đź‘‹ Welcome to CS 2500: Algorithms!

Welcome to CS 2500: Algorithms — a rigorous and rewarding course that will teach you how to design, analyze, and communicate efficient solutions to computational problems. This class focuses on both thinking algorithmically and writing clearly — in code, logic, and mathematics.

Note: This website provides only minimal public-facing information. For full details — including lecture materials, assignments, announcements, and grading — please refer to the course’s Canvas pages or explore the additional sections linked on this site.

Course Info

  • Course: CS 2500: Algorithms
  • Credits: 3
  • Semester: Fall 2025
  • Where: CS Building Room 222
  • When: Tuesdays and Thursdays, 11:00 AM – 12:15 PM
  • Labs: Weekly

Instructor Info

  • Instructor: Dr. Shubham Chatterjee
  • Email: shubham.chatterjee@mst.edu
  • Office: CS 320
  • Office Hours: By appointment — see Office Hours and Support page on Canvas

Course Overview

CS 2500: Algorithms is a rigorous and engaging course designed to teach you how to design, analyze, and communicate efficient solutions to computational problems. You will explore fundamental algorithmic techniques — including divide-and-conquer, greedy methods, dynamic programming, and graph algorithms — while learning to reason mathematically about correctness, efficiency, and complexity. The course emphasizes both theoretical understanding and practical implementation, helping you build the skills needed to tackle challenging problems in computer science.

What You’ll Need

Main Book (Required)

  • Algorithm Design by Jon Kleinberg and Eva Tardos

Supplementary Reading

  • Algorithms by Sanjoy Dasgupta, Christos Papadimitriou, and Umesh Vazirani
  • Introduction to Algorithms by Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein
  • Introduction to the Design and Analysis of Algorithms by Anany Levitin

What This Course Is (and What It Isn’t)

Understanding the true nature of this algorithms course will help you approach it with the right mindset and expectations. This is primarily a mathematical problem-solving course that uses programming as a tool — not the main focus.

What You’ll Dive Into:

  • Using mathematical thinking to tackle computational problems
  • Learning how to write clear, rigorous proofs to show why algorithms work
  • Exploring the big theoretical ideas that shape computer science
  • Sharpening your analytical skills with interesting, challenging problems
  • Understanding the why behind algorithm efficiency and complexity
  • Practicing formal notation and clear communication of your ideas
  • Building on concepts from discrete math, like graphs and combinatorics

What You Don’t Need to Worry About:

  • This isn’t a course focused on specific programming languages or syntax tricks
  • We won’t spend time on software design patterns or engineering best practices
  • It’s not about memorizing solutions — the focus is on understanding and reasoning
  • Writing code that “just works” without explanation won’t be the goal here
  • You won’t master this overnight — progress comes with practice and patience
  • While intuition helps, we will always back up ideas with formal proof

Big Picture: Think of this course as a fun intellectual workout — you’ll stretch your problem-solving muscles, build confidence in mathematical thinking, and gain tools that will make you a stronger computer scientist. And don’t worry — we’ll be here to guide you every step of the way!

Course Focus: Theory First, Implementation Second

This course is primarily a theoretical exploration of the mathematical foundations of algorithms. While there is a lab component, the heart of the course centers on:

  • Rigorous mathematical proofs of algorithm correctness
  • Formal complexity analysis using asymptotic notation
  • Theoretical understanding of algorithm design paradigms
  • Precise technical communication of mathematical concepts

Important Note: Do not be misled by the programming components — coding implementations are included to reinforce your understanding of theoretical concepts, not to replace them.

Your success in this course will be measured primarily by your ability to construct clear, rigorous mathematical arguments and communicate them effectively.

Remember, developing strong proof-writing skills is not just an academic exercise — it is a key ABET accreditation criterion and reflects the problem-solving and communication abilities that employers highly value in computer science graduates. Submissions that are not at least 95% compliant with the taught proof format will lose substantial points, as clear mathematical communication is just as important as arriving at the correct answer.

Classroom Conduct: Fostering a Respectful Learning Environment

Our classroom and associated online forums are dedicated spaces for learning, intellectual exploration, and the respectful exchange of ideas. To maintain a positive and inclusive environment for everyone, please follow these expectations:

In the Classroom

  • Respectful Engagement: Engage courteously with peers and instructors. Listen actively, value diverse perspectives, and avoid interruptions or dismissive remarks.
  • Constructive Dialogue: Focus disagreements on ideas, not individuals. Share your viewpoints thoughtfully and remain open to different perspectives.
  • Inclusive Language: Use language that respects all identities and avoids discrimination based on race, ethnicity, gender, orientation, religion, ability, or other characteristics.
  • Appropriate Demeanor: Maintain a demeanor conducive to learning. Minimize distractions and follow any class-specific technology use guidelines.

In Online Forums and Communication

  • Netiquette: Communicate with a polite, professional tone. Written communication can be easily misinterpreted, so prioritize clarity and consideration.
  • Thoughtful Contributions: Make meaningful, relevant points in discussions. Avoid short, repetitive, or off-topic posts.
  • Appropriate Language: Avoid offensive language, personal attacks, or discriminatory remarks.
  • Privacy: Respect the privacy of classmates and instructors. Be mindful when sharing personal information online.
  • Clarity and Conciseness: Write clearly and use proper grammar and spelling to ensure your messages are easily understood.
  • Informative Subject Lines: Use descriptive subject lines in emails to help instructors and classmates navigate topics efficiently.
  • Stay Focused: Keep online discussions relevant to the course material.

Consequences of Disrespectful Behavior

Disruptive or disrespectful behavior, whether in person or online, will not be tolerated. Depending on severity and frequency, consequences may include:

  • A verbal warning
  • Removal from the classroom or online discussion
  • Lowering of the participation grade
  • Referral to the Dean of Students or appropriate university officials under the student code of conduct

By fostering a respectful, thoughtful environment, we can all contribute to a richer and more effective learning experience. Thank you for helping create a positive community!