CS302 Algorithms and Data Structures

Print this page Please use the scale options of your printing settings for adjustments.

Course Code Course Title Weekly Hours* ECTS Weekly Class Schedule
T P
CS302 Algorithms and Data Structures 3 2 6 Monday 3-5:50pm
Prerequisite CS105, MATH204 It is a prerequisite to
Lecturer Office Hours / Room / Phone

Currently not available

E-mail
Assistant Assistant E-mail
Course Objectives The objecitve of the course is to introduce and train students in design and analysis of data structures and algorithms in the program
implementation. It demonstrates the analysis of the computational complexity of programs along with their comparative analysis.
Textbook The Algorithm Design Manual, 2nd Edition, Steven S. Skiena, Springer Introduction to Algorithms, 2nd edition by Cormen, Leiserson, Rivest and Stein, MIT Press Algorithms, 4th Edition, Sedgewick and Wayne, Pearson
Additional Literature
Learning Outcomes After successful  completion of the course, the student will be able to:
  1. Define basic types of data structures like stackcs, queues, sets, arrays, etc.
  2. Define, explain and use various algorithmic paradigms for problem-solving
  3. Modify existing and develop new efficient algorithms
  4. Analyze complexity of algorithms
  5. Be able to recognize the appropriate algorithmic method to solve a newly given problem
Teaching Methods Class discussions with examples.
Teaching Method Delivery Teaching Method Delivery Notes
WEEK TOPIC REFERENCE
Week 1 Course logistics
Week 2 Introduction to algorithms, Asymptotic notation Chapter 1, PPT 1, 2
Week 3 Logarithms, Elementary Data Structures Chapter 2, PPT 3, 4
Week 4 Dictionaries, Hashing Chapter 3, PPT 5, 6
Week 5 Heapsort, Priority Queues Chapter 3,4, PPT 7
Week 6 Mergesort, Quicksort, Linear Sorting Chapter 4, PPT 8, 9
Week 7 Review and Test 1 Chapter 6
Week 8 Graph Data structures, BFS, DFS Chapter 5, PPT 10, 11, 12
Week 9 Minimum spanning trees, shortest paths Chapter 6, PPT 13, 14
Week 10 Backtracking and examples Chapter 7, PPT 15
Week 11 Introduction to dynamic programming Chapter 8, PPT 16
Week 12 Edit distance, applications of DP Chapter 8, PPT 17, 18
Week 13 Review and Test 2 Chapter 5,6
Week 14 NP-completeness Chapter 9, PPT 19
Week 15 Satisfiability and Review Chapter 9, PPT 20
Assessment Methods and Criteria Evaluation Tool Quantity Weight Alignment with LOs
Final Exam 1 40 1,2,3,4,5,6,7,8
Semester Evaluation Compenents
Tests 2 50 1,2,3,4,6
In-class participation 1 10 1,2,3,4,5,6,7,8
***     ECTS Credit Calculation     ***
 Activity Hours Weeks Student Workload Hours Activity Hours Weeks Student Workload Hours
Lecture Hours 3 15 45 Tests study 17 2 34
Final Exam Study 26 1 26 Home Study 3 15 45
        Total Workload Hours = 150
*T= Teaching, P= Practice ECTS Credit = 6
Course Academic Quality Assurance: Semester Student Survey Last Update Date: 15/02/2021
QR Code for https://ecampus.ius.edu.ba/course/math204-discrete-mathematics

Print this page Please use the scale options of your printing settings for adjustments.