igmGuru's Generative AI Course builds practical skills in Large Language Models, prompt engineering, RAG, and AI agents through instructor-led training, hands-on projects, and certification guidance for beginners and working professionals.
✅ Level - Beginner to Advanced ✅ 35-Hour Instructor-Led Training ✅ 100% Practical LLM, RAG & Prompt Engineering Projects and Use Cases ✅ Industry-Recognized Generative AI Certification ✅ Hands-on LangChain, Vector Database & AI Agent Labs ✅ Experienced Generative AI & Data Science Trainers ✅ Tutor - Ravi Singh
Generative AI is reshaping how businesses create content, automate workflows, and build intelligent products, and igmGuru's Generative AI Course helps you keep pace with this shift. Across 35 hours of live, instructor-led sessions, you move from Core AI and Machine Learning Concepts to advanced topics such as Large Language Models, Prompt Engineering, Retrieval-Augmented Generation, AI Agents, and Enterprise deployment. The training blends conceptual clarity with hands-on labs, so you build real applications instead of only watching demonstrations. Whether a fresher, working professional, or business leader, this course prepares you for practical, in-demand Generative AI roles.
Generative AI has moved from an experimental technology to a core part of how enterprises build products, serve customers, and make decisions. In 2026, organizations across banking, retail, healthcare, and technology are actively hiring professionals who can work with Large Language Models, design reliable prompts, build Retrieval-Augmented Generation pipelines, and deploy AI agents that reason and act with minimal supervision. Industry reports continue to show strong year-on-year growth in AI hiring, and Generative AI-specific skills command a noticeable salary premium over generalist AI or software roles. At the same time, tools such as ChatGPT, Claude, and Gemini have become everyday utilities inside marketing, engineering, and operations teams, making Generative AI literacy relevant for technical and non-technical professionals alike. Learning it now means getting ahead of a curve that is still rising, rather than catching up to one that has already flattened out.
By the end of this course, you will be able to design, build, and deploy real-world Generative AI applications with confidence. This program is built to help you:
This course takes you step by step from AI fundamentals to advanced, job-ready Generative AI skills, including:
This Generative AI course is designed for a wide range of learners, including:
By the time you complete this training, you will have hands-on command over:
Completing this course opens doors to a wide range of in-demand Generative AI careers, such as:
Generative AI professionals are in growing demand across technology, consulting, finance, healthcare, and other industries. Salaries vary based on experience, location, technical skills, job role, and organization. The following table provides salary benchmarks for Generative AI-related roles in India and the USA.
| Generative AI Job Role | India - Average/Typical Salary | USA - Average/Typical Salary |
|---|---|---|
| Generative AI Engineer | ₹9 LPA base pay | $152,868/year |
| AI/ML Engineer | ₹6-₹25 LPA | $152,868/year |
| AI Developer | ₹8-₹20 LPA | $152,462/year |
| Senior Generative AI / AI Engineer | ₹14-₹30+ LPA | $180,000-$250,000+* |
Note: Salary figures are based on available market data from Glassdoor and Indeed. Actual compensation can vary based on experience, location, employer, technical expertise, bonuses, and equity.
igmGuru has trained thousands of professionals across AI and emerging technologies, and here is what makes this Generative AI course worth your time:
Generative AI Trainer
Ravi is a software engineer and AI workflow consultant with over 15 years of experience in full-stack development, Software Development, Machine Learning, and applied Generative AI. Over the last few years, he has worked extensively with Large Language Models and modern AI frameworks, helping engineering and product teams at startups and enterprises design, fine-tune, and deploy Generative AI applications, from prompt engineering and RAG pipelines to AI agent orchestration and production-grade model deployment.
On completing igmGuru's Generative AI Course, you receive a course Completion Certificate that reflects your practical skills in LLMs, prompt engineering, RAG, and AI agent development. The certificate is shareable on LinkedIn and in professional portfolios, and it is grounded in the hands-on project work completed during training rather than a single closed-book exam.
If you who want an additional globally recognized credential can pursue independent certifications from providers such as Google Cloud, Microsoft Azure, or OpenAI, building on the practical foundation this course provides.
Generative AI is a type of artificial intelligence that can create new content such as text, images, code, audio, and video. It learns patterns from existing data and uses them to produce contextually relevant, human-like outputs.
The training helps learners understand how to apply Gen AI to practical business needs such as knowledge retrieval, workflow improvement, customer interactions, content operations, data analysis, and AI-powered applications.
Yes, the course exposes learners to multiple AI ecosystems and concepts, helping them understand how to work across different models rather than depending on a single AI platform.
Using an AI tool generally means interacting with an existing model, while building a Gen AI application involves connecting models with APIs, data sources, databases, workflows, and application logic. The course focuses on the latter as well.
Yes. Gen AI is being applied across areas such as marketing, analytics, product management, content operations, automation, finance, healthcare, retail, and other business functions. The course is therefore relevant to both technical and business-oriented learners.
Look for training that goes beyond basic AI-tool usage and covers model concepts, application development, evaluation, data retrieval, model customization, deployment considerations, and hands-on implementation. A practical curriculum is more useful than one focused only on theory.
It can provide a practical foundation for moving toward roles such as Generative AI Engineer, AI Application Developer, LLM Integration Specialist, AI Automation Engineer, and AI Product Specialist. Your existing technical or domain experience will also influence which role is the best fit.
Continue by building small AI applications, experimenting with different models, following model and framework updates, improving evaluation practices, and applying Gen AI to problems relevant to your current industry or role.
Basic knowledge of programming languages like Python is helpful but not mandatory. We cover foundational implementation steps clearly.
Yes. After completing the Generative AI online course, you can build practical projects using LLMs, APIs, RAG, prompt engineering, and AI frameworks. The hands-on learning helps you turn concepts into working AI applications for real-world use cases.
Yes. Our comprehensive curriculum is fully updated to include Agentic AI. You will move beyond basic prompt engineering and RAG to learn how to design, build, and deploy multi-agent systems using cutting-edge frameworks like LangGraph and CrewAI for end-to-end workflow automation.
Nice training
Experience good
Comprehensive and Practical oriented
Good training session
Learning Experience
