Skip to content

Xiangyu2141480/DTS203

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

2 Commits
 
 
 
 

Repository files navigation

DTS203TC - Design and Analysis of Algorithms

Module Overview

  • Credit Value: 5.0
  • Semester: Block 1 of Semester 2, 2023-2024
  • Module Leader: Dr. Qi Chen (Qi.Chen02@xjtlu.edu.cn)

Educational Aims

This module introduces key concepts in algorithm design and analysis, focusing on:

  • Fundamental methods in data structures and algorithms
  • Computationally hard problems and solutions
  • Application of algorithms in various domains

Learning Outcomes

  1. Algorithm Classes: Describe different algorithm classes and their design principles.
  2. Algorithm Design: Apply principles to create efficient algorithms.
  3. Data Structures: Use basic data structures for solving classical problems.
  4. Computational Intractability: Understand and demonstrate familiarity with NP-completeness.

Schedule

Lectures

  • Mon 16:00 – 18:00: TC-AB-2003 / Qi Chen
  • Tue 13:00 – 15:00: TC-AB-2003 / Qi Chen
  • Wed 10:00 – 12:00: TC-AB-2003 / Qi Chen
  • Thu 16:00 – 18:00: TC-E-2032 / Pascal Lefèvre

Labs

  • Thu 18:00 – 19:00: TC-D-2001 / TC-D-3001 / Pascal Lefèvre

Seminars

  • Week 6, Thu 16:00 – 18:00: TC-E-2032 / Qi Chen

Assessment

  • Exam (60%): 2 hours, Week 6
  • Coursework (40%): Deadline March 24th, 2024, 23:59 Beijing Time

Syllabus Highlights

  • Week 1: Introduction, Growth of Functions, Divide-and-Conquer
  • Week 2: Elementary Data Structures, Heapsort, Hash Tables
  • Week 3: Dynamic Programming, Greedy Algorithms
  • Week 4: Graph Algorithms, Minimum Spanning Trees
  • Week 5: String Matching, NP-Completeness
  • Week 6: Revision Q&A

Key Text

  • Introduction to Algorithms (3rd Edition), Thomas H. Cormen et al.

Contacts

Additional Information

  • Attendance: Required for all sessions; use AMS for recording.
  • Coursework Submission: Via Learning Mall before the deadline.
  • Academic Integrity: Strict adherence required; no Generative AI allowed.
  • Support: Contact your Module Leader or Academic Advisor for assistance.

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published