CS302 Algorithms and Data Structures

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Course Code Course Title Weekly Hours* ECTS Weekly Class Schedule
T P
CS302 Algorithms and Data Structures 3 2 6 TUE 13:00-14:50, THU: 11:00-11:50
Prerequisite CS105, MATH204 It is a prerequisite to
Lecturer Office Hours / Room / Phone

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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. Algorithms Made Easy, 5th Edition, Narasimha Karumanchi, M.Tech.
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. Active tutorial sessions for engaged learning and continuous feedback on progress. Active lab involve real algorithms, analysis, interpretation.
WEEK TOPIC REFERENCE
Week 1 Introduction to Course Chapter 1
Week 2 Basic Data Structures (Stacks, Queues, Sets, Arrays, Lists) Chapter 3
Week 3 Algorithm Analyses (Running Time) Chapter 2
Week 4 Searching (Linear Search, Binary Search) Chapter 4
Week 5 Sorting (Bubble Sort, Insertion Sort) Chapter 4
Week 6 Divide-Conquer (Quick Sort, Merge Sort) Chapter 4
Week 7 Binary Trees, Tree Traversal Chapter 6
Week 8 Review+MIDTERM EXAM
Week 9 Binary Search Trees, AVL Trees Chapter 6
Week 10 B Tree Chapter 7
Week 11 Hashing Chapter 7
Week 12 Heaps Chapter 4
Week 13 Graphs Chapter 5,6
Week 14 Dynamic Programming Chapter 8
Week 15 Review
Assessment Methods and Criteria Evaluation Tool Quantity Weight Alignment with LOs
Final Exam 1 35 1,2,3,4,5,6,7,8
Semester Evaluation Compenents
Midterm Exam 1 30 1,2,3,4,6
Quizzes 2 20 1,2,3,4,5,6,7,8
Homeworks 3 15 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 Quizzes Study 6 2 12
Homeworks 6 3 18 Homeworks 6 3 18
Active Tutorials 2 10 20 Final Exam Study 15 1 15
Quizzes Study 6 2 12 Quizzes Study 6 2 12
        Total Workload Hours = 150
*T= Teaching, P= Practice ECTS Credit = 6
Course Academic Quality Assurance: Semester Student Survey Last Update Date: 04/03/2020
QR Code for https://ecampus.ius.edu.ba/course/math204-discrete-mathematics

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