Set Theory - Mathematics (Undergraduate Foundation)

Master the bedrock of modern mathematics. This course provides a rigorous introduction to set theory, the fundamental language used to structure nearly every mathematical discipline. We move quickly from defining basic sets and elements to complex operations including unions, intersections, and complements. You will analyze relationships between collections using Venn diagrams, master set-builder notation, and examine the properties of power sets and Cartesian products, establishing the ground rules for all subsequent mathematical study. Mathematical rigour is essential for advanced problem-solving. Set theory is not abstract trivia; it is the critical organizational framework underpinning computer science database structures, logical reasoning systems in artificial intelligence, and complex data stratification in statistical analysis. Fluency in set operations allows you to define precise categories, manage data relationships efficiently, and construct watertight logical arguments required in professional technical environments. Upon completion, you will possess the skills to define sets accurately using various notations and execute operations on finite and infinite collections with precision. You will demonstrate competence in proving fundamental set identities, manipulating Venn diagrams to solve practical problems, and formalising relationships between distinct data groups. Furthermore, you will establish the foundational understanding of relations and functions necessary for progression into advanced calculus and abstract algebra. This course is targeted at students entering undergraduate foundation programmes requiring strong quantitative proficiency, particularly in mathematics, computer science, and engineering. It also serves as an intensive structural refresher for professionals shifting into data-architecture or analytical roles demanding strong logical literacy. Prior exposure to standard secondary school mathematics is assumed; focus is placed strictly on mastery and application of rigorous definitions.

Enrolment valid for 12 months
This course is also part of the following learning track. You may join the track to gain comprehensive knowledge across related courses.
MTH 101: Elementary Mathematics I - Algebra and Trigonometry
MTH 101: Elementary Mathematics I - Algebra and Trigonometry
Master the foundational mathematical structures essential for success in quantitative undergraduate degrees and professional technical roles. This comprehensive learning track delivers a rigorous treatment of algebra and trigonometry, moving rapidly from fundamental set theory and real number operations to advanced topics including matrix algebra, complex numbers, and analytical trigonometry. You will establish the critical problem-solving framework required for advanced study in calculus, engineering mechanics, and data science. This programme is primarily designed for first-year university students in STEM disciplines requiring strong analytical bases, particularly engineering, physics, computer science, and economics. It also serves as an intensive, high-level refresher for professionals returning to academia or shifting into data-driven roles demanding precise numerical literacy and logical structuring. Prior competence in standard secondary school mathematics is assumed; focus is placed strictly on mastery and application of core definitions. Upon completion, you will possess the skills to construct rigorous logical arguments using set theory and mathematical induction, model complex relationships with functions and matrices, and analyze periodic systems using advanced trigonometry. You will demonstrate competence in solving diverse equation types, from quadratics to linear systems, and manipulating complex numbers in engineering applications. This track prepares you directly for the mathematical demands of second-year university studies and technical professional certification exams.

Master the foundational mathematical structures essential for success in quantitative undergraduate degrees and professional technical roles. This comprehensive learning track delivers a rigorous treatment of algebra and trigonometry, moving rapidly from fundamental set theory and real number operations to advanced topics including matrix algebra, complex numbers, and analytical trigonometry. You will establish the critical problem-solving framework required for advanced study in calculus, engineering mechanics, and data science. This programme is primarily designed for first-year university students in STEM disciplines requiring strong analytical bases, particularly engineering, physics, computer science, and economics. It also serves as an intensive, high-level refresher for professionals returning to academia or shifting into data-driven roles demanding precise numerical literacy and logical structuring. Prior competence in standard secondary school mathematics is assumed; focus is placed strictly on mastery and application of core definitions. Upon completion, you will possess the skills to construct rigorous logical arguments using set theory and mathematical induction, model complex relationships with functions and matrices, and analyze periodic systems using advanced trigonometry. You will demonstrate competence in solving diverse equation types, from quadratics to linear systems, and manipulating complex numbers in engineering applications. This track prepares you directly for the mathematical demands of second-year university studies and technical professional certification exams.

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Course Chapters

1. Introduction
7
This chapter introduces the fundamental language and notation of set theory. Mastering these primary definitions is mandatory for structuring logical arguments and categorising data in all advanced mathematical and computational disciplines. You will master four objectives: defining sets and elements with precision; using roster and set-builder notation; identifying finite and infinite collections; and applying basic symbols for membership and subsets.
Concept Overviews
7 Lessons
1:52:52
2. Subsets
7
This chapter defines the hierarchical inclusion of sets and the precise conditions for set equality. Mastery of subset logic is critical for constructing rigorous proofs and managing data inheritance in computational architecture. You will master four objectives: distinguishing between proper and improper subsets; proving set equality through mutual inclusion; calculating the total number of subsets for finite collections; and defining the universal set and empty set within inclusion frameworks.
Concept Overviews
7 Lessons
3. Sets of Numbers
7
This chapter defines the rigorous classification of numerical collections and their hierarchical inclusion. Mastery of these standard sets is mandatory for defining domains in calculus, establishing computational constraints, and ensuring logical consistency in mathematical proofs. You will master four objectives: categorising natural, integer, rational, and irrational numbers; identifying the real and complex number systems; applying interval notation for continuous subsets; and mapping the nested relationship between numerical sets.
Concept Overviews
7 Lessons
4. Operations on Sets
5
This chapter covers the algebraic manipulation of sets to form new collections through rigorous logical rules. Mastering these operations is foundational for database querying, probability theory, and complex data stratification in engineering and analytical systems. You will master four objectives: performing unions, intersections, and set differences; calculating absolute and relative complements; applying De Morgan's laws to simplify set expressions; and identifying disjoint sets.
Concept Overviews
5 Lessons
5. Algebra of Sets
9
This chapter covers the fundamental laws governing set operations and the formal proof of set identities. Mastering this symbolic logic is essential for simplifying complex boolean expressions and ensuring the validity of analytical arguments in computer science and mathematical engineering. You will master four objectives: applying idempotent, associative, and commutative laws; implementing distributive and absorption laws; proving identities using De Morgan's laws; and simplifying expressions using identity and complement laws.
Concept Overviews
9 Lessons
6. Venn Diagrams
5
4
This chapter introduces the visual representation of set relationships and the spatial logic of inclusions. Mastery of Venn diagrams is essential for mapping data overlaps, solving combinatorial problems, and verifying set identities through geometric interpretation. You will master four objectives: constructing diagrams for two and three sets; shaded representation of unions and intersections; interpreting regions of relative and absolute complements; and solving practical survey problems using the principle of inclusion-exclusion.
Concept Overviews
5 Lessons
Problem Walkthroughs
4 Lessons
7. Cartesian Products
4
1
This chapter defines the construction of ordered pairs and the product of distinct sets. Understanding these mappings is mandatory for defining relations, functions, and the multidimensional coordinate systems used in linear algebra and database schema design. You will master four objectives: constructing ordered pairs and n-tuples; calculating the cardinality of product sets; representing Cartesian products on a coordinate plane; and applying the non-commutative property of set multiplication.
Concept Overviews
4 Lessons
Problem Walkthroughs
1 Lesson