Version: 13.0 (Professional Edition, Complete Syllabus)
Status: ✅ Complete, MIT-Level Depth, v13 Comprehensive Syllabus-Aligned
License: 📜 MIT (Free for learning and teaching)
This is a comprehensive, narrative-driven Data Structures and Algorithms curriculum designed to transform you from foundational understanding (RAM model, Big-O, recursion) to mastery (advanced patterns, systems design, production-grade code, interview readiness) over 19 weeks.
It preserves the structure, tone, and visual style of professional DSA education, while delivering the complete phase, week, and day-by-day syllabus aligned with COMPLETE_SYLLABUS_v13.md (v13.0).
- 🎓 Mental Models First — Understand why before how. Systems-level thinking precedes code.
- 📖 Narrative-Driven — Reads like MIT lecture notes from a master teacher, not a reference manual checklist.
- ⚙️ Systems-Grounded — Every concept connects to real production systems (Linux kernel, PostgreSQL, Redis, Netflix engineering).
- 🎨 Pattern-Centric — 180+ topics organized as learnable, reusable patterns across interview problems.
- 🎯 Interview-Ready — ~98% coverage of real FAANG-style technical interview question patterns.
- 💻 Production-Grade Code — C# implementations with professional quality, not LeetCode spaghetti.
- 🌐 Visual + Interactive — 30+ ASCII diagrams per week + dedicated visual playbooks and external visualization tools.
- Grind 100–500 LeetCode problems
- Study algorithms in isolation, disconnected from systems
- Learn code templates without understanding invariants or trade-offs
- Hope interview questions match what you practiced
- Fight against forgetting (high cognitive load, low retention)
- Build mental models of how data structures live in memory
- Understand why some algorithms are faster (cache behavior, locality, CPU physics)
- Learn patterns that appear across 100+ problems (two-pointer, window, DP families, graph templates)
- See real systems (Linux, PostgreSQL, Redis, search engines) using these ideas
- Walk into interviews confident you can solve new variants, not just memorize old ones
- Retain knowledge via narrative flow, spaced repetition, and multi-angle explanations
-
🖥️ Hardware Intuition
Understand cache lines, virtual memory, TLB, page faults, pointer chasing, CPU pipelines, SIMD. Know why contiguous arrays often beat pointer-heavy structures. -
📊 Complexity Mastery
Analyze time and space complexity, prove bounds with recurrences, recognize amortized behavior, and know when Big-O hides important constants. -
🔍 Pattern Recognition
Spot the same algorithmic ideas across many problems: two-pointer, sliding windows, monotonic stack, BFS/DFS, subset DP, flows, etc. -
⚖️ Trade-off Thinking
Choose between arrays vs linked lists, hash tables vs balanced trees, heap vs sort, greedy vs DP, recursion vs iteration. Explain trade-offs clearly. -
🏭 Systems Perspective
Connect DSA to real production engineering: indexes in databases, schedulers, caches, graph engines, search, load balancing, etc.
- 🎓 CS Students: Campus placements, internships, strong foundations
- 🏫 Bootcamp Graduates: First-principles DSA after intense coding practice
- 🤖 Self-Taught Developers: Structured, end-to-end FAANG-style interview prep
- 💼 Working Professionals: 2–8+ years experience aiming for senior/staff roles
- 🎯 Interview Candidates: Targeting Google, Amazon, Meta, Microsoft, Apple, Netflix, and top product companies
- ✅ Basic programming in any language (C, C++, Python, Java, C#, Go, TypeScript, etc.)
- ✅ Understanding of arrays, loops, functions, basic OOP
- ✅ Willingness to commit 10–15 hours/week for 19 weeks (or more for acceleration)
- ✅ Curiosity about how things actually work under the hood
| Path | Duration | Hours/Week | Best For |
|---|---|---|---|
| Complete Mastery | 16–20 weeks | 10–15 | Deep understanding, elite readiness |
| Interview Acceleration | 6–8 weeks | 20–30 | Working professionals, tight deadlines |
| Quick Reference | 2–4 weeks | Flexible | Last-mile prep, topic refresh |
| Phase | Weeks | Focus | Topics | Interview Coverage | Goal |
|---|---|---|---|---|---|
| 🟦 A: Foundations | 1–3 | RAM model, Big-O, Recursion, Linear DS, Sorting, Hashing | 15+ core | 25–30% | Foundation Set |
| 🟩 B: Core Patterns | 4–6 | Two-Pointer, Sliding Window, Hash/Stack/Intervals, Strings | 15+ core | 70–80% | Strong Base |
| 🟨 C: Trees, Graphs & DP | 7–11 | Trees, BSTs, Graphs, Shortest Paths, DP I–II | 25+ core | 80–88% | Competent |
| 🟧 D: Paradigms | 12–13 | Greedy, Algorithm Paradigms, Amortized Analysis | 10+ core | 85–90% | Proficient |
| 🟪 E: Integration & Extensions | 14–15 | Matrix problems, Backtracking, Bits, Advanced Strings & Flow | 15+ core | 90–95% | Advanced |
| 🟫 F: Deep Dives (Optional) | 16–18 | Segment Trees, BIT, Geometry, HLD, FFT, Probabilistic DS | 15+ advanced | 95%+ | Elite |
| 🔴 G: Mock Interviews | 19 | Full Mock Interviews, Weak Points, Final Prep | Integration | 98% | Interview Ready |
Goal: Deep understanding, systems-aware, production-ready, interview-ready
Best For: Students, career changers, lifelong learners, elite preparation
Week 1–3 : Build foundations (RAM model, Big-O, recursion, space)
Week 4–6 : Master core patterns (arrays & strings)
Week 7–11: Trees, graphs, DP I–II (classic CS core)
Week 12–13: Paradigms (greedy, algorithm paradigms, amortized analysis)
Week 14–15: Integration (matrix problems, backtracking, bits, advanced strings, intro to flow)
Week 16–18: Optional deep dives (segment trees, BIT, geometry, HLD, FFT, probabilistic DS)
Week 19 : Mock interviews & integration
Expected Outcomes:
- ✅ Understand core algorithms from first principles
- ✅ Solve 90%+ of common coding interview problems
- ✅ Write production-quality C# implementations
- ✅ Explain trade-offs and systems implications
Goal: Solve 85%+ of interview problems, with strong pattern recognition
Best For: Working professionals with limited time
Pre-Week: 2–3 hour crash review of Weeks 1–3 (summaries + visuals)
Week 1 : Weeks 4–5 (Two-pointer, windows, Tier 1 critical patterns)
Week 2 : Week 6 (strings) + core of Week 7 (tree basics)
Week 3 : Weeks 8–9 (graph fundamentals, shortest paths, MST)
Week 4 : Weeks 10–11 (DP fundamentals + trees/DAGs)
Week 5 : Weeks 12–13 (greedy, algorithm paradigms, amortized)
Week 6–8: Week 19-style mocks + focused gap-filling using Summaries & QA
Expected Outcomes:
- ✅ Strong pattern classification across 100+ patterns
- ✅ Ability to solve most medium/hard interview problems
- ✅ Clear, structured communication during interviews
Goal: Targeted refresh and gap-filling before interviews
Best For: Experienced developers who need structured revision
Need trees/graphs? → Week 7–9 Summaries + Roadmaps + Interview_QA
Weak on DP? → Week 10–11 + Week 15 Summaries + Visual Playbooks
String algorithms? → Week 6 + Week 15
Greedy/amortized? → Week 12–13
Flows/advanced DS? → Weeks 16–18 overview
Benefits:
- ✅ No wasted time on topics you already know
- ✅ Fast "map" of what to review for a given role
Every week follows a consistent file structure so you always know where to go.
Purpose: 🏫 Deep learning in narrative form (MIT-style lectures). Build COnceptual understanding.
Structure (5-Chapter Arc):
- 🎣 Context & Motivation
- 🧠 Mental Model
- ⚙️ Mechanics & Implementation
- 🏭 Performance & Real Systems
- 🎓 Integration & Mastery
Use When: You need to truly understand a concept, not just memorize patterns
Purpose: 🖼️ Offline visual learning + enhanced with external references. Leran concepts visually
Contains:
- 🗺️ Pattern family trees (per day)
- 📊 30+ ASCII diagrams & trace tables per week
⚠️ Failure modes (wrong vs right, side-by-side)- ❓ 15 quiz questions (no answers)
- 🌐 Links to interactive visual references
Use When: You are a visual learner or need quick, diagram-based revision
Purpose: 💻 Production-grade C# implementations and patterns, see problems or patterns for weekly topics in C# language. Useful for revision or checking how concept is used or implemented in C# or using C#.
Contains:
- 🎯 Problem "signals" mapped to patterns and C# collections
- 💡 C#-specific mental model per pattern
- 🔧 C# skeletons (guard clauses, comments explaining why, not just what)
- 📚 Notes on performance characteristics and pitfalls
- 🪜 C#-focused problem ladders
Use When: Implementing in C# or preparing for C#-heavy interviews
Purpose: 💻 Conceptual weekly summary. used for quick refresher and revision.
Contains:
- includes daywise concepts/topics summary
- Pattern selection tables
Use When: Required reviesion or quick recap.
Purpose: 🧭 Strategic weekly overview and learning roadmap
Contains:
- 🎯 Learning arc (why this week matters, how it fits into the 19-week journey)
- 📅 Day-by-day overview (mental models, not just topic names)
- ⏱️ Time allocation guidance (theory vs practice vs review)
- 🚫 5–7 week-specific pitfalls and how to avoid them
- 🗺️ ASCII concept map for the week
- ✨ 7–10 key insights (aha moments)
- ✅ Weekly mastery checklist
Use When: Starting the week, or when you feel lost about direction
Purpose: 📖 Detailed reference for conceptual mastery
Contains:
- 📝 Explanations of all topics from all days
- 🔄 Comparison tables (e.g., array vs list, BFS vs DFS, greedy vs DP)
- ❌ 7–10 misconceptions corrected
- 🏭 Real-systems examples (Linux, PostgreSQL, Redis, etc.)
- 💡 Multiple mental models per concept
Use When: Deep study, concept consolidation, or pre-interview revision
Purpose: 🎯 Interview coaching with 30–50 carefully crafted questions
Contains:
- ❓ 30–50 interview questions (no answers, to force active recall)
- ➡️ 2–3 depth-based follow-ups per question
- 🟢 Difficulty tags (Easy/Medium/Hard)
- 💡 Guidance for mock interviews and self-evaluation
Use When: Practicing interviews, or stress-testing your understanding
Purpose: 🎓 Structured problem-solving strategy and problem selection
Contains:
- 🎯 3-stage progression: Mastery → Analysis → Application
- 📊 Progression tables (which problems to do at which level)
⚠️ 5–7 problem-solving pitfalls + defensive strategies- 🔧 Pattern and data-structure selection decision matrix
- 📋 Pattern templates and pseudocode skeletons
Use When: Choosing problems to solve, or debugging your problem-solving process
Purpose: 🎯 Daily action plan
Contains:
- 📅 Day-wise checklists (Mon–Sat)
- 🧠 Specific concepts to internalize each day
- 🏋️ Structured exercises (trace, draw, code, review)
- 🔗 Weekly integration tasks
- 🤔 Reflection prompts
Use When: Planning or reviewing your daily study routine
Topics: RAM Model, Pointers, Complexity Analysis, Space, Recursion I-II, Peak Finding
- 📅 Day 1: RAM Model, Virtual Memory, Pointers
- 📅 Day 2: Asymptotic Analysis (Big-O, Big-Ω, Big-Θ)
- 📅 Day 3: Space Complexity
- 📅 Day 4: Recursion I (Call Stack & Patterns)
- 📅 Day 5: Recursion II (Memoization & Advanced)
- 🌟 Day 6 (Optional): Peak Finding (1D & 2D, MIT 6.006)
Topics: Arrays, Dynamic Arrays, Linked Lists, Stacks, Queues, Binary Search
- 📅 Day 1: Static Arrays & Memory Layout
- 📅 Day 2: Dynamic Arrays & Amortized Growth
- 📅 Day 3: Linked Lists & Cache Effects
- 📅 Day 4: Stacks, Queues & Deques
- 📅 Day 5: Binary Search & Invariants
- 📅 Day 6: Strings & Numbers conceptual understanding
Topics: Elementary Sorts, Merge/Quick Sort, Heaps, Hash Tables
- 📅 Day 1: Elementary Sorts (Bubble, Selection, Insertion)
- 📅 Day 2: Merge Sort & Quick Sort
- 📅 Day 3: Heaps, Heapify & Heap Sort
- 📅 Day 4: Hash Tables I (Separate Chaining)
- 📅 Day 5: Hash Tables II (Open Addressing & Rolling Hash)
Topics: Two-Pointer, Sliding Window, Divide & Conquer, Binary Search as Pattern
- 📅 Day 1: Two-Pointer Techniques
- 📅 Day 2: Sliding Window (Fixed Size)
- 📅 Day 3: Sliding Window (Variable Size)
- 📅 Day 4: Divide & Conquer Pattern
- 📅 Day 5: Binary Search as Pattern
Interview Coverage: 25–30%
Mastery: 60–70 problems solved
Topics: Hash Maps, Monotonic Stack, Intervals, Partition & Kadane, Fast-Slow Pointers
- 📅 Day 1: Hash Map & Hash Set Patterns
- 📅 Day 2: Monotonic Stack
- 📅 Day 3: Merge Operations & Interval Patterns
- 📅 Day 4: Partition, Cyclic Sort & Kadane's Algorithm
- 📅 Day 5: Fast-Slow Pointers & Cycle Detection
Interview Coverage: 40–50%
Milestone: 70–80% interview problem coverage by end of week
Topics: Palindromes, Substrings, Parentheses, String Building, Matching
- 📅 Day 1: Palindrome Patterns
- 📅 Day 2: Substring & Sliding Window
- 📅 Day 3: Parentheses & Bracket Matching
- 📅 Day 4: String Transformations & Building
- 🌟 Day 5 (Optional): String Matching & Rolling Hash
Interview Coverage: 10–15%
Total to Date: 80%+ interview problems
Topics: Binary Trees, Traversals, BSTs, AVL Trees, Red-Black Trees, Tree Patterns, Augmented Trees
- 📅 Day 1: Binary Trees & Traversals
- 📅 Day 2: Binary Search Trees (BSTs)
- 📅 Day 3: Balanced BSTs (AVL & Red-Black)
- 📅 Day 4: Tree Patterns (Paths, Diameter, LCA)
- 🌟 Day 5 (Optional): Augmented Trees & Order-Statistics
Topics: Graph Models, Representations, BFS, DFS, Connectivity, Bipartite Graphs, SCCs
- 📅 Day 1: Graph Models & Representations
- 📅 Day 2: Breadth-First Search (BFS)
- 📅 Day 3: Depth-First Search (DFS)
- 📅 Day 4: Topological Sort & Cycle Detection
- 📅 Day 5: Connectivity & Advanced Search (2-Color, SCCs)
Topics: Dijkstra, Bellman-Ford, Floyd-Warshall, Kruskal, Prim, Union-Find
- 📅 Day 1: Dijkstra's Algorithm
- 📅 Day 2: Bellman-Ford & Negative Cycles
- 📅 Day 3: Floyd-Warshall (All-Pairs Shortest Paths)
- 📅 Day 4: Minimum Spanning Trees (Kruskal & Prim)
- 🌟 Day 5: Union-Find (Disjoint Set Union)
Topics: DP Basics, 1D DP, 2D DP, Knapsack Family, LCS, LIS, Sequence DP
- 📅 Day 1: DP Basics & Memoization vs Tabulation
- 📅 Day 2: 1D DP (Stairs, House Robber, Coin Change)
- 📅 Day 3: 2D DP (Grids, Edit Distance)
- 📅 Day 4: Sequence DP (LCS, LIS)
- 🌟 Day 5 (Optional): Story-Driven DP Problems
Topics: DP on Trees, DP on DAGs, Bitmask DP, Subset DP, State Compression
- 📅 Day 1: DP on Trees (Diameter, Independent Set)
- 📅 Day 2: DP on DAGs (Topological Order, Path Counting)
- 📅 Day 3: Bitmask & Subset DP (TSP, Hamiltonian Paths)
- 📅 Day 4: State Space Optimization & Circular Arrays
- 🌟 Day 5 (Optional): Complex Mixed DP Problems
Topics: Greedy Choice Property, Interval Scheduling, Activity Selection, Huffman Coding, Exchange Arguments
- 📅 Day 1: Greedy Algorithm Fundamentals
- 📅 Day 2: Interval Scheduling & Activity Selection
- 📅 Day 3: MST as Greedy (Cut Property & Proof)
- 📅 Day 4: Huffman Coding & Optimal Prefix Trees
- 📅 Day 5: When Greedy Fails (Counterexamples vs DP)
Topics: Backtracking Fundamentals, Backtracking Problems, Branch & Bound, Amortized Analysis
- 📅 Day 1: Backtracking Fundamentals
- 📅 Day 2: Backtracking Problems & Pruning
- 📅 Day 3: Branch & Bound Optimization
- 📅 Day 4: Amortized Analysis Techniques
- 🌟 Day 5 (Optional): Advanced Problem Solving
Topics: Matrix Traversal, Backtracking, Bitmask Tricks, Number Theory, Probability, Reservoir Sampling
- 📅 Day 1: Matrix Traversal & Search Patterns
- 📅 Day 2: Backtracking on Grids & Constraints
- 📅 Day 3: Bitmask Tricks & State Compression
- 📅 Day 4 (Optional): Number Theory & Modular Arithmetic
- 🌟 Day 5 (Optional): Probability & Sampling
Topics: KMP, Z-Algorithm, Suffix Arrays, Manacher, String Matching, Network Flow, Max-Flow Min-Cut
- 📅 Day 1: KMP String Matching
- 📅 Day 2: Z-Algorithm & Applications
- 📅 Day 3 (Optional): Manacher's Algorithm
- 📅 Day 4 (Optional): Suffix Arrays & Trees
- 📅 Day 5: Network Flow Basics & Applications
Topics: Segment Trees, Fenwick Tree (BIT), Geometry, Matrix Exponentiation, Convex Hull
- 📅 Day 1: Segment Trees & Range Queries
- 📅 Day 2: Lazy Propagation & Range Updates
- 📅 Day 3: Fenwick Tree (Binary Indexed Tree)
- 📅 Day 4: Matrix Exponentiation
- 📅 Day 5: Computational Geometry Fundamentals
Topics: Heavy-Light Decomposition, Advanced String Algorithms, FFT, Polynomial Multiplication
- 📅 Day 1: Heavy-Light Decomposition for Forests
- 📅 Day 2: Advanced Graph Problems
- 📅 Day 3: Aho-Corasick Algorithm (Conceptual)
- 📅 Day 4: FFT & Polynomial Operations
- 📅 Day 5: Advanced Optimization Techniques
Topics: Bloom Filters, Count-Min Sketch, HyperLogLog, Min-Cost Flow, Circulation, Systems Integration
- 📅 Day 1: Bloom Filters & Space-Efficient Sets
- 📅 Day 2: Count-Min Sketch & Frequency Estimation
- 📅 Day 3: HyperLogLog & Cardinality Estimation
- 📅 Day 4: Min-Cost Flow & Circulation (Conceptual)
- 📅 Day 5: Algorithmic Patterns in System Design
Topics: Mixed Problem-Solving, Communication Skills, Meta-Skills, System Integration
- 📅 Day 1: Mock Interview A – Arrays & Strings
- 📅 Day 2: Mock Interview B – Trees & Graphs
- 📅 Day 3: Mock Interview C – Dynamic Programming
- 📅 Day 4: Mixed Problem Solving Session
- 📅 Day 5: Final Assessment & Weakness Diagnosis
| Aspect | v13 Curriculum | LeetCode | YouTube | Books | Educative |
|---|---|---|---|---|---|
| Mental Models | ✅ Deep first (narrative, diagrams) | ❌ Problem list | 🟡 Varies | ✅ Strong | 🟡 Some |
| Systems Grounding | ✅ OS/DB/cache examples | ❌ None | 🟡 Some channels | 🟡 Limited | ❌ None |
| Structured Path | ✅ 19-week arc | ❌ Self-chosen | ❌ Random videos | ✅ Linear | ✅ Linear |
| Interview Q&A | ✅ 500+ prompts with follow-ups | ✅ Many, but shallow | ❌ Rare | ❌ Rare | 🟡 Some |
| Trade-off Analysis | ✅ Every major topic (chapter 4) | ❌ Minimal | 🟡 Some | ✅ Deep | ❌ Minimal |
| Narrative Flow | ✅ Lecture-style chapters | ❌ Problem dump | 🟡 Varies | ✅ Good | ✅ Mixed |
| Support Files | ✅ 6–8 per week | ❌ None | ❌ None | ❌ None | 🟡 Few |
| Visual Playbook | ✅ 30+ diagrams + tools | ❌ None | ✅ Some | 🟡 Some | ✅ Some |
| C# Support | ✅ Production-grade | ❌ None | ❌ Rare | ❌ Rare | ❌ None |
| Real Systems | ✅ 3–5 case studies/week | ❌ None | 🟡 Some | 🟡 Limited | ❌ None |
- LeetCode — Large problem bank, company tags
- NeetCode.io — Curated patterns, high-quality explanations
- AlgoExpert — Focused, high-quality interview problems
- Educative (Grokking Series) — Pattern-first practice with visuals
- Abdul Bari — Visual explanations for sorting, trees, graphs
- William Fiset — Graph theory and data structures deep dives
- Tushar Roy — Dynamic programming and recursion walkthroughs
- Tech Dose — Daily DSA problems and interview topics
- Introduction to Algorithms (CLRS) — Comprehensive theoretical reference
- Cracking the Coding Interview — Interview meta-strategy + problems
- Elements of Programming Interviews (EPI) — Implementation and edge cases
- Algorithm Design Manual (Skiena) — Design techniques and real-world stories
- MIT 6.006 — RAM model, peak finding, sorting, hashing, DP
- Princeton Algorithms (Coursera) — Sorting, searching, graphs
- GeeksforGeeks — Broad quick-reference articles and examples
- Codeforces — Advanced competitive problems
- HackerRank — Company prep kits and warm-up problems
- AtCoder — Beginner-friendly to intermediate contests
- Visualgo.net — Interactive algorithm visualizations
- Algorithm Visualizer — Code + step-by-step animations
1. Read Instructional file — 1–2 sections (20–30 min)
2. Note down 3–5 key insights (5 min)
3. Draw diagrams / traces by hand (10–15 min)
4. Study Visual Playbook diagrams (10–15 min)
5. Explain one concept aloud (10 min)
1. Solve 2–3 problems from Roadmap (50–60 min)
2. Avoid solution peeking; struggle productively (20 min)
3. Trace your solution; check invariants (20 min)
4. Compare with optimal patterns; adjust mental model (10–20 min)
1. Do 5 Interview_QA questions from the week (10–15 min)
2. Record one answer; listen critically (5–10 min)
3. Log confusion points for next day (5 min)
1. Solve 3–5 higher-difficulty problems (90 min)
2. Simulate one full mock interview (60 min)
3. Deep review of weak areas (30 min)
- ✅ Understand RAM model, memory layout, pointers
- ✅ Classify algorithms by Big-O, with proofs via simple recurrences
- ✅ Trace recursion and reason about space/time
- ✅ Implement basic sorts, heaps, and hash tables
Mastery Level: Foundation Set ⚙️
- ✅ Solve 70–80% of array/string interview problems
- ✅ Recognize two-pointer, window, hash, interval, stack patterns quickly
- ✅ Solve most medium-level problems in 25–35 minutes
Mastery Level: Strong Base 📋
- ✅ Solve 80–88% of common interview problems
- ✅ Design tree and graph solutions including shortest paths
- ✅ Implement BFS, DFS, Dijkstra, Bellman–Ford, MST
- ✅ Recognize and implement core DP families
Mastery Level: Competent 🌳
- ✅ Understand and explain greedy correctness (via exchange arguments)
- ✅ Make informed choices between greedy and DP
- ✅ Perform formal amortized analysis for key data structures
Mastery Level: Proficient ⚙️
- ✅ Solve 90–95% of interview problems
- ✅ Integrate multiple patterns in a single solution (e.g., DP + intervals + stack)
- ✅ Communicate complex solutions and trade-offs clearly
Mastery Level: Advanced 🔄
- ✅ Understand advanced data structures and algorithms
- ✅ Discuss flows, geometry, advanced graphs, probabilistic DS
- ✅ Connect algorithms to modern large-scale systems
Mastery Level: Elite 🚀
- ✅ Confidently handle novel interview problems
- ✅ Pass typical FAANG technical screens
- ✅ Present solutions like a senior engineer
Mastery Level: Interview Ready 🎤
Complete Mastery? → Sequential, Week 1–19, 16–20 weeks
Interview Prep? → Intensive, Week 4+, 6–8 weeks
Quick Refresh? → Topic-based, 2–4 weeks
1. README_v13.md — overview & map
2. START_HERE.md — path selection
3. COMPLETE_SYLLABUS_v13.md — fine-grained syllabus
1. Open Week_01_Guidelines.md — weekly strategy
2. Study Week_01_Day_01_...Instructional — narrative learning
3. Follow Week01_Daily_Progress_Checklist.md
4. Use Roadmap + Interview_QA for practice & review
dsa-master-curriculum-v13/
📄 README_v13.md # Main entrypoint (this file)
📄 START_HERE.md # Path selection & orientation
📄 LICENSE
📄 COMPLETE_SYLLABUS_v13.md
📄 COMPLETE_CONTENT_INDEX.md
📁 v12orV13-prompts/
├── MASTER_PROMPT.md
├── SYSTEM_CONFIG.md
├── SYSTEM_PROMPT_v12_FOR_AI_CHAT.md
├── SYSTEM_PROMPT_v13_EXTENDED_SUPPORT_CSHARP.md
└── Additional support files
📁 v12-templates/
├── Template_v12_Narrative_FINAL.md
├── EMOJI_ICON_GUIDE_v12.md
├── VISUAL_PLAYBOOK_GENERATION_PROMPT_v12.md
└── Supporting templates
📁 week_01_foundations_i_computational_fundamentals/
│ Week_01_Day_01_RAM_Model_Pointers_Instructional.md
│ Week_01_Day_02_Asymptotic_Analysis_Instructional.md
│ Week_01_Day_03_Space_Complexity_Memory_Usage_Instructional.md
│ Week_01_Day_04_Recursion_I_Call_Stack_Instructional.md
│ Week_01_Day_05_Recursion_II_Memoization_Instructional.md
│ Week_01_Day_06_Peak_Finding_Algorithmic_Thinking_Instructional.md
│ WEEK_01_FULL_PLAYBOOK.md
│ Week_01_Problem_Solving_Roadmap_Extended_CSharp.md
│ Week_01_Visual_Concepts_Playbook_HYBRID.md
│
├───📁 support files
│ Week01_DailyProgressChecklist.md
│ Week01_Guidelines.md
│ Week01_InterviewQA_Reference.md
│ Week01_ProblemSolvingRoadmap.md
│ Week01_Summary_KeyConcepts.md
📁 week_02_foundations_ii_linear_data_structures/
📁 week_03_foundations_iii_sorting_and_hashing/
📁 week_04_core_problem_solving_patterns_i/
📁 week_05_tier_1_critical_patterns/
📁 week_06_string_manipulation_patterns/
📁 week_07_trees_and_balanced_search_trees/
📁 week_08_graph_fundamentals/
📁 week_09_graph_algorithms_i/
📁 week_10_dynamic_programming_i_fundamentals/
📁 week_11_dp_ii_advanced/
📁 week_12_greedy_and_paradigms/
📁 week_13_backtracking_and_branch_bound/
📁 week_14_matrix_backtracking_bits/
📁 week_15_advanced_strings_flow/
📁 week_16_advanced_data_structures/
📁 week_17_advanced_graphs_hld_fft/
📁 week_18_probabilistic_ds_systems/
📁 week_19_mock_interviews_mastery/
📁 assets/
├── diagrams/
├── flowcharts/
├── traces/
└── tables/
- ✅ Narrative-First: Every instructional file reads like a lecture, not a checklist
- ✅ Pattern-Centric: Focus on ideas that generalize across many problems
- ✅ Production-Grade C#: No spaghetti code, thoughtful data-structure choices
- ✅ Systems-Grounded: Frequent links to real systems and engineering trade-offs
- ✅ MIT-Level Rigor: Explicit coverage of core 6.006/6.046 topics
- ✅ Visual Support: At least 30 diagrams per week via Visual Playbook
- ✅ Interview-Ready: Hundreds of Q&A prompts with realistic follow-ups
For now, this curriculum is primarily a learning artifact. If you spot errors, ambiguities, or have suggestions:
- Open an issue in your repo
- Propose a fix via PR with a clear explanation
Q: Is this only for C# developers?
A: No. Concepts are language-agnostic. C# support is a bonus layer.
Q: Can I skip the optional deep-dive weeks (16–18)?
A: Yes. They are recommended for elite prep and competitive programming, not mandatory for normal interviews.
Q: How many problems should I solve per week?
A: Typical range: 20–40, depending on time and difficulty.
📜 MIT License — You may use, modify, and teach from this material. Attribution is appreciated but not required.
