πŸ“š Learning Journey

πŸ€– GenAI/LLM INTEGRATION FROM DAY 1
ACTIVE - Stage 1 in Progress

37-Month GenAI-First Career Transformation
Business Ops β†’ GenAI-First Data Analyst & AI Engineer β†’ GenAI Data Engineer + AI Systems β†’ ML Engineer + Local LLM Specialist β†’ Agentic AI Engineer β†’ Senior LLM Engineer

πŸš€ 2026 Market Advantage: GenAI/LLM Engineering from Week 1

While most candidates learn traditional tools only, this journey integrates GenAI/LLM engineering systematically from Week 1β€”building production AI systems with LLM SDKs (Gemini, OpenAI, Claude), RAG pipelines, Multimodal AI, and Streamlit by Month 1. Progressing through Vector DBs, local LLMs, to MCP + multi-agent orchestration by Month 34.

LLM SDKs (Gemini/OpenAI/Claude) RAG + ChromaDB Multimodal AI Pydantic Streamlit PandasAI Cursor AI IDE

πŸ† Production Code, Not Just Tutorials

1099 Reconciliation ETL Pipeline: Live system at Daybright Financial

95% Time Saved
$15K+ Annual Savings
10x Scalability
0 Errors

🎯 Career Progression: Stage 1 of 5

πŸ“Š Stage 1: GenAI-First DA & AI Eng

Status: Active (Months 1-5)

Focus: Python, SQL + LLM SDKs + RAG + Multimodal AI + Streamlit

Goal: AI Engineer who knows Analytics

πŸ”§ Stage 2: GenAI DE + AI Systems

Timeline: Months 6-15

Focus: AWS + Vector DBs + RAG Infrastructure

πŸ€– Stage 3: ML + Local LLM Specialist

Timeline: Months 16-29

Focus: ML + Ollama + Fine-Tuning (PEFT)

🧠 Stage 4: Agentic AI Engineer

Timeline: Months 30-34

Focus: MCP + LangGraph + Multi-Agent Systems

⭐ Stage 5: Senior LLM Eng

Timeline: Months 35-37

Focus: LLMOps Evaluation + Production AI

πŸ’Ό Project Pipeline β€” Skills Progression (Easy β†’ Flagship)

Each project introduces new skills that build on the previous

37
Months Total
5
GenAI-Powered Stages
25
Hours/Week
7
Production-Grade Projects