📚 Content

This practical module develops core quantitative skills needed in AI and programming. Learners will engage in applied activities across the following areas:

1. Basic Mathematics & Computational Thinking

  • Apply order of operations (PEMDAS/BOMDAS)

  • Perform integer division and modulus operations

  • Work with mixed data types and casting in programming

2. Linear Algebra for AI

  • Work with vectors and matrices

  • Perform matrix operations and transformations

  • Apply functions used in AI such as ReLU, Sigmoid, and Softmax

3. Binary & Number Systems

  • Convert decimal numbers to binary

  • Perform binary arithmetic operations

4. Magnitude & Conversions

  • Use scientific notation for large and small values

  • Convert between measurement systems (e.g., SI to Imperial)

5. Error Handling in Calculations

  • Fix rounding errors

  • Convert repeating decimals

  • Ensure correct unit representation in results

6. Coordinate Systems & Geometry

  • Use Cartesian coordinates

  • Apply the Pythagorean theorem to calculate distances

7. Programming Logic with Increments

  • Use increment variables and compound operators

  • Implement iterative logic in code

8. Calculus for AI

  • Apply differentiation and integration

  • Use derivatives, chain rule, and special functions

9. Probability & Statistics

  • Apply probability rules and notation

  • Use conditional probability and Bayes’ Theorem

  • Perform statistical calculations and parameter estimation

🎯 Outcome

By completing this module, learners will be able to apply mathematical and statistical reasoning to support AI model development, data analysis, and algorithm design in real-world scenarios.

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