Data Science & Machine Learning for Non-Engineers

Program

1. 1

   Module 1 — What Machine Learning Actually Is

2. 2

   Module 2 — Preparing Data for a Model

3. 3

   Module 3 — Classification and Regression Models: The Basics

4. 4

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

5. 5

   Module 5 — Using Pre-Trained Models

6. 6

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

7. 7

   Module 7 — Ethics and Algorithmic Bias

8. 8

   Module 8 — When to Call In a Data Scientist

9. 9

   Professional Integration: Machine Learning Practitioner

   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.