Course Details
01:198:206 - Introduction to Discrete Structures II
- Course Number: 01:198:206
- Instructor: Konstantinos Michmizos
- Course Type: Undergraduate
- Semester(s) Offered: Fall, Winter, Spring, Summer
- Semester 1: Fall
- Semester 2: Spring
- Credits: 4
- Description:
Provides the background in combinatorics and probability theory required in design and analysis of algorithms, in system analysis, and in other areas of computer science.
- Learning Management System (LMS): https://rutgers.instructure.com/courses/104702
- Syllabus: https://rutgers.instructure.com/courses/104702/assignments/syllabus
- Video Intro: https://youtu.be/sHacD6aDnbQ
- Instructor Profile: Michmizos, Konstantinos
- Prerequisite Information:
01:198:205 or 14:332:202; 01:640:152. Credit not given for this course and 01:640:477 or 14:332:226.
- A grade below a "C" in a prerequisite course will not satisfy that prerequisite requirement.
- Course Links: 01:198:205 - Introduction to Discrete Structures I
- This course is a Pre-requisite for the Following Courses: 01:198:334 - Introduction to Imaging and Multimedia, 01:198:344 - Design and Analysis of Computer Algorithms, 01:198:352 - Internet Technology, 01:198:460 - Introduction to Computational Robotics, 16:198:522 - Network and Combinatorial Optimization Algorithms
- Topics:
Counting: Binomial Coefficients, Permutations, Combinations, Partitions.
Recurrence Relations and Generating Functions.
Discrete Probability:
Events and Random Variables;
Conditional Probability, Independence;
Expectation, Variance, Standard Deviation;
Binomial, Poisson and Geometric Distributions; law of large numbers.
Some Topics from Graph Theory: Paths, Components, Connectivity, Euler Paths, Hamiltonian Paths, Planar Graphs, Trees. - Expected Work: Weekly assignments
- Exams: 1 or 2 tests, Final Exam
- Learning Goals:
Computer Science majors ...
- will be prepared to contribute to a rapidly changing field by acquiring a thorough grounding in the core principles and foundations of computer science (e.g., techniques of program design, creation, and testing; key aspects of computer hardware; algorithmic principles).
- will acquire a deeper understanding on (elective) topics of more specialized interest, and be able to critically review, assess, and communicate current developments in the field.
- will be prepared for the next step in their careers, for example, by having done a research project (for those headed to graduate school), a programming project (for those going into the software industry), or some sort of business plan (for those going into startups).
