Course 6 of 11

Data Engineering Foundations

Roles, Architectures, Batch vs streaming, and more.

Yiga AI

Beginner en

Beginner · 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.

Data Engineering Foundations

Advanced SQL for Engineers

Python for Data Engineering

Data Warehousing

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 hoursRolesModule 1 of 4 in Data Engineering Foundations.
  1. Overview and set-up

    Overview and set-up — Roles in Data Engineering Foundations.

    Lesson

    40 min
  2. Core concepts

    Core concepts — Roles in Data Engineering Foundations.

    Lesson · Locked

    40 min
  3. Worked example

    Worked example — Roles in Data Engineering Foundations.

    Lesson · Locked

    40 min
  4. Hands-on practice

    Hands-on practice — Roles in Data Engineering Foundations.

    Lesson · Locked

    40 min
  5. Module quiz: Roles

    Check what you learned in Roles before moving on.

    Quiz · Locked

    20 min
Module 2 · 5 lessons · 3 hours LockedArchitecturesModule 2 of 4 in Data Engineering Foundations.
  1. Overview and set-up

    Overview and set-up — Architectures in Data Engineering Foundations.

    Lesson · Locked

    40 min
  2. Core concepts

    Core concepts — Architectures in Data Engineering Foundations.

    Lesson · Locked

    40 min
  3. Worked example

    Worked example — Architectures in Data Engineering Foundations.

    Lesson · Locked

    40 min
  4. Hands-on practice

    Hands-on practice — Architectures in Data Engineering Foundations.

    Lesson · Locked

    40 min
  5. Module quiz: Architectures

    Check what you learned in Architectures before moving on.

    Quiz · Locked

    20 min
Module 3 · 5 lessons · 3 hours LockedBatch vs streamingModule 3 of 4 in Data Engineering Foundations.
  1. Overview and set-up

    Overview and set-up — Batch vs streaming in Data Engineering Foundations.

    Lesson · Locked

    40 min
  2. Core concepts

    Core concepts — Batch vs streaming in Data Engineering Foundations.

    Lesson · Locked

    40 min
  3. Worked example

    Worked example — Batch vs streaming in Data Engineering Foundations.

    Lesson · Locked

    40 min
  4. Hands-on practice

    Hands-on practice — Batch vs streaming in Data Engineering Foundations.

    Lesson · Locked

    40 min
  5. Module quiz: Batch vs streaming

    Check what you learned in Batch vs streaming before moving on.

    Quiz · Locked

    20 min
Module 4 · 6 lessons · 5 hours LockedTooling mapModule 4 of 4 in Data Engineering Foundations.
  1. Overview and set-up

    Overview and set-up — Tooling map in Data Engineering Foundations.

    Lesson · Locked

    40 min
  2. Core concepts

    Core concepts — Tooling map in Data Engineering Foundations.

    Lesson · Locked

    40 min
  3. Worked example

    Worked example — Tooling map in Data Engineering Foundations.

    Lesson · Locked

    40 min
  4. Hands-on practice

    Hands-on practice — Tooling map in Data Engineering Foundations.

    Lesson · Locked

    40 min
  5. Module quiz: Tooling map

    Check what you learned in Tooling map before moving on.

    Quiz · Locked

    20 min
  6. Graded project: Data Engineering Foundations

    Apply everything from Data Engineering Foundations in one graded, portfolio-ready build.

    Graded project · Locked

    120 min

Applied learning project

Make the learning visible.

Use Graded project: Data Engineering Foundations 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

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