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Topic outline
- Welcome to Algorithms & Algorithms Lab
Welcome to Algorithms & Algorithms Lab
Dear Students
Welcome to the Algorithms (CSE 214) & Algorithms Lab (CSE 215) courses. Algorithms are used in every part of computer science. They form the field's backbone. In computer science, an algorithm gives the computer a specific set of instructions,
which allows the computer to do everything, be it running a calculator or running a rocket. I am Zabirul Islam will be your co-pilot in this online journey of learning. I care about your success in these courses. I'm glad you are here.
Md. Zabirul Islam
Lecturer, Department of Computer Science and Engineering
Daffodil International University
Welcome Note from Instructor
Instructor
Md. Zabirul Islam
Lecturer, Department of CSE
Daffodil International University
Algorithms deals with efficient ways to solve different mathematical and real-life problems. It covers the common algorithms, algorithmic paradigms, and data structures used to solve computational problems. This course emphasizes the relationship between
algorithms and programming and explores algorithms from the programmer’s perspective for solving problems efficiently using various programming languages.
This course introduces students to the analysis and design of computer algorithms. Upon completion of this course, students will be able to do the following:
- Analyse the asymptotic performance of algorithms.
- Demonstrate familiarity with major algorithms and data structures.
- Apply important algorithmic design paradigms and methods of analysis.
- Synthesize efficient algorithms in common engineering design situations.
CO1
Analyze and calculate time complexity and space complexity of various algorithms or any written code using mathematical formula and comparison of algorithms.
CO2
Generate and interpret the output of iterative and recursive codes with the analysis of the problem definition.
CO3
Identify which algorithm listed under which algorithmic paradigm. Compare among various algorithms/implemented codes and choose the efficient one.
CO4
Break down and describe the simulation of various algorithms for different input values.
CO5
Design and apply appropriate algorithms to solve real-life problems.
1.
Introduction to Algorithms, (3rd Edition, MIT Press, 2009) ISBN: 9780262033848.
by Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein
2.
Algorithms (4th Edition)
by Robert Sedgewick and Kevin Wayne
3.
Algorithm Design
by Jon Kleinberg, Eva Tardos
4.
Data Structures And Algorithms Made Easy In JAVA
by Narasimha Karumanchi
-
Quick Guide
Weeks
Assessments
-
Lesson Objective:
- To appreciate the role of algorithm in problem solving and importance of complexity analysis for algorithms
Topics of Discussion:
- Introduction and importance of Algorithm and its application
- Function and Recursion, Euclid’s Greatest Common Divisor(GCD) Algorithm
Expected Learning Outcomes:
- Gain knowledge about the importance of algorithm
- Perform exercise on function and recursion function
Class Video Resources
Lesson 1 (Introductory Class-L)
Reading Materials
Lesson 1 Slide
Additional Video Resources
Lesson 1
Interactive Contents
You are expected to give at least one post under each discussion topic
-
week 2
Notation and Complexity Analysis
Lesson Objective:
- To appreciate the role of algorithm in problem solving and importance of complexity analysis for algorithms
Topics of Discussion:
- Introduction with the Asymptotic Notation
- Discussion on the Complexity of Algorithms
- Importance of Complexity for designing an Algorithm
Expected Learning Outcomes:
- Gain knowledge about the importance of algorithm
- Find out the Asymptotic Notation from an Algorithm
- Find out the complexity from any code or algorithm
-
week 3
Searching and Sorting Algorithm
Lesson Objective:
- To introduce with brute force type problems in searching & sorting domains
Topics of Discussion:
- Introduction to brute force techniques.
- Introduction to the searching Algorithm.
- Introduction to the sorting Algorithm
Expected Learning Outcomes:
- Knowledge about the Linear Search algorithm and its complexity
- Knowledge about the Insertion sort algorithm and its complexity
- Knowledge about the Bubble sort algorithm and its complexity
- Knowledge about the Selection sort algorithm and its complexity
- Exercise the Sorting and searching Algorithm with some additional problems.
Class Video Resources
Lesson 1 (K)
Lesson 1 (L)
Reading Materials
Lesson 1 Slide
Additional Video Resources
Lesson 1
Interactive Contents
You are expected to give at least one post under each discussion topic
-
week 4
Searching and Sorting Algorithm
Lesson Objective:
- To teach the main strategy of divide & conquer and the examples/ problems those are typically solved by this strategy and the complexity analysis of those problems
Topics of Discussion:
- Introduction to Divide and Conquer Approach.
- Introduction to the searching Algorithm based on Divide and Conquer Approach.
- Introduction to the Sorting Algorithm based on Divide and Conquer Approach.
Expected Learning Outcomes:
- Knowledge about the Binary Search algorithm and its complexity
- Knowledge about the Merge sort algorithm and its complexity
- Knowledge about the Quicksort algorithm and its complexity
- Knowledge about the Selection sort algorithm and its complexity
- Exercise the Sorting and searching Algorithm with some additional problems.
Class Video Resources
Lesson 1 (K)
Lesson 1 (L)
Reading Materials
Lesson 1 Slide
Additional Video Resources
Lesson 1
You are expected to give at least one post under each discussion topic
-
week 5
Introduction to Greedy Approach
Lesson Objective:
- To teach the basic methodology of greedy algorithm and the examples/ problems those are typically solved by this methodology and the complexity analysis of those problems
Topics of Discussion:
- Introduction to Greedy Approach
- Discussion on Coin Change Problem
- Discussion on Bin packing Problem
- Discussion on Knapsack Problem
- Discussion on Hoffman coding
Expected Learning Outcomes:
- Solve the Coin Change Problem based on Greedy Method
- Solve the Knapsack Problem based on Greedy Method
- Solve the Hoffman coding based on Greedy Method
- Solve the Bin packing Problem based on Greedy Method
- Exercise the Sorting Algorithm with some additional problems in the Lab.
Class Video Resources
Lesson 1 (K)
Lesson 1 (L)
Reading Materials
Lesson 1 Slide
Additional Video Resources
Lesson 1
Interactive Contents
Greedy Algorithm
Quiz (Greedy Algorithm)
You are expected to give at least one post under each discussion topic
-
week 6
Introduction to Dynamic Programming
Lesson Objective:
- To teach the strategy of dynamic programming and the examples/ problems those are typically solved by this strategy and the complexity analysis of those problems
Topics of Discussion:
- Introduction to Dynamic Programming (DP)
- Discussion on Fibonacci Numbers Problem
- Discussion on Coin Change Problem (DP)
- Discussion on Knapsack Problem (0/1)
- Quiz #02
Expected Learning Outcomes:
- Solve the Coin Change Problem based on DP
- Solve the Knapsack Problem based on DP
- Solve the Fibonacci Numbers Problem based on DP
- Exercise the Bin-packing Algorithm with some additional problems in the Lab.
Class Video Resources
Lesson 1 (K)
Lesson 1 (L)
Reading Materials
Lesson 1 Slide
Additional Video Resources
Lesson 1
Interactive Contents
Dynamic Algorithm
Quiz (Dynamic Algorithm)
You are expected to give at least one post under each discussion topic
-
Lab 1 Task (L) Assignment
Restricted Not available unless: You belong to CSE215-L
Lab 1 Task (K) Assignment
Restricted Not available unless: You belong to CSE215-K
Lab 2 Task (K) Assignment
Restricted Not available unless: You belong to CSE215-K
1. Linear Search
2. Binary Search
3. Bubble Sort
4. Merge Sort
Lab 2 Task (L) Assignment
Restricted Not available unless: You belong to CSE215-L
1. Linear Search
2. Binary Search
3. Bubble Sort
4. Merge Sort
Lab Task 3 Assignment
Restricted Not available unless: You belong to CSE215-K
Insertion Sort
Selection Sort
Quicksort
Lab Task 3 Assignment
Restricted Not available unless: You belong to CSE215-L
Insertion Sort
Selection Sort
Quicksort
Lab Task 4 Assignment
Restricted Not available unless: You belong to CSE215-L
1. Greedy Algorithm ( Fractional Knapsack, Coin Exchange, Bin Packing)
2. Dynamic Algorithm ( 0/1 Knapsack (Recursive+Iterative) )
Lab task 5 (k) Assignment
Restricted Not available unless: You belong to CSE215-K
Implement BFS and DFS including finding the path and submit the source file here.
Lab task 5 (L) Assignment
Restricted Not available unless: You belong to CSE215-L
Implement BFS and DFS including finding the path and submit the source file here.
-
week 8 Introduction to Graph And Graph Traversal
Lesson Objective:
- To teach how graphs and trees play an important role in solving many of our real life problems and writing corresponding algorithms to solve the problems
Topics of Discussion:
- Introduction to Graph
- Graph Representation
- Discussion on Graph Traversal
Expected Learning Outcomes:
- Solve the Breadth-First Search (BFS) algorithm
- Solve the Depth First Search (DFS) algorithm
Class Video Resources
Lesson 1 (K)
Lesson 1 (L)
Reading Materials
Lesson 1 Slide
Additional Video Resources
Lesson 1
Interactive Contents
BFS/DFS
BFS/DFS (Quiz
)
You are expected to give at least one post under each discussion topic
-
week 9 Shortest Path Algorithm
Lesson Objective:
- To teach how graphs and trees play an important role in solving many of our real life problems and writing corresponding algorithms to solve the problems
Topics of Discussion:
- Discussion on Single Source Shortest Path
- Discussion on All Pair Shortest Path Algorithm
Expected Learning Outcomes:
- Single-Source Shortest Path(SSSP) by Dijkstra’s Algorithm
- All Pair Shortest Path Algorithm by Floyd–Warshall algorithm
Class Video Resources
Lesson 1 (K)
Lesson 1 (L)
Reading Materials
Lesson 1 Slide
Additional Video Resources
Lesson 1
Interactive Contents
BFS/DFS
BFS/DFS (Quiz
)
You are expected to give at least one post under each discussion topic
-
Lesson Objective:
- To teach the strategy of dynamic programming and the examples/ problems those are typically solved by this strategy and the complexity analysis of those problems.
- To teach the basic methodology of greedy algorithm and the examples/ problems those are typically solved by this methodology and the complexity analysis of those problems
Topics of Discussion:
- Knapsack Problem
- 0/1 Knapsack Problem
- Greedy Algorithm
- Dynamic Programming on 0/1 Knapsack Problem
Expected Learning Outcomes:
- Understanding the 0/1 Knapsack & Frictional Knapsack
- Applying Greedy Algorithm on Knapsack Problem
- Problems on Greedy Algorithm on 0/1 Knapsack
- Optimal Solution to 0/1 Knapsack Problem using Dynamic Programming
Class Video Resources
Lesson 1 (K)
Lesson 1 (L)
Reading Materials
Lesson 1 Slide
Additional Video Resources
Lesson 1
Interactive Contents
Dynamic Algorithm
Quiz (Dynamic Algorithm)
You are expected to give at least one post under each discussion topic
-
Submit your Lab report here Assignment
Restricted Not available unless: You belong to CSE215-K
Submit your Lab report here Assignment
Restricted Not available unless: You belong to CSE215-L
-
week 12
Final Examination
Lab Quiz (K)
Restricted Not available unless: You belong to CSE215-K
Lab Quiz (L)
Restricted Not available unless: You belong to CSE215-L
- Topic 14
- Topic 15
- Topic 16
- Topic 17
- Topic 18
- Topic 19
- Topic 20
Topic 20
You are expected to give at least one post under each discussion topic