Data Structures and Algorithms Roadmap

Course Objective:

• Learn fundamental data structures and algorithms.
• Understand the principles of designing efficient algorithms.
• Develop skills to solve complex computational problems.
• Gain proficiency in analyzing algorithm performance.

1

Introduction to Data Structures and Algorithms:

• Overview of data structures and algorithms.
• Key concepts and terminology.
• Importance in computer science and software development.

2

Basic Data Structures:

• Arrays: Fixed-size sequential collection of elements.
• Linked Lists: Sequence of nodes where each node points to the next.
• Stacks and Queues: LIFO and FIFO data structures.
• Hash Tables: Efficient data retrieval using hash functions.

3

Advanced Data Structures:

• Trees: Hierarchical structure with nodes (Binary Trees, AVL Trees).
• Graphs: Set of nodes connected by edges (Directed, Undirected).
• Heaps: Binary trees for priority queues (Min-Heap, Max-Heap).
• Tries: Efficient retrieval of strings.

4

Basic Algorithms:

• Sorting: Bubble Sort, Insertion Sort, Selection Sort.
• Searching: Linear Search, Binary Search.
• Recursion: Recursive techniques and problem-solving.

5

Advanced:

• Sorting: Quick Sort, Merge Sort, Heap Sort.
• Searching: Depth-First Search (DFS), Breadth-First Search (BFS).
• Dynamic Programming: Optimizing complex problems by breaking them down.

6

Algorithm Design and Analysis:

• Big O Notation: Analyzing time and space complexity.
• Divide and Conquer: Breaking problems into subproblems.
• Greedy Algorithms: Making locally optimal choices.
• Graph Algorithms: Shortest path, Minimum spanning tree.

7

Project Work:

• Hands-on projects to apply learned concepts.
• Developing efficient algorithms for real-world problems.
• Testing and optimizing code.

Skills You'll Gain:

• Proficiency in fundamental and advanced data structures.
• Ability to design and analyze efficient algorithms.
• Knowledge of algorithm performance and complexity.
• Experience with practical problem-solving.

Duration:

Typically ranges from 6 to 12 weeks, depending on the course intensity and format.

Certification:

Earn a certificate of completion that can be added to your resume or LinkedIn profile.