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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.

1 course38 lessons~20 hrNo sign-up needed
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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
Start the first lesson
  1. 1

    Getting Started with Code

    Beginner4 lessons

    Your first program, the types your data lives in, the operators that combine it, and the branching that makes it decide.

  2. 2

    Loops and Pattern Printing

    Beginner2 lessons

    Repetition, dry running with trace tables as a graded skill, and the i-j reasoning gymnasium that everything later depends on.

  3. 3

    Functions and Data Containers

    Beginner5 lessons

    Naming and reusing code, then the containers you will spend the rest of the course filling: arrays, strings, matrices and the standard library.

  4. 4

    Complexity and Math

    Beginner2 lessons

    How to count what your code costs before you run it, and the number theory that shows up in interview problems.

  5. 5

    Recursion and Bits

    Intermediate2 lessons

    The call stack drawn out frame by frame, and the bit operations that turn arithmetic tricks into one-liners.

  6. 6

    Sorting and Searching

    Intermediate4 lessons

    Four algorithms built from scratch and compared honestly on stability, adaptivity and cost - not on reputation.

  7. 7

    Array and String Patterns

    Intermediate4 lessons

    The named patterns interviewers actually test, and the recognition skill that lets you name the right one from the problem statement.

  8. 8

    Linear Data Structures

    Intermediate3 lessons

    Pointer rewiring, the monotonic stack that collapses a quadratic scan to linear, and the queues behind sliding windows and BFS.

  9. 9

    Trees, Heaps and Tries

    Advanced4 lessons

    Non-linear structures: traversals as one recursion with the visit moved, the BST property, the heap array trick, and prefix trees.

  10. 10

    Graphs and Algorithmic Techniques

    Advanced5 lessons

    Traversal on graphs and grids, then the four techniques that solve most hard problems: backtracking, dynamic programming, greedy and the advanced structures.

  11. 11

    Interview Preparation

    Advanced3 lessons

    Core CS revision, the six-step method run end to end on a real problem, and what each company track actually tests.