Data Structures & Algorithms in Python: DSA Course

Overview

Data structures and algorithms are the language of technical interviews—and the reason many self-taught developers stall when problems stop being step-by-step tutorials. This course uses Python because interviewers expect it, your syntax stays readable under pressure, and you can focus on thinking instead of fighting semicolons.\n\nWe do not treat DSA as a memorization sport. Each structure—lists, stacks, queues, hash maps, trees, graphs—is introduced with a concrete use case: why would a browser back button use a stack? Why does deduplication lean on a set or hash map? Once the why is clear, you implement and trace operations by hand before optimizing.\n\nAlgorithm patterns follow the same philosophy. Sorting and searching are not trivia; they teach you how to compare trade-offs in time and space. You practice translating vague problem statements into clear steps, then into working code you can explain aloud—exactly what a whiteboard or live coding round demands. By the end, LeetCode-style prompts feel like variations on patterns you have already internalized, not random puzzles.

What you will learn

• Implement core structures: arrays, linked lists, stacks, queues, hash maps, trees, and graphs in Python
• Choose the right structure for a problem based on access patterns and constraints
• Apply sorting and searching algorithms and articulate when each is appropriate
• Analyze time and space complexity with Big-O intuition for interview discussions
• Recognize patterns: two pointers, sliding window, BFS/DFS, and divide-and-conquer
• Walk through code out loud—the habit interviewers actually score
• Debug logical errors in recursive and iterative solutions systematically
• Build a reusable mental checklist for unseen problem statements

Syllabus outline

1. Module 1: Complexity and Python Collections — Big-O basics and when built-ins already solve the problem
2. Module 2: Linear Structures — arrays, linked lists, stacks, and queues with interview classics
3. Module 3: Hashing and Sets — O(1) lookups, collision intuition, and frequency-count patterns
4. Module 4: Trees and Traversals — BST concepts, DFS, BFS, and recursion vs iteration
5. Module 5: Graphs — adjacency models, shortest-path intuition, and grid-as-graph problems
6. Module 6: Sorting and Searching — implementations, stability, and trade-off analysis
7. Module 7: Pattern Drills — mixed sets that mirror real interview difficulty curves

Who this course is for

Developers preparing for coding interviews at product companies or service firms, computer science students who want implementation practice beyond theory lectures, and self-taught programmers who can build apps but freeze on algorithmic questions. Python users moving from tutorials to problem-solving will feel at home immediately.

Prerequisites

You should know Python variables, loops, functions, and basic lists. No formal computer science background is required, but willingness to think on paper before coding is essential.

How to study this course

Alternate watching with pencil work: draw the structure before you code it. After each module, solve two problems without looking at notes—one easy, one medium. Timebox to twenty-five minutes; if stuck, study the solution, then rewrite from scratch the next day. Keep a error log: wrong pointer move, off-by-one, missed base case. Review that log weekly. Interview prep rewards consistency over cramming; thirty minutes daily beats a single eight-hour binge before an onsite.

Why this guide exists on the site

The course videos demonstrate solutions; this guide maps the full arc—structures, patterns, and study rhythm—so you know which week to spend on trees versus graphs. Use it as your syllabus between practice sessions instead of guessing what topic to pick next on a problem site. That clarity turns random grinding into deliberate preparation.

How enrollment works

Sharad Khare hosts structured video lessons on Udemy for convenient playback, progress tracking, and certificates. Use the button above to open the official course page. Pricing and promotions are set by Udemy. Pair lessons with free note packs on the Notes page and related reading in Articles.