u/Any_Dependent6603

Web Foundations (Current Stage)

HTML (tags, forms, semantics)

CSS (Flexbox, Grid, responsive design)

Basic JavaScript (variables, functions, DOM, events)

2. Programming Fundamentals

Python Basics (variables, data types, loops, conditionals)

Functions, Modules & Packages

Data Structures (lists, dictionaries, sets, tuples)

Object-Oriented Programming (classes, inheritance)

File handling, error handling & debugging

Git & GitHub (branching, PRs, collaboration)

3. Web Development for AI Apps

Advanced Frontend (HTML + CSS + JavaScript, interactive UIs)

Backend: FastAPI (preferred) or Flask

REST APIs, authentication (JWT, OAuth)

Connecting frontend to backend

Full-stack projects with AI integration

4. Data & Math Basics

NumPy & Pandas (data manipulation)

Data cleaning, exploration & visualization (Matplotlib, Seaborn)

SQL (queries, joins, indexing)

Linear algebra (vectors, matrices)

Probability & Statistics (basics)

Basic calculus concepts (for understanding optimization)

5. AI & Machine Learning Core

Machine Learning fundamentals (supervised, unsupervised, evaluation metrics)

Scikit-learn (regression, classification, clustering)

Neural networks & Deep Learning intro

PyTorch (preferred) or TensorFlow basics

6. Modern Generative AI (Core for Builders)

Prompt Engineering (basic to advanced, chain-of-thought, context engineering)

LLM APIs (OpenAI, Grok, Claude, Gemini)

Hugging Face (models, datasets, spaces)

Fine-tuning (LoRA/QLoRA)

Multimodal AI (text + image + voice basics)

7. AI Application Skills

Retrieval-Augmented Generation (RAG)

Vector databases (Chroma, FAISS, Pinecone, Weaviate)

Embeddings & semantic search

AI Agents & Tool use (planning, memory, execution)

Frameworks: LangChain / LangGraph / LlamaIndex / CrewAI

AI Workflow Automation & Tool Stacking

8. Production & SaaS Technical Skills

Authentication & Authorization (secure user management)

Databases (PostgreSQL + vector extensions, Supabase)

Multi-tenant architecture & data isolation

Docker & containerization

Cloud deployment (Vercel, Railway, AWS, Render)

API scaling, rate limiting & cost control (LLM tokens)

Monitoring, logging & observability (LangSmith, Prometheus)

Evaluation & Testing AI outputs (evals, hallucination checks)

Security, guardrails & Responsible AI

Usage-based billing & webhooks (Stripe integration)

9. Business & Founder Skills for AI SaaS

Idea validation & customer discovery (interviews, surveys)

Problem framing & niche selection

Landing page building & waitlist collection

Pricing strategy & packaging (tiered, usage-based)

Sales, marketing & growth (SEO, content, ads, indie hacking)

Customer support & retention systems

Financial basics (burn rate, runway, profitability)

Product metrics & ROI measurement

Legal & compliance (privacy/GDPR, terms of service)

10. Advanced & Supporting Skills

AI-assisted coding (Cursor, Claude, Grok for vibe coding)

Clean code, system design & architecture

Context engineering & long-term memory systems

MLOps / LLMOps basics

Staying updated with AI trends & new models

Aesthetic judgment, UX polish & taste

11. Projects & Portfolio (Build These Progressively)

Static + interactive websites

Python automation scripts

Full-stack web apps

Simple LLM chatbot

RAG-powered document/Q&A tool

Multi-agent AI workflow

Production-ready AI SaaS MVP (with auth, payments, deployment)

Public launches + user feedback iterations