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Data Structures & Algorithms with Python

  • Ace the coding interviews of top tech companies.
  • Gamified Experience to understand Data Structures/Algorithms.
  • Break complex coding problems into simpler tasks and solve them using the correct Data Structures/Algorithms.
  • Compare the complexities of various algorithms and employ the most optimal one.
  • Learn to implement algorithms with 200+ programming challenges and puzzles.
Data Structures & Algorithms with Python

200+ Problems

Concepts and Interview Questions

3 Months

Learn at your own pace

70+ Hours

High-quality lectures with code-along videos

Data Structures & Algorithms with Python

This extensive hands-on course takes you from the fundamentals of Data Structures and Algorithms to an advanced level in weeks. It contains 12 modules and covers a wide range of topics in data structures and algorithms such as Object-Oriented Programming, Searching and Sorting Algorithms, Greedy Algorithms, and Dynamic Programming. At the end of each module, you will apply the skills learned during the course to solve real-world programming problems quickly. This course also contains solutions to the interview questions from top companies with code-along explanations to give the learners a competitive advantage. This course is designed for all stages of learning, whether you are a complete beginner or from a non-tech background.

  • Self-paced Training

  • 200+ Problems

  • 70+ Hours of video content

  • 80+ Assignments

  • Interactive games

  • Beginner Friendly

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Sample Certification
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Why this Course?


The more diverse the role, the greater is the monetary variation. According to Indeed, entry-level Software Engineers earn up to $92,824 per year, while experienced Software Engineers earn up to $107,510.

Job Aspects

DSA is of prime importance and is one of the top skills when it comes to software engineering that results in impactful career transition. Another example of application of DSA is AI algorithms. AI Scientists use advanced Data Structures and Algorithms to solve complex mathematical problems.

Importance of DSA

Data Structures and Algorithms are at the core of any computer science application. DSA is used to solve real-world problems, and when paired with machine learning algorithms, DSA can be very useful; a great example is Google ranking systems. Learning and exploring DSA helps you to think and come up with the best possible solutions.

Why AI Probably?

Gamified Experience

Gamified approach for understanding of concepts and memory retention based on Cognitive Neuroscience.

Solved Interview Problems

Contains solved interview questions from top companies with an in-depth explanation.

State-of-the-Art LMS

A modular LMS designed with an easy-to-navigate user interface.

Taught by Industry Experts

Get on-demand video lectures and learn from renowned industry experts.

Number of hours

Get more than 70+ hours of explicit content in the form of lectures and code-along videos.

24 x 7 Learning Support

Get learning support at any point of time during your enrolment in the course.


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Learning Objectives

Gives the potential of Python Programming Language and introduces different Python data types such as Strings, Loops, conditional structures, and so on.


  • Data Types & Data Structures
  • Conditional Structures
  • Loops
  • Strings
  • Functions

Learning Objectives

Learn about various programming styles and get to know about the four pillars of Object-Oriented Programming.


  • Inheritance
  • Polymorphism
  • Encapsulation
  • Abstraction

Learning Objectives

Work with the basic Data Structures of Python and implement Sorting Algorithms by utilizing them.


  • Lists
  • Sets
  • Arrays
  • Bubble Sort
  • Selection Sort
  • Insertion Sort
  • Quick Sort
  • Merge Sort

Learning Objectives

Learn about Asymptotic Analysis, the Notations and calculate the time complexities of various algorithms


  • Big-O Notation
  • Omega-Ω Notation
  • Theta-ϴ Notation
  • Comparison of Algorithms
  • Complexity Calculation

Learning Objectives

Understand the properties and working of Linked Lists, differentiate between Linked Lists and Arrays, and visualize various types of Linked Lists


  • Working of Linked Lists
  • Singular Linked Lists
  • Doubly Linked Lists
  • Circular Linked Lists
  • Skip Lists

Learning Objectives

Comprehend Recursion and Backtracking, and distinguish between Recursion and Iteration


  • Recursive Functions
  • Recursion vs. Iteration
  • Backtracking Examples
  • Applications

Learning Objectives

Illustrate how operations on Stack and Queues are performed and explore different types of Queues.


  • Working of Stacks & Queues
  • Types of Queues
  • Implementation
  • Applications

Learning Objectives

Implement Hash Tables for relevant problems and analyze Hash Functions to detect and prevent collisions (Direct Chaining and Double Hashing)


  • Hashing Operations
  • Hash Tables
  • Hash Functions
  • Hashing Techniques
  • Collision Detection & Handling
  • Applications

Learning Objectives

Implement nonlinear data structures such as Trees, Heaps, Graphs, and Tries and study their operations and traversal techniques.


  • Types of Trees
  • Tree Traversals - Inorder, Postorder, and Preorder
  • Tries
  • Heaps
  • Graphs
  • BFS vs. DFS
  • Shortest Path Algorithm
  • Applications

Learning Objectives

Code various Searching algorithms, compare time complexities, and learn about Advanced String Manipulation.


  • Linear Search
  • Binary Search
  • Interpolation Search
  • String Manipulation
  • Rabin-Karp Algorithm

Learning Objectives

Compare the two most prominent algorithmic strategies to find an optimized solution to the given problem.


  • Greedy Approach
  • Dynamic Programming
  • Top-down vs. Bottom-up Strategy
  • Popular Algorithms & Problems

Learning Objectives

Compare between Threads and Processes and implement Multithreading in your code using the threading module in Python.


  • Threads & Multithreading
  • Synchronization
  • Locks
  • The Ray Framework
  • Async I/O in Python

Tools and
Technologies covered

Frequently Asked Questions

Learning and exploring DSA helps to think out of the box and develop optimal solutions. Companies like Google, Facebook, or Microsoft want engineers who can create unique algorithms to solve highly complex issues they face.

All you need is a stable internet connection and a laptop to stream the video classes. The course starts with the most basic concepts of Python and DSA.

Your system should have a minimum of 4 GB RAM. You can also run your programs in Google Colab Notebook.

You will be able to use the correct algorithms and data structures in your daily work and develop programs of a faster magnitude. You will be able to solve programming challenges like those seen in Google, Facebook, Microsoft, Yandex, and the questions asked in the technical interviews of Fortune 500 companies.

Yes, the course has a curated list of more than 200+ questions solved by the industry experts with in-depth code-along explanations.

Whether you are a student or a professional, the knowledge you gain from the course will open a bundle of opportunities, in terms of job and amazing problem-solving skills.

Our payment gateway supports a wide array of payment options. You can use any online mode viz. Netbanking, Credit Card, Debit Card, UPI, or Wallets.

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