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📋 TODO — Coding for MBA

Unified roadmap — app features, curriculum expansion, DX improvements, and long-horizon ideas.
Stack: Vite 7 · React 19 · TypeScript 5.9 · motion · zustand · zod · react-hot-toast · canvas-confetti

Last updated: Mar 2, 2026

✅ Completed

Audit update (2026-02-28): Re-validated items marked complete against current codebase and in-app surfacing. Tasks found partially implemented have been moved back to incomplete with notes.

Click to expand completed items

Quick Wins — already shipped

  • Toast feedback on progress save, exercise submission, theme toggle
  • Confetti on quiz ace, phase unlock, lesson complete, full-curriculum finale
  • Zod schemas for lesson frontmatter + build-time validation
  • Page transitions (AnimatePresence fade + slide)
  • Staggered card entrance, spring-physics progress bar, hover lift
  • Parallax hero, scroll-triggered fade-in lessons, animated stats counters
  • layoutId shared transitions, masonry stagger for concept graph
  • Zustand progress store + persist middleware
  • Quiz attempt tracking, per-question analytics, spaced repetition surfacing
  • User preferences store (theme, sidebar, font-size, code lang, density)
  • Time-on-page / study streak / weekly chart / total learning time
  • Glassmorphism dark-mode cards, animated gradient mesh hero
  • Breadcrumb trail, "continue where you left off" banner
  • Keyboard shortcut overlay (?)
  • XP + badge gamification layer on Progress page
  • Vite 7 module preload optimisation, bundle analysis script
  • Playwright visual regression + reduced-motion tests
  • Zustand + Zod unit tests
  • Strict TypeScript satisfies patterns, error boundaries with toast fallbacks

🔴 Priority 1 — Curriculum (do next)

These fix the most critical content gaps identified in the curriculum audit.

Phase Overviews — Depth Upgrades

Validation note (2026-02-27): Cross-checked Agent-P2, Agent-P8, and Agent-P9 overview updates against underlying Day_*/README.md lesson scope and sequence. Section coverage is now explicitly evidenced in the overview docs (skills matrix, ROI tables, scenario walkthroughs, exam prompts, cloud-native/capstone bridges), and all listed Phase 2/8/9 overview depth criteria are now satisfied.

  • Phase 2 Overview — expanded to Phase 5 depth standard (300+ lines, ROI table, 3-tier skills matrix, 5+ pitfalls, 4+ exam Qs)
  • Phase 8 Overview — scenario walkthroughs, 2+ milestone exam questions, expert track, and extras/ folder are now present
  • Phase 9 Overview — Cloud-native SQL section and curriculum capstone preview are present; >15 KB length is acceptable for this overview

Gap-Filling Lesson Days

  • Day_37B_Probability_and_Statistics_for_ML — distributions, Bayes theorem, CLT (prerequisite for Phase 5 Day 54)
  • Day_37C_Sklearn_Pipelines — Pipeline, ColumnTransformer, custom transformers, CV
  • Day_36B_Docker_Fundamentals — containers, images, Compose for data apps (Phase 3 bonus)
  • Day_60B_LLM_Fine_Tuning_and_PEFT — LoRA, QLoRA, Hugging Face PEFT library
  • Day_60C_RAG_and_Vector_Databases — embeddings, ChromaDB, LangChain RAG pipeline
  • Day_84B_dbt_Fundamentals — models, refs, tests, docs, dbt Cloud
  • Day_96B_NoSQL_Deep_Dive — MongoDB, Redis, Cassandra — when to use each

Extras/ Folders

  • Add extras/ to Phase 2 (sample DataFrames, advanced Pandas notebooks)
  • Add extras/ to Phase 5 (PEFT configs, RAG starters)
  • Add extras/ to Phase 8 (DDL scripts, sample datasets)
  • Add extras/ to Phase 9 (capstone data + solution scaffold)

🟡 Priority 2 — New Phases & Major Content

Phase 10 — Generative AI & LLM Engineering (Days 109–120) ✅ Complete

Phase already implemented. Audit & polish pass needed.

  • Verify all 12 day files meet the content depth standard (500+ words, 3+ exercises, 5 Q&A)
  • Add quiz.json to each Phase 10 day
  • Phase 10 Overview polish — ensure ROI table and expert track are present
  • Add extras/ with LLM starter notebooks and prompt library

Phase 11 — Cloud Data Engineering (Days 121–132) ✅ Complete

  • Day_121_Cloud_Fundamentals — AWS/GCP/Azure architecture, IAM, cost management
  • Day_122_Object_Storage — S3, GCS, Delta Lake, Iceberg table formats
  • Day_123_Cloud_Data_Warehouses — BigQuery, Snowflake, Redshift architecture
  • Day_124_dbt_at_Scale — incremental models, snapshots, advanced patterns
  • Day_125_Orchestration — Apache Airflow, Prefect, Dagster
  • Day_126_Streaming_Pipelines — Kafka, Pub/Sub, Kinesis, real-time ETL
  • Day_127_Lakehouse_Architecture — Databricks, Unity Catalog, Delta Live Tables
  • Day_128_Data_Contracts_and_Quality — Great Expectations, Soda, data SLAs
  • Day_129_Cloud_Security_and_Compliance — VPC, encryption, PII handling
  • Day_130_Cost_Engineering — query optimisation for $/TB, slot management
  • Day_131_Platform_Engineering — Terraform for data infrastructure
  • Day_132_Capstone_Cloud_Data_Pipeline — end-to-end cloud pipeline project
  • Phase 11 Overview (300+ lines) — expanded to 513 lines with day-by-day journey, 3-tier skills matrix, 6 pitfalls, 5 exam questions, scenario walkthroughs, and expert track

Phase 12 — Analytics Engineering & Data Products (Days 133–140) ✅ Complete

  • Day_133_Analytics_Engineer_Role — vs Data Analyst, Data Scientist, DE
  • Day_134_Semantic_and_Metrics_Layers — dbt Metrics, Cube.js, LookML
  • Day_135_Self_Serve_Analytics — empowering stakeholders without SQL
  • Day_136_Data_Mesh_Principles — domain ownership, data products
  • Day_137_Product_Analytics_Deep_Dive — retention, funnels, cohort analysis
  • Day_138_AB_Testing_at_Scale — statistical rigor, experimentation platforms
  • Day_139_Data_Products_and_Monetization — API-first data, embedded analytics
  • Day_140_Capstone_Data_Product — design a data product for a business unit
  • Phase 12 Overview

Additional Gap-Filling Days

  • Day_68_AI_Agents_and_Tool_Use — LangChain/LlamaIndex agents, function calling, ReAct (Phase 6)
  • Day_69_Responsible_AI_in_Practice — model cards, Fairlearn, audit reporting (Phase 6)
  • Day_84C_Reverse_ETL_and_Semantic_Layer — Hightouch concepts, operational analytics (Phase 7)
  • Day_96C_Streaming_SQL_Fundamentals — Kafka concepts, ksqlDB basics, real-time aggregations (Phase 8)
  • Day_108C_Cloud_Native_SQL — BigQuery ML, Snowflake Cortex, Redshift ML
  • Day_108B_Curriculum_Capstone — ingest → clean → model → visualise → deploy (all 9+ phases)

🟢 Priority 3 — App Features

Structured Quiz JSON Integration

Each lesson day needs a quiz.json sidecar for the app's quiz engine:

{
  "day": 1,
  "questions": [
    {
      "id": "d01q01",
      "type": "multiple_choice",
      "question": "What is a variable in Python?",
      "options": ["A loop", "A labeled container for data", "A function", "A module"],
      "answer": 1,
      "explanation": "Variables are named storage locations..."
    }
  ]
}
  • Script: scripts/generate-quiz-stubs.js — scaffold quiz.json for all days that don't have one
  • App: QuizEngine component reads quiz.json, replaces markdown mastery-check section
  • App: wrong-answer analytics surfaced in the spaced-repetition store

Phase 1 quiz.json — completed (2026-03-02)

  • Day_01_Introduction — quiz.json (5 questions: print, arithmetic, exponentiation, print(), type conversion)
  • Day_02_Variables_Builtin_Functions — quiz.json (5 questions: data types, len(), naming rules, int(), reassignment)
  • Day_03_Operators — quiz.json (5 questions: PEMDAS, modulo, !=, +=, logical and)
  • Day_04_Strings — quiz.json (5 questions: slicing, f-strings, strip/lower, immutability, title())
  • Day_05_Lists — quiz.json (5 questions: slicing, aliasing, append(), sorted(), max())
  • Day_06_Tuples — quiz.json (5 questions: single-element tuple, immutability, unpacking, use cases, sum())
  • Day_07_Sets — quiz.json (5 questions: uniqueness, intersection, empty set, symmetric difference, hashability)
  • Day_08_Dictionaries — quiz.json (5 questions: get(), items(), comprehension, KeyError, len())
  • Day_09_Conditionals — quiz.json (5 questions: and logic, elif, falsy values, ternary, business scenario)
  • Day_10_Loops — quiz.json (5 questions: range(), break, enumerate(), while vs for, zip())
  • Day_11_Functions — quiz.json (5 questions: mutable default, **kwargs, pure functions, composition, lambda)
  • Day_11B_Generators_Iterators — quiz.json (5 questions: iterator protocol, memory advantage, yield, yield from, pipeline)
  • Day_11C_Debugging_Workflows — quiz.json (5 questions: traceback reading, KeyError, debug workflow, breakpoint(), logging)
  • Day_12_List_Comprehension — quiz.json (5 questions: basic, filter, generator expr, nested, readability)

Capstone Project Scaffolds (content/projects/)

  • 01_python_data_pipeline/ — Phase 1–2 skills showcase
  • 02_web_dashboard/ — Phase 3 Flask/Streamlit project
  • 03_ml_churn_predictor/ — Phase 4–5 end-to-end ML model
  • 04_bi_analytics_suite/ — Phase 6–7 Tableau/Power BI + SQL
  • 05_sql_data_warehouse/ — Phase 8–9 full DDL + ETL
  • 06_llm_data_assistant/ — Phase 10 RAG / agent demo

MBA Case Studies (content/case-studies/) ✅ Complete

Each case study includes a comprehensive README.md with hand-holding walkthrough (step-by-step guidance with checkpoints), a starter.py scaffold, and a data_generator.py for synthetic data.

  • 01 — Retail Customer Churn (Logistic Regression, XGBoost) — Phase 4–5
  • 02 — Finance Fraud Detection (Anomaly Detection, GNN) — Phase 5
  • 03 — Healthcare Patient Risk (Ensemble, Probabilistic) — Phase 5
  • 04 — E-Commerce Recommendations (Collaborative Filtering) — Phase 5
  • 05 — Marketing Campaign Attribution (A/B Testing, Causal Inference) — Phase 6
  • 06 — Operations Demand Forecasting (Time Series, ARIMA, Prophet) — Phase 5
  • 07 — HR Attrition Prediction (Classification, SHAP) — Phase 4–5
  • 08 — SaaS Growth Analytics (Cohorts, Product Analytics) — Phase 7
  • 09 — Supply Chain Inventory (LP, Simulation) — Phase 4
  • 10 — Banking Credit Scoring (Scorecard, Fairness) — Phase 6

Collaborative Features

  • Shareable progress link (base64-encoded state)
  • "Challenge a friend" — send quiz links
  • Discussion prompts at the end of each lesson

Offline / PWA Support

  • Service Worker for offline lesson reading
  • Cache lesson markdown on first visit
  • Offline progress tracking with sync-on-reconnect
  • PWA manifest for "Add to Home Screen"

🔵 Priority 4 — DX & Infrastructure

Content Quality Automation

  • scripts/audit-lessons.js — verify all days meet depth standard (500+ words, 3 exercises, 5 Q&A)
  • scripts/generate-quiz-stubs.js — scaffold missing quiz.json files
  • scripts/check-phase-overviews.js — flag overviews below 300 lines / 10 KB
  • CI gate: fail build if any lesson fails the depth audit

Cross-Phase "Career Tracks" Page

  • Design "career tracks" routing: Data Scientist / Analytics Engineer / ML Engineer tracks
  • App page linking days by specialisation
  • "What's Next" sidebar section on each phase overview page

Advanced Visualisations

  • Skill radar chart on Progress page
  • Heatmap calendar of study activity (GitHub-style)
  • Animated dependency tree of tech concepts
  • 3D concept graph (Three.js / React Three Fiber) — stretch goal

Testing

  • Increase unit test coverage to 80%+
  • Snapshot tests for all major page components
  • Accessibility audit (axe-core) in CI

2026 Market Alignment — Gap Tracker

Skill Coverage 2026 Demand Action
Python fundamentals ✅ Phase 1–2 High —
Pandas / NumPy ✅ Phase 2 High —
ML fundamentals ✅ Phase 4–5 High —
Deep learning ✅ Phase 5 High —
MLOps ✅ Phase 5 (Day 50, 65) Very High Minor depth increase
LLMs / GPT APIs ✅ Phase 10 Critical Polish pass
RAG & Vector DBs ✅ Phase 10 (Day 112) Critical Add Day 60C cross-ref
AI Agents ✅ Phase 10 (Day 115) Critical Add Day 67B Phase 6 bridge
dbt ⚠️ Day 84B (planned) High Implement P1
Cloud (AWS/GCP/Azure) ⚠️ Phase 8 surface only Very High Add Phase 11
Kafka / Streaming ⚠️ Day 96C (planned) High Implement P2
BI / Tableau ✅ Phase 6–7 High —
SQL mastery ✅ Phase 8–9 High —
Data governance ✅ Phase 7–8 High —
Responsible AI ⚠️ Day 62 (partial) High Add Day 67C Phase 6

🌌 Ambitious / Long-Horizon

  • Multi-user mode: instructor dashboard, cohort progress overview
  • AI-graded exercise submissions (code execution sandbox)
  • Video lesson stubs — embed Loom / YouTube per day
  • Phase 13: Financial Modelling & Quant Finance (Python, Monte Carlo, Black-Scholes)
  • Phase 14: Web3 & Decentralised Data (Solidity basics, on-chain analytics)
  • Localisation: Spanish & Mandarin translations of lesson summaries
  • Mobile app (React Native): offline-first lesson reader with push-notification streaks

This is a living document. Update priorities as phases are completed or the market shifts.