Do I need machine learning experience?

No, we focus on using and integrating existing AI models rather than building them from scratch. Basic programming knowledge is sufficient.

Which AI models will we work with?

We work with popular models including GPT, Claude, and open-source alternatives, teaching you how to integrate and use them effectively.

Will I learn to build AI chatbots?

Yes, building AI chatbots and conversational agents is a major component of the course.

Is this course focused on theory or practical applications?

We focus heavily on practical applications. You'll build real AI-powered projects throughout the course.

Build real AI features with LLMs and prompt engineering

Integrate models safely into apps: prompts, RAG, tool calling, and deployment basics

without getting lost in pure theory.

4.8+(Course feedback)

1000+ students trained

Hands-on labs with popular model APIs
Prompt patterns you can reuse
RAG and app integration projects
Responsible AI and guardrails

Limited seats per cohort — we cap batches for live Q&A.

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Live Instructor-Led Sessions
Real-World Industry Projects
Interview & Placement Guidance

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Real Results from Our Students

Shipping assistants, RAG workflows, and automation—outcomes from learners applying AI on real tasks.

1000+ students trained
Hands-on real projects
Industry-focused training

Featured story

I went from tutorial loops to a real project on my resume—callbacks turned into interview conversations I could steer.

Amit R.

Developer, Hyderabad

Shortlisted 4× after capstone

Mentor feedback on my code mattered more than theory. I shipped a cleaner portfolio and stopped freezing in technical rounds.

Kavya N.

Engineer, Pune

Offer after 2nd serious interview

Small cohort meant I wasn’t competing for airtime—I fixed real gaps and walked into the next role with proof, not promises.

Vikram P.

Consultant, Remote

Promoted within 6 months

Course Overview

Learn to leverage Generative AI technologies including Large Language Models, prompt engineering, and building AI applications. Discover how to integrate AI into your projects, fine-tune models, and build intelligent applications that leverage the power of modern AI.

Prerequisites

Basic programming knowledge
Understanding of APIs
Familiarity with web technologies

Delivery Modes

Online

Live project walkthroughs
Hands-on labs with AI APIs
Recorded sessions for revision

Offline

Classroom labs with guided exercises
Group brainstorming and prototyping
On-site mentor support

Course Details

Duration

35 hours

Level

Intermediate

Format

Online & Offline

Learning Outcomes

Understand how LLMs work and their capabilities
Master prompt engineering for optimal results
Build AI-powered applications and chatbots
Implement responsible AI practices

Your instructor

Learn from industry practitioners

Real-world delivery experience—not just slides.

TechNet Faculty

Industry practitioners with hands-on delivery experience

Our instructors focus on practical workflows used in real projects—not slides alone.

Hands-on labs and mentor feedback
Curriculum aligned with workplace tasks
Support for building your portfolio

Certifications & focus areas

Domain-relevant delivery
Hands-on mentoring
Project-based learning

Detailed Course Curriculum

A structured, real-world curriculum designed to build job-ready skills step by step.

Module 1: AI Foundations

6 hours

Generative AI concepts and terminology
LLM capabilities, limitations, and costs
AI safety and responsible usage

Module 2: Prompt Engineering

8 hours

Prompt patterns and best practices
Few-shot and chain-of-thought prompting
Evaluation and iteration workflows

Module 3: Building AI Apps

10 hours

API integration with popular models
Retrieval-augmented generation (RAG)
Tool calling and structured outputs

Module 4: Deployment & MLOps Basics

6 hours

Latency, cost, and caching strategies
Monitoring and safety guardrails
Deployment workflows

Module 5: Capstone Project

5 hours

AI assistant or chatbot build
Evaluation metrics and feedback loops
Presentation and demo day

Download full curriculum PDF

Includes real projects, interview questions, and step-by-step roadmap. Enter your details below to download the PDF.

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What You'll Learn

This comprehensive course covers all essential topics to make you proficient

1Introduction to Generative AI and LLMs

2Large Language Models (GPT, Claude, etc.)

3Prompt engineering techniques and strategies

4Fine-tuning and model customization

5Building AI-powered applications

6Ethics and responsible AI practices

7Integration with existing systems and APIs

8Future trends and emerging technologies

Course Benefits

Everything you need to learn effectively and stand out in real-world roles.

1Hands-on projects with real AI APIs

2Prompt engineering frameworks and templates

3Production-ready AI integration patterns

4Ethics and responsible AI guidance

5Portfolio projects for AI roles

Projects You'll Build

Hands-on projects designed to build a strong portfolio

1RAG-based knowledge assistant

2AI content summarizer with evaluation

3Prompt-driven automation workflow

Download Curriculum PDF

Get the full course curriculum, module breakdown, and learning outcomes in a downloadable PDF. Includes real projects, interview questions, and step-by-step roadmap.

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