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CoursTech

Certified training

Master
Data Science & Machine Learning for Non-Engineers

Turn data into decisions

Practical skills for the AI era

Data • AI • Decision-making

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$74.99

Billed in CFA francs: 45 000 FCFA (≈ $74.99).

PAYMENT METHOD

Payment is processed in CFA francs. Payment provider transaction fees are added to the displayed amount, shown before you confirm payment.

See the course in action

$74.99

Payment provider fees (Mobile Money, about 4%) are added at checkout.

By purchasing, you agree to our Terms of Sale.

Billed in CFA francs: 45 000 FCFA (≈ $74.99).

PAYMENT METHOD

Payment is processed in CFA francs. Payment provider transaction fees are added to the displayed amount, shown before you confirm payment.

  • All content hours, with no expiry
  • CodeLab in the browser, nothing to install
  • AI tutor available at any hour
  • AI-graded exercises
  • Final exam and verifiable certificate + an optional field challenge for the Field Practice Validated distinction

Final exam: 2 attempts, 70% pass threshold. After a second failed attempt, a deferral period applies before retrying, with a $10.99 retake fee — see the Terms of Service.

Try lesson 1 for free, no account needed

Lifetime access. No deadline: finish in 6 weeks or in ten months.

Data Science & Machine Learning for Non-Engineers

Understand and apply machine learning to real cases, without becoming a data scientist

Recommended before this course: Data Analytics & Business Intelligence (SQL, Python, Power BI)

Level
Intermediate
Duration
6 weeks
Total hours
30 h(estimated personal workload)
Price
$74.99

The program, module by module

  1. Module 1 — What Machine Learning Actually Is

    Understand what machine learning adds beyond classic analysis: predicting from past examples rather than describing them.

  2. Module 2 — Preparing Data for a Model

    Build meaningful features through feature engineering — ratios, encoding, dates — without causing data leakage.

  3. Module 3 — Classification and Regression Models: The Basics

    Choose between classification and regression based on the kind of answer needed, starting with the simplest model.

  4. Module 4 — Evaluating a Model: Precision, Recall, Limitations

    Evaluate a model using precision and recall rather than accuracy alone, on data never seen during training.

  5. Module 5 — Using Pre-Trained Models

    Use a pre-trained model via an API — text, image — instead of training a custom one, unless a specific need proves it necessary.

  6. Module 6 — Business Use Cases: Churn Prediction, Scoring, Recommendation

    Recognize ML business use cases — churn, scoring, recommendation — as support for human decisions, never blind automation.

  7. Module 7 — Ethics and Algorithmic Bias

    Detect algorithmic bias by comparing model performance across subgroups, not just on the overall average.

  8. Module 8 — When to Call In a Data Scientist

    Recognize the signals that call for a professional data scientist rather than continuing alone.

  9. Module 9 — Professional Integration and Certification

    Certification

    Cross-cutting module: CV/portfolio, professional brand, interview practice, and job market activation — specific to this course's real career outcomes. Triggers generation of the final certificate.

How long will it take me?

Duration: 30 h (estimated personal workload)

3 h/wk ≈ 10 wks

6 h/wk ≈ 5 wks

12 h/wk ≈ 3 wks

20 h/wk ≈ 2 wks

Estimates, not deadlines. Pause for a month and pick up where you left off.

CERTIFICATE VERIFIABLE ONLINE

What you deliver at the end

Cross-cutting module: CV/portfolio, professional brand, interview practice, and job market activation — specific to this course's real career outcomes. Triggers generation of the final certificate.

See a sample certificate

How certification works

Three levels, from simplest to most demanding. Each one only claims what it actually verifies.

Attendance certificate

Earned by: Modules followed

Proves: You followed the track — no graded assessment.

Certificate of achievement

Earned by: Full track completed on the platform, final project included, and final exam passed

Proves: Your knowledge and your final project, evaluated by the platform.

Field Practice Validated distinction

Earned by: A field challenge completed after the exam, in a real situation, with evidence

Proves: A CoursTech mentor reviewed and validated a genuine real-world application.

The distinction is added to your certificate of achievement — it never replaces it: nothing off-platform ever blocks the certificate itself.

Mentor support and validation: handled on request, within 72 business hours. If no mentor is active, the distinction stays open for 12 months as planned: no learner is penalized.

Mentor sessions: limited spots, on request. Reply within 48 h.

See a sample certificate with the distinction →