Generative AI, LLM Engineering & AI Agents
A cutting-edge curriculum covering LLM APIs, vector similarity search, retrieval augmented generation, and custom model fine-tuning.
Generative AI is transforming software engineering. Master prompt engineering layouts, design Retrieval Augmented Generation (RAG) pipelines, configure local models, and build cognitive applications.
Structured Curriculum Roadmap
Generative AI Basics & Prompt Engineering
Understand model parameters (temperature, top-p), write detailed prompt templates, parse json outputs, and use OpenAI/Anthropic APIs.
Text Embeddings & Vector Databases
Generate floating-point vector embeddings from documents, set up vector databases, configure indexes, and execute cosine similarity searches.
Retrieval Augmented Generation (RAG) Pipelines
Build automated document ingestion pipelines, chunk text files, query vector databases, and inject context into LLM templates.
Local LLMs & Self-Hosted AI Agents
Run open-source models (Llama 3, Mistral) locally using Ollama, construct interactive tools, and configure memory relays.
LLM Fine-Tuning & Quantization
Prepare custom dataset arrays, fine-tune models using LoRA/QLoRA methods, configure loss plots, quantize models to GGUF format, and deploy.
Skills Acquired
- • Prompt Engineering Layouts
- • Vector Search Indexes
- • RAG System Construction
- • Local LLM Deployment
- • LoRA Model Fine-Tuning
Tools & Libraries
- • Hugging Face
- • Ollama Engine
- • pgvector DB
- • Unsloth
- • LangChain
Capstone Outcomes
- • Construct context-aware enterprise chatbots
- • Fine-tune open-source models on custom text datasets
- • Deploy local self-hosted LLM services
Academy Advantages & Career Outlook
Flexible Blended Learning: Online & Offline
To ensure high-performance execution, we offer both structured online classes (with live instructor-led screenshares) and immersive offline classes at our technical campus hubs.
- • Interactive offline lab sandboxes & physical server setups
- • Flexible online portals with direct classroom recordings
- • Shared enterprise repository code reviews on GitHub
GenAI-Optimized Curriculum
Software engineering is evolving. We train candidates to integrate Generative AI directly into their core workflows:
"Deep immersion in LLM APIs, fine-tuning open source models (Llama 3/Mistral), vector databases, RAG structures, and building multi-agent systems."
Target Roles & Earning Potential
Graduating from this roadmap qualifies you for high-paying roles across various tech domains.
International & Remote Success
Companies globally are seeking top engineers specialized in this tech domain. Our certification is recognized internationally.
- • Direct integration with US, UK, and European remote contract companies
- • Relocation mentoring & cross-border interview coaching sessions
- • Active portfolio support with production-grade project samples
Retrieval Augmented Generation (RAG) Success
"Discover how to implement advanced search scoring, re-ranking models, and semantic chunking to ensure your custom LLMs retrieve accurate factual context from your company documents. This phase provides direct codebase exposure, giving you experience with standard enterprise development loops."
Frequently Asked Questions
Is this course suitable for beginners in Python?
You should have basic Python programming skills. We cover all libraries (LangChain, PyTorch helper utilities, transformers) in detail.
