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.

When does the next batch start?

Please request the current batch details. Confirm the start date, session timings and delivery mode before enrolling.

Can learners from Nadiad attend?

Yes. Choose live online training or ask about attending the classroom in Anand. TechNet has no physical training centre in Nadiad.

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.

Live training(Anand and online)

Instructor-led learning

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

Teaching hours are separate from the number of calendar days needed to complete the course.

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Use the syllabus and your own goals to decide whether this course is the right next step. These are planning notes, not learner testimonials.

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Learning focus

Choose a practical problem you want to solve. Compare the topics below with your current experience and the skills you want to develop.

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Course planning

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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. Want stronger programming foundations for AI-related work? Review the Python Programming syllabus and prerequisites to decide whether it is the right starting point.

Prerequisites

Basic programming knowledge
Understanding of APIs
Familiarity with web technologies

Choose Your Learning Format

Live online

Join instructor-led sessions live online and practise with course exercises.
Confirm the available batch format, timetable and software requirements before enrolling.
Ask whether recordings and other review materials are included in your selected batch. Request Course and Batch Details.

Classroom in Anand

F-6, 1st Floor, Vihang Trade Center, Mota Bazaar, Vallabh Vidyanagar, Anand, Gujarat 388120.
Confirm the classroom timetable and venue before your first visit.
Learners from Nadiad can join online or attend in Anand. TechNet has no physical training centre in Nadiad. Request Course and Batch Details.

Course Details

Teaching hours

35 hours

Level

Intermediate

Format

Live online & Classroom in Anand

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 learning plan

Discuss your course with TechNet

Confirm the trainer, timetable and support before enrolling.

TechNet Training Team

Course and batch enquiries

Share your experience, learning goals and availability. Ask about the assigned trainer, teaching approach and support included in your selected batch before enrolling.

Discuss your current experience
Review practice requirements
Confirm support and feedback arrangements

Course focus areas

Introduction to Generative AI and LLMs
Large Language Models (GPT, Claude, etc.)
Prompt engineering techniques and strategies

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.

Frequently Asked Questions

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