TechLearn India/FAANG-Ready: Mastering Data Structures and Algorithms with TechLearn India

  • ₹9,000

FAANG-Ready: Mastering Data Structures and Algorithms with TechLearn India

  • Course
  • 50 Lessons

Dive into the world of Big Tech with our comprehensive course, 'FAANG Ready: Master Data Structures & Algorithms with TechLearn India'.

Gain the essential skills and knowledge needed to crack the FAANG interview process, led by industry experts.

From mastering data structures to tackling complex algorithms, this course equips you with the tools to succeed in the competitive tech landscape.

Contents

Course Outline

Introduction to Data Structures and Algorithms

- Understanding the importance of Data Structures and Algorithms in software development.

- Overview of common data structures (arrays, linked lists, stacks, queues, trees, graphs) and algorithms (searching, sorting, recursion, dynamic programming).


Week 1: Basics of Programming and Problem Solving

- Introduction to programming concepts using a familiar language like Python.

- Solving basic problems involving loops, conditionals, and functions.

- Introduction to problem-solving strategies and techniques.


Week 2: Arrays and Strings

- Understanding arrays and strings, their representation, and manipulation.

- Implementing basic array and string operations.

- Solving problems involving arrays and strings, such as array manipulation, string matching, and substring search.


Week 3: Linked Lists and Stacks

- Introduction to linked lists and stacks, their implementation, and applications.

- Implementing basic operations on linked lists and stacks.

- Solving problems involving linked lists and stacks, such as reversing linked lists, evaluating postfix expressions, and implementing stack-based algorithms.


Week 4: Queues and Recursion

- Understanding queues and recursion, their characteristics, and applications.

- Implementing basic operations on queues and recursive algorithms.

- Solving problems involving queues and recursion, such as implementing queue-based data structures and recursive functions.


Week 5: Trees and Binary Search Trees (BST)

- Introduction to trees and binary trees, their properties, and traversal algorithms.

- Understanding binary search trees (BST) and their operations.

- Implementing basic tree operations and BST algorithms.

- Solving problems involving trees and BST, such as tree traversal, searching, insertion, and deletion.


Week 6: Graphs and Graph Algorithms

- Understanding graphs and their representations.

- Introduction to graph traversal algorithms (BFS, DFS) and their applications.

- Implementing basic graph operations and algorithms.

- Solving problems involving graphs, such as shortest path algorithms, graph traversal, and connectivity.


Week 7: Advanced Data Structures

- Introduction to advanced data structures like heaps, hash tables, and balanced trees.

- Understanding their implementation and applications in solving complex problems.

- Solving advanced problems using these data structures.


Week 8: Dynamic Programming

- Understanding dynamic programming principles and techniques.

- Solving problems using dynamic programming approach.

- Implementing dynamic programming solutions for various problems.


Week 9: Advanced Algorithms

- Introduction to advanced algorithms like greedy algorithms, divide and conquer, and backtracking.

- Understanding their implementation and applications in solving complex problems.

- Solving advanced problems using these algorithms.


Week 10: Problem-Solving Strategies and Practice

- Recap of problem-solving techniques learned throughout the course.

- Practicing problem-solving skills through a series of coding challenges and competitions.

- Reviewing and discussing solutions to common and challenging problems.


Let's Get Started

Week 1: Basics of Programming and Problem Solving

- Introduction to programming concepts using a familiar language like Python.

- Solving basic problems involving loops, conditionals, and functions.

- Introduction to problem-solving strategies and techniques.

Introduction to Data Structures and Algorithms
Week 1: Basics of Programming and Problem Solving
Test Your Knowledge

Week 2: Arrays and Strings

- Understanding arrays and strings, their representation, and manipulation.

- Implementing basic array and string operations.

- Solving problems involving arrays and strings, such as array manipulation, string matching, and substring search.

Understanding arrays and strings, their representation, and manipulation:
Code Examples & Solving problems involving arrays and strings:
Test your Knowledge

Week 2: Additional Topics

1. Common Array and String Operations:

Introduce more operations commonly used with arrays and strings, such as finding the maximum or minimum element in an array, sorting arrays, splitting and joining strings, etc.

2. Complexity Analysis:

Introduce the concept of time complexity and space complexity, and analyze the time and space complexity of various array and string operations. This will help students understand the efficiency of different algorithms and make informed decisions when solving problems.

3. Advanced String Manipulation:

Cover more advanced string manipulation techniques such as regular expressions, formatting strings, string interpolation, and handling unicode characters. These are valuable skills for text processing and data manipulation tasks.

4. Array and String Algorithms:

Introduce common algorithms and techniques used to solve problems involving arrays and strings, such as two-pointer technique, sliding window technique, hashing, and prefix sums. Provide examples and exercises for students to practice implementing these algorithms.

5. String Matching Algorithms:

Cover string matching algorithms such as naive string matching, Knuth-Morris-Pratt (KMP) algorithm, and Boyer-Moore algorithm. These algorithms are used to search for a substring within a larger string efficiently.

6. Practical Applications:

Discuss real-world applications of arrays and strings in software development, such as parsing data from files, processing input from users, implementing data structures like stacks and queues, etc.

Common Array and String Operations:
Complexity Analysis:
Advanced String Manipulation:
Array and String Algorithms:
String Matching Algorithms (Naive String Matching)
Practical Applications:
Test Your knowledge

Week 3: Linked Lists and Stacks

- Introduction to linked lists and stacks, their implementation, and applications.

- Implementing basic operations on linked lists and stacks.

- Solving problems involving linked lists and stacks, such as reversing linked lists, evaluating postfix expressions, and implementing stack-based algorithms.

Introduction to Linked Lists and Stacks:
Implementing Basic Operations on Linked Lists and Stacks:
Solving Problems Involving Linked Lists and Stacks:
Evaluating Postfix Expressions:
Implementing Stack-Based Algorithms:
Test your Knowledge

Week 4: Queues and Recursion

- Understanding queues and recursion, their characteristics, and applications.

- Implementing basic operations on queues and recursive algorithms.

- Solving problems involving queues and recursion, such as implementing queue-based data structures and recursive functions.

Understanding Queues and Recursion:
Implementing Basic Operations on Queues and Recursive Algorithms:
Recursive Algorithms:

Week 5: Trees and Binary Search Trees (BST)

- Introduction to trees and binary trees, their properties, and traversal algorithms.

- Understanding binary search trees (BST) and their operations.

- Implementing basic tree operations and BST algorithms.

- Solving problems involving trees and BST, such as tree traversal, searching, insertion, and deletion.

Introduction to trees and binary trees, their properties, and traversal algorithms.
Understanding Binary Search Trees (BST):
Solving Problems Involving Trees and BST:
Test Your Knowledge

Week 6: Graphs and Graph Algorithms

- Understanding graphs and their representations.

- Introduction to graph traversal algorithms (BFS, DFS) and their applications.

- Implementing basic graph operations and algorithms.

- Solving problems involving graphs, such as shortest path algorithms, graph traversal, and connectivity.

Understanding Graphs and Their Representations:
Introduction to Graph Traversal Algorithms:
Implementing Basic Graph Operations and Algorithms:
Solving Problems Involving Graphs:
Test Your Knowledge

Week 7: Advanced Data Structures

- Introduction to advanced data structures like heaps, hash tables, and balanced trees.

- Understanding their implementation and applications in solving complex problems.

- Solving advanced problems using these data structures.

Heaps
Hash Tables
Balanced Trees
Understanding Implementation and Applications of Advanced Data Structures

Week 8: Dynamic Programming

In this week, we'll explore dynamic programming principles and techniques, solve problems using the dynamic programming approach, and implement dynamic programming solutions for various problems.

- Understanding dynamic programming principles and techniques.

- Solving problems using dynamic programming approach.

- Implementing dynamic programming solutions for various problems.

Understanding Dynamic Programming Principles and Techniques:
Solving Problems Using Dynamic Programming Approach:
Implementing Dynamic Programming Solutions for Various Problems:

Week 9: Advanced Algorithms

In Week 9, we'll delve into advanced algorithms such as greedy algorithms, divide and conquer, and backtracking. Let's explore each of these concepts in detail with code snippets and explanations.

- Introduction to advanced algorithms like greedy algorithms, divide and conquer, and backtracking.

- Understanding their implementation and applications in solving complex problems.

- Solving advanced problems using these algorithms.

Greedy Algorithms:
Divide and Conquer:
Backtracking:
Understanding their implementation and applications in solving complex problems:
Solving advanced problems using these algorithms:

Week 10: Problem-Solving Strategies and Practice

In Week 10, we'll focus on refining problem-solving techniques learned throughout the course, practicing problem-solving skills through coding challenges and competitions, and reviewing solutions to common and challenging problems.

- Recap of problem-solving techniques learned throughout the course.

- Practicing problem-solving skills through a series of coding challenges and competitions.

- Reviewing and discussing solutions to common and challenging problems.

Recap of Problem-Solving Techniques:
Practicing Problem-Solving Skills:
Reviewing and Discussing Solutions:

Algorithmic Proficiency Challenge Test : Mastering Techniques from Week 1 to Week 10

🚀 Welcome to the "Algorithmic Proficiency Challenge: Mastering Techniques from Week 1 to Week 10"! 🌟

This comprehensive quiz is designed to test your proficiency in various problem-solving techniques covered throughout our course.

From fundamental programming concepts to advanced algorithms, this quiz will challenge your understanding and application of topics spanning from basic loops and conditionals to dynamic programming, graph algorithms, and more.

Sharpen your problem-solving skills and put your knowledge to the test with this comprehensive assessment covering a wide range of algorithmic concepts. Are you ready to take on the challenge and demonstrate your mastery of algorithmic problem-solving?

Let's get started! 🎯

Final Test your Knowledge
FAANG Algorithmic Coding Exam
FAANG Algorithmic coding Answer Key.pdf