Yiga AI

Course 14 of 16

Time Series Analysis

Trends & seasonality, ARIMA, Prophet, 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.

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

Module 1 · 6 lessons · 3.7 hoursTrends & seasonalityModule 1 of 4 in Time Series Analysis.

  1. Overview and set-up

    Overview and set-up — Trends & seasonality in Time Series Analysis.

    Lesson

    40 min

  2. Core concepts

    Core concepts — Trends & seasonality in Time Series Analysis.

    Lesson · Locked

    40 min

  3. Worked example

    Worked example — Trends & seasonality in Time Series Analysis.

    Lesson · Locked

    40 min

  4. Hands-on practice

    Hands-on practice — Trends & seasonality in Time Series Analysis.

    Lesson · Locked

    40 min

  5. Common pitfalls

    Common pitfalls — Trends & seasonality in Time Series Analysis.

    Lesson · Locked

    40 min

  6. Module quiz: Trends & seasonality

    Check what you learned in Trends & seasonality before moving on.

    Quiz · Locked

    20 min
Module 2 · 6 lessons · 3.7 hours LockedARIMAModule 2 of 4 in Time Series Analysis.

  1. Overview and set-up

    Overview and set-up — ARIMA in Time Series Analysis.

    Lesson · Locked

    40 min

  2. Core concepts

    Core concepts — ARIMA in Time Series Analysis.

    Lesson · Locked

    40 min

  3. Worked example

    Worked example — ARIMA in Time Series Analysis.

    Lesson · Locked

    40 min

  4. Hands-on practice

    Hands-on practice — ARIMA in Time Series Analysis.

    Lesson · Locked

    40 min

  5. Common pitfalls

    Common pitfalls — ARIMA in Time Series Analysis.

    Lesson · Locked

    40 min

  6. Module quiz: ARIMA

    Check what you learned in ARIMA before moving on.

    Quiz · Locked

    20 min
Module 3 · 6 lessons · 3.7 hours LockedProphetModule 3 of 4 in Time Series Analysis.

  1. Overview and set-up

    Overview and set-up — Prophet in Time Series Analysis.

    Lesson · Locked

    40 min

  2. Core concepts

    Core concepts — Prophet in Time Series Analysis.

    Lesson · Locked

    40 min

  3. Worked example

    Worked example — Prophet in Time Series Analysis.

    Lesson · Locked

    40 min

  4. Hands-on practice

    Hands-on practice — Prophet in Time Series Analysis.

    Lesson · Locked

    40 min

  5. Common pitfalls

    Common pitfalls — Prophet in Time Series Analysis.

    Lesson · Locked

    40 min

  6. Module quiz: Prophet

    Check what you learned in Prophet before moving on.

    Quiz · Locked

    20 min
Module 4 · 7 lessons · 5.7 hours LockedForecast evaluationModule 4 of 4 in Time Series Analysis.

  1. Overview and set-up

    Overview and set-up — Forecast evaluation in Time Series Analysis.

    Lesson · Locked

    40 min

  2. Core concepts

    Core concepts — Forecast evaluation in Time Series Analysis.

    Lesson · Locked

    40 min

  3. Worked example

    Worked example — Forecast evaluation in Time Series Analysis.

    Lesson · Locked

    40 min

  4. Hands-on practice

    Hands-on practice — Forecast evaluation in Time Series Analysis.

    Lesson · Locked

    40 min

  5. Common pitfalls

    Common pitfalls — Forecast evaluation in Time Series Analysis.

    Lesson · Locked

    40 min

  6. Module quiz: Forecast evaluation

    Check what you learned in Forecast evaluation before moving on.

    Quiz · Locked

    20 min

  7. Graded project: Time Series Analysis

    Apply everything from Time Series Analysis in one graded, portfolio-ready build.

    Graded project · Locked

    120 min

Applied learning project

Make the learning visible.

Use Graded project: Time Series 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
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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Your next best step.

Following the order of Data Scientist with Python.

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Time Series Analysis

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