The 6-Month Roadmap
The curriculum is structured into three distinct phases, each building upon the last. This timeline provides a high-level overview of the core focus for each month, guiding you from setup to specialization.
Month 1: Foundations
Establish your developer office and rapidly cover IT fundamentals, networking, and security.
Month 2: Core SWE I (Java)
Master Data Structures, Algorithms, and advanced Git workflows using Java.
Month 3: Core SWE II (Java)
Build RESTful APIs and connect to databases, solidifying your backend skills in Java.
Month 4: Python & AI Math
Transition to Python and build the mathematical foundation for AI with Linear Algebra and Calculus.
Month 5: RAG & Vector DBs
Dive into Embeddings, Vector Databases, and build Retrieval Augmented Generation pipelines.
Month 6: Fine-Tuning & Deploy
Train your own LLM, build AI agents, and learn to deploy models into production.
Curriculum Focus Distribution
The program is weighted towards advanced topics, ensuring you spend the most time on the specialized skills required for AI engineering roles.
Language Focus: Java to Python
The curriculum begins with Java to build strong, typed programming fundamentals, then strategically pivots to Python, the lingua franca of AI and machine learning.
Key Technologies You'll Master
You'll gain hands-on experience with a modern, industry-standard tech stack. The size of each bubble represents its relative focus within the advanced AI portion of the curriculum.
The Mathematical Foundation
A conceptual and practical understanding of key mathematical areas is essential for truly understanding how AI models work. This chart shows the relative focus on each topic.
Capstone Project: Custom LLM
The curriculum culminates in a capstone project where you fine-tune and deploy your own Language Model, a critical skill that demonstrates end-to-end AI engineering capability.
Data Prep
Model Choice
Fine-Tuning
Evaluation
Deployment