Free lesson · DSA Mastery - Interview Prep, End to End

Course Roadmap

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Course Roadmap

Welcome to DSA Mastery. Before you dive in, take a few minutes to understand what is ahead of you. This course is large - over 600 topics across 32 sections - and how you move through it should depend on where you are starting from and what kind of interview you are preparing for.

This page is your map. It tells you what is in the course, how the sections relate to each other, what order to take them in (and when to skip), and roughly how long the whole thing takes. If you read nothing else before starting, read this.

What This Course Covers

DSA Mastery is a comprehensive interview-preparation course covering data structures, algorithms, and the problem-solving patterns that show up in technical interviews at FAANG-tier companies. The content is built around three layers.

The foundations layer covers how interviews work, how to think about algorithm efficiency (Big O), and language-specific setup for whatever language you are coding in. Sections 1 through 4.

The patterns layer covers the core problem-solving techniques: sorting, arrays, strings, hash tables, two pointers, sliding window, recursion, binary search, trees, graphs, dynamic programming, and more. This is the bulk of the course - Sections 5 through 30 - and it is what most interview problems reduce to once you know how to recognize them.

The advanced layer covers senior-level material: data structure design problems, advanced math and geometry, string-matching algorithms, line sweep, and other techniques that show up in harder interviews. Sections 31 and 32.

You do not need to read every section to be interview-ready. You probably should not. The course is designed to be both a learning path for new interview-preppers and a reference library for engineers who want to brush up on specific topics. Use it however serves you best.

How the Sections Connect

The sections are listed in a sensible learning order, but they are not strictly linear. Some sections depend on earlier ones; others stand alone. Here is the rough dependency graph.

graph TD
    A["Foundations<br/>Sections 1-4"] --> B["Core Data Structures<br/>Sections 5-8"]
    B --> C["Pattern-Based Sections<br/>Sections 9-14"]
    C --> D["Linked Structures<br/>Sections 15-17"]
    D --> E["Recursion Foundation<br/>Sections 19-20"]
    E --> F["Trees<br/>Sections 22-24"]
    F --> G["Heaps and Intervals<br/>Sections 25-26"]
    C --> H["Search Patterns<br/>Section 21"]
    G --> I["Design Problems<br/>Section 27"]
    E --> J["Greedy<br/>Section 28"]
    F --> K["Graphs<br/>Section 29"]
    K --> L["Dynamic Programming<br/>Section 30"]
    L --> M["Advanced Topics<br/>Sections 31-32"]
    
    style A fill:#4338ca,stroke:#6366f1,color:#f1f5f9
    style B fill:#4338ca,stroke:#6366f1,color:#f1f5f9
    style C fill:#4338ca,stroke:#6366f1,color:#f1f5f9
    style D fill:#4338ca,stroke:#6366f1,color:#f1f5f9
    style E fill:#b45309,stroke:#f59e0b,color:#f1f5f9
    style F fill:#b45309,stroke:#f59e0b,color:#f1f5f9
    style G fill:#b45309,stroke:#f59e0b,color:#f1f5f9
    style H fill:#4338ca,stroke:#6366f1,color:#f1f5f9
    style I fill:#b45309,stroke:#f59e0b,color:#f1f5f9
    style J fill:#b45309,stroke:#f59e0b,color:#f1f5f9
    style K fill:#dc2626,stroke:#ef4444,color:#f1f5f9
    style L fill:#dc2626,stroke:#ef4444,color:#f1f5f9
    style M fill:#16a34a,stroke:#10b981,color:#f1f5f9

This diagram shows how the course sections build on each other. Foundations come first, leading into core data structures and pattern-based sections. These feed into linked structures, recursion, trees, heaps, and intervals. Search patterns and design problems are mostly independent branches. Graphs and dynamic programming are the deepest sections and depend on most of what came before. Advanced topics close out the course.

The blue sections are foundational and build sequentially. The amber sections are pattern-heavy and assume you have the basics down. The red sections are the deep ones - Graphs and DP - which are the largest and assume comfort with recursion, trees, and most earlier patterns. The green section at the bottom is the closing advanced material.

If you are absolutely new to interview prep, work through the sections roughly in order. If you have prepped before and just want to fill gaps, jump to whichever section addresses what you are weak on.

Suggested Learning Paths

Different people come to this course at different stages of interview prep. Here are three paths that fit common situations.

The Three-Month Comprehensive Path

You have three months until your first interview and want to cover everything important. This is the most thorough path.

• Month 1: Sections 1-12. Foundations through Sliding Window. This builds the core vocabulary and the most-tested patterns.
• Month 2: Sections 13-22. Through Binary Tree. This adds the linked-structure and recursion-heavy material, plus the full tree coverage.
• Month 3: Sections 23-30. BST through Dynamic Programming. This is the heaviest stretch, but by this point you have the foundation to absorb it.

The advanced sections (31-32) and the deeper graph/DP topics in 29-30 are optional unless you are targeting senior or staff-level interviews.

The Six-Week Targeted Path

You have six weeks and want to cover the highest-leverage material without trying to be comprehensive.

• Weeks 1-2: Sections 3-4 (Big O, Programming Fundamentals), then Sections 6 and 9 (Arrays, Hash Tables). These three topic areas account for roughly half of all interview problems.
• Weeks 3-4: Sections 10-12 (Two Pointers, Prefix Sum, Sliding Window) and Section 19 (Recursion & Backtracking). The pattern recognizers.
• Weeks 5-6: Section 21 (Binary Search), Section 22 (Binary Tree), and the first half of Section 29 (Graphs - DFS and BFS). The big three "structures" interview problems test.

Skip everything else for now. Come back to it after the first round of interviews.

The Refresher Path

You know this material already and just want to brush up before an upcoming interview. Skim the introduction of each section to remind yourself of the patterns, then drill 5-10 problems per section in the areas you are rustiest. Time required: 1-2 weeks of evenings, depending on how rusty you are.

This is also a good way to use the course as a long-term reference library - bookmark sections you find yourself returning to.

Section Reference

Here is the full list of sections so you know what is available. Each section is independently linkable from the course sidebar.

Roughly 600 topics total. At a sustained pace of one topic per hour of focused study, the full course is 600 hours - about 6 months of evenings, or 3-4 months of full-time study. Most learners do not work through every topic in detail; they focus on the patterns most relevant to their target role and skim or skip the rest.

How to Use This Course

A few suggestions for getting the most out of it.

Code along, do not just read. Every algorithm topic includes a Java implementation. Open your editor, type it out, and run it against the example input. Reading is faster, but doing produces deeper understanding. If you only have time for one of those, do.

Trace the examples by hand. Every algorithm topic has a step-by-step walkthrough showing what happens on a real input. Pause before reading the walkthrough and try to predict what each step will produce. When your prediction does not match, that is where the learning happens.

Do not skip the complexity analysis. Knowing that something is O(n log n) is not enough - you should be able to explain why. The complexity sections walk through the reasoning. Interviewers will ask you to defend your complexity claims, and the explanation is often more important than the number itself.

Use the patterns. Practice the problems. This course is structured around patterns precisely because interview problems cluster into a small number of repeated patterns. Once you recognize the pattern, the solution often falls out. Each pattern section has many practice problems - work through enough of them that the pattern becomes automatic before moving on.

Come back. Most people do not retain everything on the first pass. That is fine. The course is built to be revisited. Bookmark the topics you find hardest and return to them after a week or two - you will be surprised how much settles in once you have seen related material.

Welcome aboard. Section 2 covers how technical interviews actually work, which is worth reading before you dive into the algorithm material. After that, the rest of the course is yours to navigate.

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