The Agentic Developer Course: Master AI-Assisted Full-Stack Engineering– Live Training
(Master AI Assisted Coding, Prompt Engineering, React, FastAPI & Production Deployment)
Master the future of software development with our The Agentic Developer Course: Master AI-Assisted Full-Stack Engineering program — a hands-on course designed to help you build modern, intelligent applications using AI-powered development tools and industry-leading technologies.
This program combines Python development, Generative AI, Prompt Engineering, Full Stack Development, and AI-assisted coding workflows to prepare you for the next generation of software engineering careers.
You will start with Python fundamentals, developer tools, Git, APIs, and modern development environments. Then, you’ll explore the exciting world of Artificial Intelligence, Large Language Models (LLMs), Agentic AI, and Prompt Engineering to understand how modern AI systems work and how developers can effectively interact with them.
The course provides practical experience with GitHub Copilot and Claude Code, enabling you to build real-world AI-assisted applications faster and smarter. You will learn how to create responsive frontends using React or modern JavaScript frameworks, develop scalable backends with Python FastAPI, and integrate databases using PostgreSQL.
About the Instructor:
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Yesh is an experienced AI and Automation professional with over 10 years of IT industry experience, having worked on enterprise-level projects across product-based and global technology environments. Over the years, he has specialized in AI-powered engineering, intelligent workflow automation, and Agentic AI solutions, helping professionals adopt next-generation AI technologies in real-time enterprise environments. His strong industry exposure and practical implementation approach make his sessions highly hands-on, industry-oriented, and aligned with current market demands. Yesh currently delivers advanced live training programs on AI Agent Bootcamp: Master N8N and Workflow Automation, The Agentic Developer Course: Master AI-Assisted Full-Stack Engineering, ISTQB Certified AI Tester – Advanced QA with AI & ML, and AI Agents Engineering Course – Live Training. His core training areas include AI agents, workflow orchestration using n8n, LLM integrations, prompt engineering, AI-assisted development, intelligent automation, AI-driven testing strategies, and real-time AI workflow implementation. He focuses heavily on practical use cases, live project scenarios, event-driven automations, and modern AI engineering concepts that help learners build production-ready AI solutions. Teaching and mentoring have always been Yesh’s passion, and he has successfully trained and mentored more than 300+ professionals through live interactive sessions, workshops, and real-time project-based learning programs. Known for his practical teaching style and simplified explanation of complex AI concepts, he has helped many working professionals transition into AI-focused roles and modern engineering domains. Passionate about continuous learning and innovation, Yesh aims to empower learners with future-ready AI and automation skills required to succeed in rapidly evolving technology landscapes. |
Sample Videos:
The Agentic Developer Course- Live Training Demo Video:
The Agentic Developer Course- Live Training Day 1 Video:
Live Sessions Price:
For LIVE sessions – Offer price after discount is 300 USD 109 USD or 25000 INR 8,900 Rupees
OR
Free Day 1 On:
Indian Timings: 10th June @ 9 PM – 10 PM (IST)/
U.S Timings: 10th June @ 11:30 AM – 12:30 PM (EST)/
U.K Timings: 10th June @ 4:30 PM – 5:30 PM (BST)
Class Schedule:
For participants in India: Monday to Friday @ 9 PM – 10 PM (IST)
For participants in US: Monday to Friday @ 11:30 AM – 12:30 PM (EST)
For participants in UK : Monday to Friday @ 4:30 PM – 5:30 PM (BST)
What Students Say about the trainer:
| ⭐ The trainer explained The Agentic Developer Course: Master AI-Assisted Full-Stack Engineering concepts in a very simple and practical way. I learned Python, FastAPI, React, and AI tools like GitHub Copilot with real-time examples. The hands-on sessions were excellent. – Kumar
⭐ Excellent course for learning Full Stack Development with AI tools like GitHub Copilot and Claude Code. The trainer covered Prompt Engineering, LLMs, and backend development simply. Real-time projects helped me improve my coding skills. Great learning experience overall. – Priya ⭐ The practical sessions and real-world projects made learning AI-assisted development very easy. – Joshi ⭐ One of the best industry-focused training programs I have attended. The course covered both full-stack development and modern AI tools in detail. The trainer supported us throughout the practical sessions and projects. I gained hands-on experience in React, FastAPI, and PostgreSQL integration. The learning environment was interactive and professional. – Sneha ⭐ The trainer provided clear explanations and real-world examples throughout the course. I gained strong knowledge in AI-assisted application development. – Vijaya |
Who can enroll for this course?
- 20 Hours of Live Training along with recorded videos
- Lifetime access to the recorded videos
- Course Completion Certificate
What will I learn by the end of this course?
Module 1: Python & Dev Environment Bootcamp
- Python essentials for AI: functions, loops, APIs, JSON, async/await
- Setting up VS Code, GitHub Copilot, virtual environments, API keys
- Git basics — committing, pushing, branching
Module 2: The AI Landscape & LLM Foundations
- The story of AI → ML → Deep Learning → GenAI → Agentic AI
- Why now?
- How LLMs work — tokens, context windows, temperature, model families (GPT, Claude, Gemini)
- Limitations of LLMs alone → why agents exist
- Agent lifecycle — Perceive → Reason → Act → Observe
- Agent types (ReAct, Plan & Execute)
Module 3: Prompt Engineering Mastery
- System prompt design — roles, constraints, personas
- Chain-of-Thought (CoT) + Few-shot prompting
- Tree-of-Thought (ToT) + Self-consistency
- Structured outputs — JSON mode, output parsers, schema enforcement
Module 4: AI Assisted Full Stack App with GitHub Copilot
- Introduction to GitHub Copilot — how it works, pricing, IDE setup
- Copilot Chat vs inline suggestions — when to use which
- Copilot for understanding existing code — explain, document, refactor
- Build Frontend using React — components, state, props, API calls
- Style the UI with Tailwind CSS — let Copilot generate component styles
- Build a Backend using Python FastAPI — routes, request/response models, middleware
- Authentication with FastAPI — JWT tokens, protected routes (Copilot-assisted)
- Implement a Database Layer using PostgreSQL — tables, queries, relationships
- Using SQLAlchemy ORM with Copilot — models, migrations, CRUD operations
- Connect Frontend → Backend → Database as a working full stack flow
- Mini Project: AI-Assisted Task Manager App (Full Stack, Copilot-built end to end)
Module 5: AI Assisted Full Stack App with Claude Code
- Introduction to Claude Code — what it is, how it differs from Copilot, CLI setup
- Claude Code vs GitHub Copilot — strengths, weaknesses, when to use each
- Using Claude Code for greenfield projects — scaffolding from a description
- Build Frontend using React — Claude Code generates components from plain English specs
- Build a responsive UI with Claude Code — forms, tables, dashboards
- Build a Backend using Python FastAPI — Claude Code writes routes, validation, error handling
- Ask Claude Code to write tests — unit tests and integration tests for your API
- Implement a Database Layer using PostgreSQL
- Claude Code manages schema design and writes migration scripts
- Debugging with Claude Code — paste errors, get fixes, understand the why
- Mini Project: AI-Assisted Expense Tracker App (Full Stack, Claude Code-built end to end)
Module 6: Deployment & DevOps with AI Assistance
- Deployment options compared — Vercel (frontend), Railway/Render (backend), Supabase (DB)
- Deploying your React frontend to Vercel — CI/CD from GitHub
- Deploying your FastAPI backend — environment variables, health checks, logs
- Connecting a production PostgreSQL database — Supabase or Neon setup
- Using Claude Code and Copilot to write Dockerfiles and deployment configs
- Domain, SSL, and going live checklist
- Project: Deploy your complete full stack AI app — live URL you can share on your portfolio
How can I enroll for this course?
OR
For any other details, Call me or Whatsapp me on +91-9133190573
Live Sessions Price:
For LIVE sessions – Offer price after discount is 300 USD 109 USD or 25000 INR 8,900 Rupees
Sample Course Completion Certificate:
Your course completion certificate looks like this….
Important Note:
To maintain the quality of our training and ensure a smooth learning experience for all participants, we do not allow batch repetition or switching between courses.
To reiterate, moving from one course to another or shifting from one trainer to another (even if it is the same course) is not possible. Changing batches or trainers in any form is strictly not permitted.
We request all learners to attend the scheduled sessions regularly and make the most of their learning journey. Thank you for your understanding and continued support.
Course Features
- Lectures 42
- Quiz 0
- Duration 20 hours
- Skill level All levels
- Language English
- Students 472
- Assessments Yes
- 6 Sections
- 42 Lessons
- 20 Hours
- Module 1: Python & Dev Environment Bootcamp3
- Module 2: The AI Landscape & LLM Foundations6
- 2.1The story of AI → ML → Deep Learning → GenAI → Agentic AI
- 2.2Why now?
- 2.3How LLMs work — tokens, context windows, temperature, model families (GPT, Claude, Gemini)
- 2.4Limitations of LLMs alone → why agents exist
- 2.5Agent lifecycle — Perceive → Reason → Act → Observe
- 2.6Agent types (ReAct, Plan & Execute)
- Module 3: Prompt Engineering Mastery4
- Module 4: AI Assisted Full Stack App with GitHub Copilot11
- 4.1Introduction to GitHub Copilot — how it works, pricing, IDE setup
- 4.2Copilot Chat vs inline suggestions — when to use which
- 4.3Copilot for understanding existing code — explain, document, refactor
- 4.4Build Frontend using React — components, state, props, API calls
- 4.5Style the UI with Tailwind CSS — let Copilot generate component styles
- 4.6Build a Backend using Python FastAPI — routes, request/response models, middleware
- 4.7Authentication with FastAPI — JWT tokens, protected routes (Copilot-assisted)
- 4.8Implement a Database Layer using PostgreSQL — tables, queries, relationships
- 4.9Using SQLAlchemy ORM with Copilot — models, migrations, CRUD operations
- 4.10Connect Frontend → Backend → Database as a working full stack flow
- 4.11Mini Project: AI-Assisted Task Manager App (Full Stack, Copilot-built end to end)
- Module 5: AI Assisted Full Stack App with Claude Code11
- 5.1Introduction to Claude Code — what it is, how it differs from Copilot, CLI setup
- 5.2Claude Code vs GitHub Copilot — strengths, weaknesses, when to use each
- 5.3Using Claude Code for greenfield projects — scaffolding from a description
- 5.4Build Frontend using React — Claude Code generates components from plain English specs
- 5.5Build a responsive UI with Claude Code — forms, tables, dashboards
- 5.6Build a Backend using Python FastAPI — Claude Code writes routes, validation, error handling
- 5.7Ask Claude Code to write tests — unit tests and integration tests for your API
- 5.8Implement a Database Layer using PostgreSQL
- 5.9Claude Code manages schema design and writes migration scripts
- 5.10Debugging with Claude Code — paste errors, get fixes, understand the why
- 5.11Mini Project: AI-Assisted Expense Tracker App (Full Stack, Claude Code-built end to end)
- Module 6: Deployment & DevOps with AI Assistance7
- 6.1Deployment options compared — Vercel (frontend), Railway/Render (backend), Supabase (DB)
- 6.2Deploying your React frontend to Vercel — CI/CD from GitHub
- 6.3Deploying your FastAPI backend — environment variables, health checks, logs
- 6.4Connecting a production PostgreSQL database — Supabase or Neon setup
- 6.5Using Claude Code and Copilot to write Dockerfiles and deployment configs
- 6.6Domain, SSL, and going live checklist
- 6.7Project: Deploy your complete full stack AI app — live URL you can share on your portfolio
