Learn it properly, then prove it.
Full courses taught idea first, then traced by hand, then coded — with a step-through simulator in almost every lesson that you drive yourself. No account, no payment, no autoplay.
DSA: Zero to Placement Ready
A complete Data Structures and Algorithms track for engineering students, assuming no prior coding at all. It starts at writing your first program and ends at defending your approach in an interview. Every topic is taught idea first, then traced by hand on a small example, then coded naive and optimised, and closes with the interview questions and practice problems that topic actually attracts.
- 11
- Modules
- 38
- Lessons
- ~20 hr
- Material
- 1
Getting Started with Code
Beginner4 lessonsYour first program, the types your data lives in, the operators that combine it, and the branching that makes it decide.
- 2
Loops and Pattern Printing
Beginner2 lessonsRepetition, dry running with trace tables as a graded skill, and the i-j reasoning gymnasium that everything later depends on.
- 3
Functions and Data Containers
Beginner5 lessonsNaming and reusing code, then the containers you will spend the rest of the course filling: arrays, strings, matrices and the standard library.
- 4
Complexity and Math
Beginner2 lessonsHow to count what your code costs before you run it, and the number theory that shows up in interview problems.
- 5
Recursion and Bits
Intermediate2 lessonsThe call stack drawn out frame by frame, and the bit operations that turn arithmetic tricks into one-liners.
- 6
Sorting and Searching
Intermediate4 lessonsFour algorithms built from scratch and compared honestly on stability, adaptivity and cost - not on reputation.
- 7
Array and String Patterns
Intermediate4 lessonsThe named patterns interviewers actually test, and the recognition skill that lets you name the right one from the problem statement.
- 8
Linear Data Structures
Intermediate3 lessonsPointer rewiring, the monotonic stack that collapses a quadratic scan to linear, and the queues behind sliding windows and BFS.
- 9
Trees, Heaps and Tries
Advanced4 lessonsNon-linear structures: traversals as one recursion with the visit moved, the BST property, the heap array trick, and prefix trees.
- 10
Graphs and Algorithmic Techniques
Advanced5 lessonsTraversal on graphs and grids, then the four techniques that solve most hard problems: backtracking, dynamic programming, greedy and the advanced structures.
- 11
Interview Preparation
Advanced3 lessonsCore CS revision, the six-step method run end to end on a real problem, and what each company track actually tests.