en

What you’ll learn

Skills you can put to work.

Introduction to Python

Intermediate Python

Data Manipulation with pandas

Data Cleaning in Python

Syllabus

Every module, step by step.

4 modules · 21 lessons · 14 hours · 1 graded project

840 minutes of guided lesson time.

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

Module 1 · 5 lessons · 3 hoursDistributionsModule 1 of 4 in Exploratory Data Analysis.

  1. Overview and set-up

    Overview and set-up — Distributions in Exploratory Data Analysis.

    Lesson

    40 min

  2. Core concepts

    Core concepts — Distributions in Exploratory Data Analysis.

    Lesson · Locked

    40 min

  3. Worked example

    Worked example — Distributions in Exploratory Data Analysis.

    Lesson · Locked

    40 min

  4. Hands-on practice

    Hands-on practice — Distributions in Exploratory Data Analysis.

    Lesson · Locked

    40 min

  5. Module quiz: Distributions

    Check what you learned in Distributions before moving on.

    Quiz · Locked

    20 min
Module 2 · 5 lessons · 3 hours LockedCorrelationsModule 2 of 4 in Exploratory Data Analysis.

  1. Overview and set-up

    Overview and set-up — Correlations in Exploratory Data Analysis.

    Lesson · Locked

    40 min

  2. Core concepts

    Core concepts — Correlations in Exploratory Data Analysis.

    Lesson · Locked

    40 min

  3. Worked example

    Worked example — Correlations in Exploratory Data Analysis.

    Lesson · Locked

    40 min

  4. Hands-on practice

    Hands-on practice — Correlations in Exploratory Data Analysis.

    Lesson · Locked

    40 min

  5. Module quiz: Correlations

    Check what you learned in Correlations before moving on.

    Quiz · Locked

    20 min
Module 3 · 5 lessons · 3 hours LockedSegmentationModule 3 of 4 in Exploratory Data Analysis.

  1. Overview and set-up

    Overview and set-up — Segmentation in Exploratory Data Analysis.

    Lesson · Locked

    40 min

  2. Core concepts

    Core concepts — Segmentation in Exploratory Data Analysis.

    Lesson · Locked

    40 min

  3. Worked example

    Worked example — Segmentation in Exploratory Data Analysis.

    Lesson · Locked

    40 min

  4. Hands-on practice

    Hands-on practice — Segmentation in Exploratory Data Analysis.

    Lesson · Locked

    40 min

  5. Module quiz: Segmentation

    Check what you learned in Segmentation before moving on.

    Quiz · Locked

    20 min
Module 4 · 6 lessons · 5 hours LockedEDA reportModule 4 of 4 in Exploratory Data Analysis.

  1. Overview and set-up

    Overview and set-up — EDA report in Exploratory Data Analysis.

    Lesson · Locked

    40 min

  2. Core concepts

    Core concepts — EDA report in Exploratory Data Analysis.

    Lesson · Locked

    40 min

  3. Worked example

    Worked example — EDA report in Exploratory Data Analysis.

    Lesson · Locked

    40 min

  4. Hands-on practice

    Hands-on practice — EDA report in Exploratory Data Analysis.

    Lesson · Locked

    40 min

  5. Module quiz: EDA report

    Check what you learned in EDA report before moving on.

    Quiz · Locked

    20 min

  6. Graded project: Exploratory Data Analysis

    Apply everything from Exploratory Data Analysis in one graded, portfolio-ready build.

    Graded project · Locked

    120 min

Applied learning project

Make the learning visible.

Use Graded project: Exploratory Data Analysis 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
Daniel O., Data & analytics

Your instructor

Daniel O.

Data & analytics

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

Brian Okello, Yiga learner

“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 Data Analyst with Python.

See the full chain

Next lesson

Overview and set-up

Exploratory Data Analysis

40 min · Resume

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