AI & Generative AI CODE: RR-INT-AIG-014 Online

AI & Generative AI Engineering Track

Explore the cutting-edge frontier of Artificial Intelligence: Neural Networks, PyTorch/TensorFlow, Large Language Models (LLMs), LangChain, RAG (Retrieval-Augmented Generation), and Prompt Engineering.

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🛠️ Core Responsibilities

✓ Build Neural Networks for classification and natural language tasks using PyTorch.
✓ Develop LLM applications using OpenAI API, LangChain, and LlamaIndex.
✓ Implement Retrieval-Augmented Generation (RAG) using Vector Databases (ChromaDB / Pinecone).
✓ Deploy Generative AI web apps using Streamlit / Gradio and FastAPI.

🎯 Learning Outcomes & Skills Acquired

🚀 Deep Learning fundamentals: Backpropagation, Transformers, Attention Mechanism.
🚀 Building production-ready RAG systems and AI agents.
🚀 Fine-tuning open-source LLMs (Llama 3, Mistral) and API orchestration.

Key Technologies & Skills

⚡ Python ⚡ PyTorch ⚡ Generative AI ⚡ LLMs ⚡ LangChain ⚡ RAG ⚡ Vector DB ⚡ Streamlit

📅 Weekly Structured Training Plan

Week 1: AI Fundamentals, Deep Learning Math & PyTorch Basics

Week 2: Building Multi-Layer Perceptrons & Training Neural Networks

Week 3: Natural Language Processing (NLP) Basics & Word Embeddings

Week 4: Transformer Architecture & Attention Mechanism Deep Dive

Week 5: Introduction to Generative AI & Large Language Models (LLMs)

Week 6: Prompt Engineering Techniques & OpenAI / HuggingFace APIs

Week 7: Vector Databases (ChromaDB, Pinecone) & Semantic Search

Week 8: Building Retrieval-Augmented Generation (RAG) Systems with LangChain

Week 9: Building Autonomous AI Agents & Tool Calling

W10

Week 10: Fine-Tuning Open-Source LLMs (PEFT / LoRA)

W11

Week 11: Deploying GenAI Apps with Streamlit, Gradio & FastAPI

W12

Week 12: End-to-End Enterprise Generative AI Capstone System

🎁 Program Inclusions & Evaluation

What Is Included & Completion Requirements

Detailed breakdown of the educational deliverables, mentor support, and certification criteria:

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Structured Educational Training

12 weeks of guided syllabus covering software engineering concepts, tools, and best practices.

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Direct Mentor Guidance

1-on-1 mentorship, code reviews, and architectural problem-solving guided by Rashesh Rehi.

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Hands-on Capstone Project

Build a production-ready application suitable for college submissions and portfolio showcases.

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Milestone Assessments

Regular milestone task evaluations to assess coding standards, problem solving, and architecture.

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Verifiable Certificate

QR-verifiable Digital Certificate of Training & Internship Completion upon meeting all criteria.

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Letter of Recommendation (LOR)

Performance-based recommendation letter endorsing your evaluated project quality and skills.

🎯 Completion & Credential Requirements:

Complete and submit all 4 required milestone tasks on the student portal.
Develop, document, and submit the functional capstone project source code.
Achieve passing evaluation from the mentor to qualify for Certificate and LOR issuance.

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Educational Program Transparency & Disclaimer

This program is an educational industrial training and project-based internship program conducted by Rashesh Rehi to help students build practical engineering skills and fulfill university curriculum requirements. It is an educational training program and does not constitute formal employment or an employer-employee relationship with any external company.

Track Overview

Fees: ₹999

Min Batch Size: 15 Students

Duration: 12 Weeks

Level: Beginner to Advanced

Language: English / Hindi / Gujarati

Mode: online

Stipend: Performance_based

Certificate: Available ✅

Recommendation Letter: Available ✅

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Rashesh Rehi

Founder & Principal Tech Lead • Rashesh Rehi Technologies

Senior Software Architect with 10+ years of industrial development experience guiding full-stack engineers and tech leads.