Cornell CS 4820: Introduction to Analysis of Algorithms
CS 4820 is Cornell's upper-level algorithms course, covering greedy algorithms, divide and conquer, dynamic programming, network flow, and NP-completeness and reductions, with a heavy emphasis on proving correctness and analyzing complexity. It's a required CS core course and a capstone of the theory sequence.
Fennie is independent and not affiliated with Cornell University. This is an unofficial study guide.
What makes it hard
The course is proof-heavy: you don't just design algorithms, you prove they're correct and analyze their running time rigorously, and on exams you invent algorithms for unseen problems and justify them. Dynamic programming and reductions are the famous walls. Recognizing the right subproblem structure or the right reduction is a creative skill that only volume builds.
What you'll cover
- • Greedy algorithms
- • Divide and conquer
- • Dynamic programming
- • Network flow
- • NP-completeness and reductions
- • Correctness proofs and complexity analysis
The CS 4820 study guide
How to study for Cornell CS 4820, step by step.
- 1
Practice inventing algorithms, not memorizing them
CS 4820 exams give you unseen problems and ask you to design and prove an algorithm. Solve many problems from scratch, because recognizing a known solution is worthless when the problem is new.
- 2
Always prove correctness and runtime
Half the credit is the proof. For every algorithm you design, write the correctness argument and the complexity analysis, because the exam grades the justification as much as the idea.
- 3
Drill dynamic programming until the structure is reflex
DP is the classic wall: it's about seeing the subproblem and recurrence. Work many DP problems until identifying the state and transition feels routine rather than mysterious.
- 4
Build a reductions playbook
NP-completeness reductions reward pattern familiarity. Collect the standard reductions and the problems they come from, then practice mapping new problems onto known hard ones.
- 5
Write solutions under exam conditions
Before each prelim, solve unfamiliar problems on blank paper under time pressure. The course rewards producing complete, rigorous arguments fast, a different skill from following a posted solution.
Today
Today's CS 4820 plan
What a Fennie Daily Plan looks like for CS 4820. Yours is built from your own syllabus and adapts every day to your deadlines and progress.
First plan free, no card required. Fennie is independent and unaffiliated with your school.
FAQ
Is CS 4820 at Cornell hard?
Yes. It's one of the harder required CS courses because it's proof-heavy and exams ask you to invent and rigorously justify algorithms for unseen problems. Dynamic programming and NP-completeness reductions are the usual walls, and only solving many problems builds the needed intuition.
How do I study for CS 4820?
Solve unfamiliar problems from scratch and prove every algorithm's correctness and runtime, since that's exactly what exams test. Drill dynamic programming until spotting the subproblem is reflexive, and build a playbook of standard NP-completeness reductions.
What should I know before CS 4820?
Solid CS 2800 discrete-math and proof skills plus comfort with data structures from CS 2110. The course assumes you can write a clean induction or contradiction proof, since correctness arguments are half of nearly every problem.
More Cornell courses
CS 1110: Introduction to Computing: A Design and Development Perspective
CS 1110 is Cornell's Python-based first programming course, covering variables and types, functions, conditionals and loops, objects and classes, recursion, and testing. It's taken by intended CS majors and a large non-major population alike, and it leads into CS 2110 for those continuing in the major.
CS 2110: Object-Oriented Programming and Data Structures
CS 2110 is Cornell's second programming course, taught in Java and cross-listed as ENGRD 2110. It covers object-oriented design, data structures (lists, trees, hash tables, graphs), recursion, and an introduction to algorithmic analysis. It's the gateway most CS and engineering students name as the major's first real workload jump.
CS 2800: Discrete Structures
CS 2800 is Cornell's discrete mathematics course for CS majors, covering logic and proof, induction, sets, functions and relations, combinatorics, graph theory, basic probability, and finite-state machines. It's the bridge from coding to the mathematical reasoning the upper-level theory courses assume.
CS 3110: Data Structures and Functional Programming
CS 3110 is Cornell's famous functional-programming and data-structures course, taught in OCaml. It covers immutability, recursion, higher-order functions, modules and functors, formal specification and verification, and reasoning about correctness and complexity. It's a required CS core course and a notorious pace step-up after CS 2110.