DESIGN AND ANALYSIS OF COMPUTER ALGORITHMS
Venue: SEC 111, Busch Campus, Rutgers University
Time: Wednesdays 12:10 - 1:30 pm ET and Fridays 2:00 - 3:20 pm ET
FALL 2025 (Sections 12, 13, 14, and 15)
Venue: SEC 111, Busch Campus, Rutgers University
Time: Wednesdays 12:10 - 1:30 pm ET and Fridays 2:00 - 3:20 pm ET
FALL 2025 (Sections 12, 13, 14, and 15)
Office hours: Friday 11:30-12:30 pm [Hill 407]
Daniel Baumgartner (Ph.D. TA) Office hours: Thursday 2:15 pm - 3:15 pm [Core 244]
Yuange Li (Ph.D. TA) Office hours: Friday 12:30 pm - 1:30 pm [Zoom]
Nicholas D Belov (Part-Time Leader) Office hours: Thursday 12 pm -1 pm [Zoom]
Aryan Raut (Part-Time Leader) Office hours: Monday 10 am - 11am [Zoom]
Pratham Chauhan (Grader)
Navid Jery Pulikkottil (Grader)
💼 What the course offers: In this course, we learn how to think algorithmically to solve computational problems. We dive into a variety of useful and elegant algorithmic paradigms and learn how to analyze their complexity and correctness.
🎓 What You’ll Gain: a strong foundation in the core algorithmic principles every computer scientist needs, while developing the analytical mindset to solve complex problems with confidence. Whether you're heading into research, software engineering, or the startup world, this course sets you up with crucial and foundational skills.
Methods for expressing and comparing the time and space complexity of algorithms. Algorithmic design paradigms: greedy, dynamic programming, and divide and conquer. Application of complexity analysis and algorithmic techniques to a variety of problems, including allocation, searching, sorting, scheduling, packing, and graph problems (including bipartite matching, shortest path, and minimum spanning tree). NP and P problems (knapsack, satisfiability, vertex cover). NP Completeness and Reductions. Approximation algorithms.
Book: Algorithms by Jeff Erickson. Online version available: https://jeffe.cs.illinois.edu/teaching/algorithms/.
Practice Sessions and Quizzes:
Section 12: Friday 0405 PM - 0500 (SEC 205)
Section 13: Wednesday 0215 PM - 0310 (ARC 105)
Section 14: Wednesday 0405 PM - 0500 (SEC 207)
Section 15: Friday 0405 PM - 0500 (ARC 105)
20% Practice Sessions and Quizzes
35% Mid-term exam
45% Final exam
+10% Bonus credit (at the discretion of the Instructor/TAs/PTLs)
*Final grades will consider the overall performance of the four sections. A curve will be applied to help balance results, if the overall grade distribution is too low.
If you miss a practice session, you miss the opportunity to retake the quiz on that day. However, there will be many opportunities to earn bonus points.
Exams will be based on the materials taught in the class and the weekly practice problems (including the parts that may not necessarily be covered in the textbook).
Students are expected to follow the Rutgers academic integrity policy and the CS Department academic integrity policy for all their work in this course.
For any absence-related issues, please read the absence policy before reaching out to the instructors/TAs.
All types of non-confidential course-related questions should be posted to the CANVAS discussion page only. For confidential questions to the instructor/TAs/PTLs/graders, use the CANVAS inbox only.
Any grade-related questions should first be directed to TAs/PTLs. If the query remains unresolved for more than a week, only then it should then be escalated to the instructor.
Friday 10/10/2025, 2:00 - 3:20 pm: Mid-Term Exam
Wednesday 12/17/2025, 8:00 -11:00 am: Final Exam (according to University Schedule)