Data Structure and Algorithm

Online | Self-paced | Start Anytime
Intermediate
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About the Course

This course covers essential data structures and algorithms in Python, emphasizing their importance in writing efficient code. Participants will gain hands-on experience through practical projects, enhancing their problem-solving skills and understanding of algorithmic principles.

Curriculum

  • Module 1: Introduction to Data Structures and Algorithms

    Overview:

    Establishes the foundational concepts of data structures and algorithms, including their significance in programming.

    Topics to Cover:

    • Time and space complexity (Big O notation)
    • Introduction to algorithm analysis

  • Module 2: Arrays and Lists

    Overview:

    Explores the fundamental building blocks of data structures, focusing on arrays and lists.

    Topics to Cover:

    • Dynamic arrays
    • Linked lists (singly, doubly, circular)

  • Module 3: Stacks and Queues

    Overview:

    Introduces linear data structures with real-world applications.

    Topics to Cover:

    • Stack operations (push, pop)
    • Queue operations (enqueue, dequeue)

  • Module 4: Hashing and Hash Tables

    Overview:

    Covers hashing techniques and the implementation of hash tables for fast lookups.

    Topics to Cover:

    • Hash functions
    • Collision handling (chaining, open addressing)

  • Module 5: Recursion

    Overview:

    Explains the concept of recursion and its applications in solving problems.

    Topics to Cover:

    • Base case and recursive case
    • Recursion vs. iteration
    • Recursion depth

  • Module 6: Searching Algorithms

    Overview:

    Examines various searching techniques crucial for efficient data retrieval.

    Topics to Cover:

    • Linear search
    • Binary search
    • Search trees (BST)

  • Module 7: Sorting Algorithms

    Overview:

    Focuses on fundamental sorting techniques used in computer science.

    Topics to Cover:

    • Bubble sort, selection sort, insertion sort
    • Merge sort, quicksort

  • Module 8: Trees and Binary Trees

    Overview:

    Introduces tree data structures and their significance in organizing data hierarchically.

    Topics to Cover:

    • Binary trees and binary search trees
    • Tree traversals (inorder, preorder, postorder)

  • Module 9: Heaps and Priority Queues

    Overview:

    Covers the implementation of heaps and their applications in priority queues.

    Topics to Cover:

    • Min-heap and max-heap
    • Heapify process

  • Module 10: Graphs and Graph Algorithms

    Overview:

    Explores graph data structures and their applications in various real-world problems.

    Topics to Cover:

    • Graph representations (adjacency matrix, adjacency list)
    • Depth-first search (DFS) and breadth-first search (BFS)
    • Dijkstra’s algorithm

  • Module 11: Dynamic Programming

    Overview:

    Introduces dynamic programming techniques for solving complex problems.

    Topics to Cover:

    • Memoization and tabulation
    • Overlapping subproblems

  • Module 12: Greedy Algorithms

    Overview:

    Discusses greedy algorithms and their applications in optimization problems.

    Topics to Cover:

    • Greedy choice property
    • Huffman coding
    • Activity selection problem

  • Module 13: Backtracking

    Overview:

    Explains the backtracking technique for solving combinatorial problems.

    Topics to Cover:

    • Constraint satisfaction problems
    • N-Queens problem
    • Sudoku solver

  • Module 14: Advanced Data Structures

    Overview:

    Covers advanced data structures for specialized use cases.

    Topics to Cover:

    • Tries for efficient searching
    • AVL trees and Red-Black trees for self-balancing
    • B-Trees for database indexing

  • Module 15: Network Flow and Matching Algorithms

    Overview:

    Introduces advanced concepts in graph theory related to network flow.

    Topics to Cover:

    • Ford-Fulkerson algorithm
    • Maximum bipartite matching

Learning Outcomes

By the end of this course, participants will be able to:

  • Understand and analyze the efficiency of various data structures and algorithms.
  • Implement and manipulate arrays, lists, stacks, queues, and hash tables in Python.
  • Solve complex problems using recursion, searching, and sorting algorithms.
  • Utilize trees, heaps, and graphs to structure data effectively.
  • Apply dynamic programming and greedy algorithms to optimize solutions.
  • Design and implement advanced data structures for specialized applications.

Tools

Python
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FAQ

Frequently asked questions about the bootcamp

The course is structured into weekly modules, each containing video lectures, reading materials, assignments, and quizzes. You can complete the modules at your own pace, but we recommend following the weekly schedule to stay on track.

You can get support in multiple ways:

  • TA Support on Slack: Our teaching assistants are available on Slack to answer your questions and provide guidance.
  • Peer Community on Discord: Join our Discord community to discuss course topics, share ideas, and collaborate with fellow students.

TAs are available on Slack from 9 AM to 6 PM (ET) Monday to Friday. Outside these hours, you can still post your questions, and TAs will respond as soon as they are back online.

After enrolling in the course, you will receive an invitation link to join the Discord community. Follow the link to create an account or log in to your existing account.

The Discord community offers peer-to-peer support, where you can discuss course topics, share resources, collaborate on projects, and network with fellow learners

The optional mentoring service includes one-on-one sessions with an experienced mentor who can provide personalized guidance, feedback on your progress, and help you set and achieve your learning goals.

Please talk to our Program Advisors to sign up for Mentorship services for an additional cost

Yes, you will have lifetime access to the course materials, including any updates made to the content in the future.

We accept all major credit cards, PayPal, and bank transfers. You can choose your preferred payment method at checkout

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