Mathematics For Computer Science

Computer Science · Level 6  ·  5 Chapters

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What Mathematics For Computer Science covers

Mathematics For Computer Science (Level 6) supplies the mathematics a computing course keeps returning to. Linear algebra covers linear equations, vectors, matrices and the inverse of a square matrix. Boolean algebra moves from basic and secondary operations to writing expressions and simplifying them with laws, theorems and reduction rules. Set theory deals with representing sets, cardinality, types of sets, Venn diagrams and set operations. Calculus takes functions and their graphs through differential calculus, first and second order differential equations, integral calculus and techniques of integration. Probability and statistics end the unit with probability axioms, permutations and combinations, conditional probability, data representation, and measures of central tendency, spread and location.

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Careers after Mathematics For Computer Science

Mathematics for Computer Science isn’t just theory - it’s the toolkit that powers the digital world you’ll help build across Kenya. Mastering linear equations, vectors, matrices, Boolean logic and set theory opens doors to many practical jobs and entrepreneurial ventures, from coding smart apps to designing the networks that keep us connected.

  • Software development firms in Nairobi’s tech hubs - you use linear equations and matrix operations to create algorithms for graphics, machine learning and optimisation, earning a salary as a junior developer or freelance coder on project contracts.
  • Telecommunications network planning offices in Kisumu or Mombasa - you apply vectors and matrix transformations to model signal propagation and antenna placement, earning wages as a network engineer or consultant on infrastructure projects.
  • GIS and remote-sensing units in county land bureaus - you employ vector maths and matrix inverses to convert satellite coordinates into accurate maps, earning as a GIS analyst or by offering paid mapping services to NGOs and private firms.
  • Digital circuit design workshops in Kiambu - you use Boolean algebra, secondary operations and simplification rules to design efficient logic gates and microcontroller firmware, earning as a hardware technician or by selling custom PCB designs to startups.
  • Fintech startups in Nairobi’s Central Business District - you apply set-theory concepts and Venn diagrams to model customer segmentation, fraud detection and risk categories, earning as a data analyst or by providing paid consultancy on data-driven product features.
  • Agricultural-technology companies in Eldoret and Nakuru - you solve linear equations and matrix problems to optimise irrigation schedules, fertilizer mixes and yield forecasts, earning as an agritech analyst or by running your own advisory service for smallholder farms.
  • University research labs and innovation hubs in Nakuru - you use Boolean simplification and set operations to develop algorithms for bio-informatics, image processing or AI research, earning stipends as a research assistant or through grant-funded project contracts.
  • ICT training centres in Thika and Kisii - you teach these mathematical tools to adult learners and secondary-school students, earning fees as an instructor or by creating and selling online courses.
  • Freelance app development for small businesses in coastal tourism towns - you apply linear algebra to build inventory-management, booking and payment systems, earning project-based income and building a portfolio of local clients.
  • Electronics repair shops in Nairobi’s Eastlands - you apply Boolean logic to troubleshoot digital devices and program microcontrollers, earning per-repair fees and the reputation that can grow into a small repair-service business.

Keep sharpening these skills - you’ll find countless ways to turn numbers into solutions that power Kenya’s future.

Chapters

4 past papers for this unit →

What Mathematics For Computer Science covers: 35 main topics in 5 chapters

1. Linear Algebra

  1. 1.1 Linear Equations
  2. 1.2 Solving linear equations
  3. 1.3 Vectors
  4. 1.4 Vector operations
  5. 1.5 Matrices
  6. 1.6 Matrix operations
  7. 1.7 Inverse of square matrix

2. Boolean Algebra

  1. 2.1 Boolean algebra
  2. 2.2 Boolean operations
  3. 2.3 Basic Boolean operations
  4. 2.4 Secondary operations
  5. 2.5 Writing Boolean Expressions
  6. 2.6 Simplification of Boolean expressions
  7. 2.7 Boolean Laws and Theorems
  8. 2.8 Simplification (Reduction) Rules for Boolean expressions

3. Set Theory

  1. 3.1 Sets Theory
  2. 3.2 Methods of Set representation
  3. 3.3 Cardinality of a set
  4. 3.4 Types of sets
  5. 3.5 Venn Diagrams
  6. 3.6 Set Operations

4. Calculus

  1. 4.1 Functions
  2. 4.2 Graphing of functions
  3. 4.3 Differential calculus
  4. 4.4 First and second order differential equations
  5. 4.5 Integral calculus
  6. 4.6 Techniques of integration

5. Probability and Statistics

  1. 5.1 Key terminologies in probability
  2. 5.2 Probability axioms and counting problems
  3. 5.3 Permutations and combinations
  4. 5.4 Conditional probability and multiplication rule
  5. 5.5 Data representation techniques
  6. 5.6 Measures of central tendency
  7. 5.7 Measures of spread
  8. 5.8 Measure of Location

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Beyond the syllabus

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