• Hello World!

Learning outcomes and competences

After attending this course, participants should be able to
  • Given an algorithm, analyze its correctness and running time.
  • Given a problem, design a correct and efficient algorithm for it, express it in a form that a programmer can easily convert into code.
  • Have an idea about what problems are intractable, and basic algorithms for those that are tractable.
  • Know the mathematical techniques that you will need to analyze your algorithms.

  • Course information


    In this course we will discuss some basic techniques for algorithm design and analysis, including:
    - Sorting and searching
    - Divide-and-conquer
    - Dynamic programming
    - Greedy algorithms
    - Graph algorithms


    Qin Zhang
    In-person office hour: Wednesday 1-2pm, Luddy 3044
    Online office hour: by appointment.

    Associate Instructors
  • Boli Fang (leading AI)
    In-person office hour: Tuesday 2-3pm, Luddy 2033EE
    Online office hour: Thursday 2-3pm, or by appointment.
    Zoom link will be posted in Canvas (as an announcement)
  • Alina Filimokhina (grader)

  • Time and place

    9:45 AM–11:00 AM Monday/Wednesday, Myles Brand Hall (Informatics) E130
    For the first two weeks, see the announcement in Canvas.


    Required Textbook: [KT] Algorithm Design, J. Kleinberg, E. Tardos. Pearson Education.
    Supplementary Textbook: [CLRS] Introduction to algorithms, T. Cormen, C.Leiserson, R. Rivest, C. Stein. 3rd edition. MIT

    Tentative Schedule

    - Introduction (overview, Big-O notations, some basic problems and running times), 3 lectures
    - Graph algorithms (representation, graph traversal, DAG, topological sort), 4 lectures
    - Greedy algorithms (interval scheduling, Shortest path, MST), 6 lectures
    - Mid-term preparation, 1 lecture
    - Mid-term
    - Divide-and-conquer (mergesort, counting inversions, closest pair), 4 lectures
    - Dynamic programming (weighted interval scheduling, subset sum, sequence alignment), 4 lectures
    - Final preparation, 1 lecture
    - Final


    • Assignments 30%

      Five written assignments. Assignments are posted in Canvas. The answers should be submitted via Canvas . If you can, typeset in your favorite software. If you are handwriting (+scanning), make sure it is legible.
      No extensions or late homework will be granted (unless emergencies; medical emergencies need doctor's notes covering the deadline dates).

    • Exams 70%

      (1) Mid-term 30%
      (2) Final 40%
      There will be NO make-up exams. If students have to miss the in-class midterm exam due to family/medical emergencies (and/or other reasons which will be granted on a case by case basis; medical emergencies need doctor's notes covering the exam dates), they need to contact the instructor before the exams for permission, and their other exam grades will be re-weighted. Internship and job application interviews and paper deadlines are NOT proper reasons to miss an exam.

    Course policies

    For assignments, students may discuss answers with anyone, including problem approaches and proofs. But all students must write their own proofs, and write-ups. The names of all people that you have talked to should be listed at the beginning of the first page. If a solution comes from existing papers/web/books, they must be properly cited, and you must write the solution in a way that demonstrates your understanding (simply copying the solution will be considered as plagiarism, and will result an "F" for the entire course). All deadlines are firm. No late assignments will be accepted unless there are legitimate circumstances.
    For more details, see Indiana University Code of Student Rights, Responsibilities, and Conduct.


      CSCI-C241 "Discrete Structures for Computer Science", CSCI-C343 "Data Structures", and MATH-M 216 "Analytic Geometry and Calculus II" (or MATH-M 212 CALCULUS II). The prerequisites are enforced.