DSA with Python
Start with Python fundamentals and then master data structures and algorithms for interview-level problem solving.
7 Weeks
Duration
Beginner+
Level
Live
Sessions
Live Cohort
DSA with Python
₹4,00038% OFF
₹2,499Enroll Now
Course Overview
Everything you will learn and accomplish in a structured 7-week programme.
What You'll Learn
- Python fundamentals and programming patterns
- Searching and sorting problem-solving techniques
- Linked Lists, Stacks, Queues, Trees, and Graphs
- Recursion, Greedy, Backtracking, and Dynamic Programming
- Interview-focused DSA practice strategy
What You'll Achieve
- Strong Python + DSA foundation for coding rounds
- Confidence to solve interview-level algorithmic questions
- Structured roadmap for 150+ practice problems
- Clear preparation strategy for technical interviews
Why choose this track?
Build Python confidence first, then crack DSA systematically.
Continuous Assignments
Doubt clearing sessions
Mock interviews
LeetCode-style problem solving
Course Curriculum
Week 1-2 cover Python foundations, followed by week 3-7 DSA interview prep.
- Introduction to Python and IDE setup
- Basic syntax, indentation, data types, and operators
- Internal working of Python and memory management
- Input/output operations
- Conditional statements (if, elif, else)
- Loops (for, while), break and continue
- Nested loops and conditions
- String manipulation and methods
- Lists, Tuples, Dictionaries, and Sets
- List and Dictionary comprehensions
- Shallow copy and deep copy
- Function definition, parameters, and return values
- Recursive and lambda functions
- Iterators, Generators, Decorators, and modules
- Linear Search & Binary Search
- First & last occurrence, floor/ceil, peak element
- Search in a row-column-wise sorted array
- Bubble Sort, Selection Sort, Insertion Sort
- Merge Sort & Quick Sort (Lomuto & Hoare's partition)
- Intersection & union of sorted arrays
- Matrix operations — snake pattern, spiral traversal, rotation
- Linked List — middle node, nth node, reverse, loop detection
- Slow & Fast pointer technique
- Stack — balanced parentheses, infix/postfix, two-stack array
- Queue — array & linked list implementation
- Implement stack using queue & vice versa
- Deque — implementation & max of subarrays of size K
- Recursion — factorial, fibonacci, subsequences, array max
- Hashing — subset check, disjoint arrays, zero-sum subarray
- Tree traversal (inorder, preorder, postorder, level order)
- Height, maximum, left view & spiral form of binary tree
- BST — min value, height, mirror, equality check
- Lowest Common Ancestor
- Heap implementation & heap sort
- Kth largest / smallest / closest element
- Merge K sorted arrays
- Graph representation — directed vs undirected
- BFS & DFS traversal
- Number of islands & shortest path (unweighted)
- Greedy — activity selection, fractional knapsack, job sequencing
- Backtracking — rat in a maze, N-Queens, Sudoku
- DP — memoization vs tabulation
- 0-1 Knapsack & its variations
- Longest Common Subsequence & variations
- Mock interview practice & problem-solving strategy
- 🚀 LeetCode Top Interview 150 guided practice