ALSS

Essential Mathematics for Computer Science

Course Overview

This course provides a comprehensive introduction to the foundational mathematical principles essential for first-year computer science students. Topics include:

  • Logic and Discrete Mathematics
  • Precalculus
  • Linear Algebra

Course Content

  • Foundations of Propositional Logic and Set Theory
  • Combinatorics
  • Introduction to Graph Theory
  • Numbers, Functions, and Precalculus Foundations
  • Linear Algebra Essentials

Course Details:

  •  Duration: 8 Weeks
  • 2 Classes Per Week | 90 Minutes + 15-Minute Break 
  • Starting Date: 02/Feb/2025
  • Tutorial fees for the whole course:
    CHF 699.90 to be paid two weeks before starting the course
  • Study Options 100% online per Zoom
  • Language:  English
  • Internet access and an email address are required

Part I: Foundations of Propositional Logic and Set Theory

Class 1: Propositional Logic
Learn logical operations, truth tables, and their application in logical statements.
Class 2: Proof Techniques
Explore direct proof, proof by contradiction, and basic induction.
Class 3: Set Theory Basics
Introduction to set operations and properties through examples.

Part II: Combinatorics

Class 4: Introduction to Combinatorics
Master fundamental counting principles and strategies.
Class 5: Counting Exercises
Engage in practical problem-solving applications.

Part III: Introduction to Graph Theory

Class 6: Basic Notations on Graphs
Understand graph types, vertices, edges, and examples.
Class 7: Introduction to Trees
Learn tree structures and their applications.
Class 8: Review Session
Comprehensive review of Propositional Logic, Set Theory, Combinatorics, and Graph Theory.

Part IV: Numbers, Functions, and Precalculus Foundations

Class 9: Numbers
Dive into types of numbers and their properties.
Class 10: Functions
Explore polynomial, rational, exponential, and logarithmic functions.
Class 11: Trigonometry
Understand the unit circle and basic trigonometric functions.
Class 12: Continuity and Limits
Grasp continuity concepts and intuitive limits.
Class 13: Sequences and Series
Learn about arithmetic and geometric sequences.

Part V: Linear Algebra Essentials

Class 14: Vectors and Matrices
Master vector and matrix operations.
Class 15: Linear Transformations
Understand linear transformations in 2D.
Class 16: Review Session
Recap Precalculus and Linear Algebra concepts.

Department Contact

Social Info

Accreditation & Certification

Why Choose This Course?

✔ Tailored for computer science beginners.
✔ Practical problem-solving focus.
✔ Step-by-step guided learning.
✔ Learn at Your Own Pace: Flexible, 100% online learning, accessible anytime, anywhere.

Ready to Build Your Math Foundation?

💻 Sign Up Now and start your journey into essential mathematics for computer science!

Lecturer: Chiara Fuda, Ph.D.

A PhD researcher in Informatics at the Università della Svizzera italiana (USI) in Lugano, Switzerland, specializing in numerical analysis, computational geometry, and scientific computing. Research focuses on developing advanced algorithms to enhance numerical stability and robustness, particularly in function approximation and computer graphics.

Significant contributions include designing innovative mathematical software (the C++ BRI class) for stable and robust evaluation of barycentric interpolants. Teaching experience includes assisting in courses such as Numerical Algorithms, Calculus, and Discrete Structures, blending theoretical expertise with practical instruction.

Holds a Master’s degree in Mathematics from the Università della Calabria, graduating with honors, and completed a research traineeship in approximation theory in Spain. Published in leading journals and honored with a Best Paper Award at the GMP 2024 conference in China for the work “A new stable method to compute mean value coordinates.”

Graduate Benefits

Completing a mathematics course offers key benefits, including enhanced critical thinking, problem-solving, and analytical skills. It strengthens logical reasoning, which is valuable across fields like science, engineering, finance, and technology. For students, it prepares for advanced studies, while for professionals, it sharpens quantitative and data interpretation skills essential in modern workplaces.

 

Professional Development

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Alumni

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