Course Name: Discrete Mathematics
Program: M.Sc. Data Science--SEM -01
This course introduces the fundamental concepts of discrete mathematics that form the mathematical foundation of data science, computer science, and artificial intelligence. It focuses on mathematical structures and techniques used to solve computational problems, analyze algorithms, and model real-world data.
Students will explore topics such as logic, set theory, relations and functions, proof techniques, combinatorics, graph theory, trees, recurrence relations, and discrete probability. The course emphasizes problem-solving, logical reasoning, and the application of discrete mathematical concepts to data-driven and computational scenarios.
By the end of the course, students will be able to apply discrete mathematical principles to algorithm design, data analysis, network modeling, optimization problems, and machine learning applications. The course develops analytical thinking and provides the theoretical background required for advanced studies in data science and related fields.
Learning Outcomes:
- Apply logical reasoning and mathematical proof techniques to solve computational problems.
- Analyze sets, relations, functions, and discrete structures used in data science.
- Solve counting and combinatorial problems using appropriate mathematical methods.
- Model and analyze networks using graph theory concepts.
- Apply recurrence relations and discrete probability in algorithmic and data science applications.
- Build a strong mathematical foundation for advanced topics in machine learning, artificial intelligence, and data analytics.
- Teacher: Admin PPSU