Best Generative AI & Prompt Engineering Bootcamp in Surat

Lead the tech revolution in Surat.

In this course, you will learn advanced skills including:

Prompt Engineering
Agentic Workflows
How to build custom GPTs

This course is designed to make you an indispensable AI asset to any IT company.

Duration: 6 Months

Course Curriculum

Introduction to Generative AI & LLMs

The evolution of AI: From traditional Machine Learning to Generative AI.
How Large Language Models (LLMs) actually work: The Transformer architecture explained simply.
Overview of the AI landscape: OpenAI (GPT-4), Google (Gemini), Anthropic (Claude), and Open-Source models (Llama 3, Mistral).
Understanding tokenization, context windows, and model limitations.
Setting up API access and navigating playground environments.

Foundations of Prompt Engineering

The anatomy of a perfect prompt: Persona, Context, Task, and Output format.
Zero-shot vs. One-shot vs. Few-shot prompting techniques.
System Prompts vs. User Prompts: Guiding model behavior at the core level.
Formatting outputs: Forcing JSON, Markdown, tabular data, and specific code structures.
Best practices for managing prompt iterations and version control.

Advanced Prompting Frameworks

Chain-of-Thought (CoT) prompting: Forcing the AI to "think step-by-step" for complex logic.
Tree of Thoughts (ToT) and reasoning pathways for complex problem-solving.
The ReAct (Reasoning and Acting) framework: Bridging text generation with external actions.
Identifying and mitigating AI hallucinations and biases in enterprise use cases.
Prompt injection attacks: Understanding vulnerabilities and securing your prompts.

Building Custom GPTs & Assistants

Navigating the OpenAI GPT Builder and Assistants API.
Crafting robust Custom Instructions for tailored AI behavior.
Uploading and managing proprietary Knowledge Bases for Custom GPTs.
Integrating APIs using Actions: Allowing your GPT to fetch live data or trigger external webhooks.
Deploying internal AI assistants for HR, customer support, and IT helpdesks.

Introduction to Agentic Workflows

What is an AI Agent? Understanding the shift from passive prompts to autonomous agents.
The core components of an agent: Planning, Memory (Short-term vs. Long-term), and Tool use.
Giving AI access to the outside world: Web search tools, calculators, and code interpreters.
Designing single-agent workflows to automate repetitive IT and administrative tasks.
Tracing agent thought processes and debugging infinite loops.

Multi-Agent Systems & Frameworks

The power of collaboration: Why multi-agent systems outperform single models.
Introduction to leading agent frameworks: CrewAI, AutoGen, and LangGraph.
Defining distinct agent roles, goals, and backstories for specialized tasks.
Orchestrating agent conversations: Sequential, hierarchical, and asynchronous workflows.
Building a "virtual IT team" (e.g., a researcher agent passing data to a coder agent, reviewed by a QA agent).

Retrieval-Augmented Generation (RAG) Foundations

Why fine-tuning is often the wrong choice: The power of RAG for enterprise data.
Understanding vector embeddings: Translating text into mathematical representations.
Chunking strategies: Breaking down large PDFs and corporate documents for AI retrieval.
Introduction to Vector Databases (Pinecone, ChromaDB).
Building a secure, offline document-chat system using open-source models.

AI Workflow Automation for IT Operations

Integrating Generative AI directly into the Software Development Life Cycle (SDLC).
Automating code reviews, unit test generation, and pull request summaries.
Using AI to translate legacy code (e.g., migrating old PHP to modern Node.js).
Automating server log analysis and infrastructure anomaly detection.
Building Zapier/Make automations supercharged by LLM decision-making.

AI Ethics, Governance & Enterprise Strategy

Navigating data privacy: Understanding SOC2 compliance and GDPR in the age of AI.
Open-source vs. Closed-source: Choosing the right model for enterprise data security.
Implementing guardrails to prevent AI from sharing sensitive intellectual property.
Calculating API costs and managing token optimization for scale.
Designing a company-wide AI adoption strategy and training non-technical staff.

Capstone Project & Career Placement

End-to-End Capstone: Building a fully functional Agentic Workflow or Custom AI Tool tailored to solve a specific Surat IT industry problem.
Packaging your AI solutions into an impressive GitHub portfolio and video demonstrations.
Crafting a resume that highlights Prompt Engineering, Agent Orchestration, and API integrations.
Interview preparation: Defending your architecture choices and demonstrating AI ROI to business leaders.
Networking and positioning yourself as a Lead AI Integrator in the local tech ecosystem.

Why Choose Extrabits for Generative AI & Prompt Engineering Bootcamp Training?

At Extrabits Academy, we provide the best Generative AI & Prompt Engineering Bootcamp course in Surat, offering more than just theory — we provide an opportunity to enhance your career with practical knowledge and live project experience.

🎓 Learn from Industry Experts

Gain insights from professionals with years of real-world experience.

💻 Hands-On, Practical Learning

Work on live projects and build a portfolio that stands out.

📅 Flexible Learning Options

Choose from weekend or weekday batches to suit your schedule.

🏗️ Build a Strong Foundation

Master core concepts and advanced techniques in modern technology.

💼 Real-World Projects

Apply your skills to solve real business problems through case studies.

🏆 Get Certified

Earn a recognized certificate to boost your career opportunities.