Technology Training · Artificial Intelligence
Generative AI Training
Build with large language models and image generators — prompting, retrieval-augmented generation (RAG), fine-tuning concepts and AI agents.
- Python
- LLM APIs
- LangChain
- LlamaIndex
Course overview
Generative AI Training Overview
Generative AI training explains how large language models (LLMs) and diffusion models create text, code and images, and how to use them to build practical applications.
You work with LLM APIs, prompt design, embeddings and vector search, retrieval-augmented generation (RAG) and agent workflows, along with evaluation, safety and cost considerations.
Course syllabus
What You'll Learn in Generative AI Training
- How generative models and LLMs work
- Transformers, tokens and embeddings
- Prompt design for reliable outputs
- Working with LLM APIs from Python
- Embeddings and vector databases
- Retrieval-augmented generation (RAG)
- Fine-tuning and model customisation concepts
- AI agents, tools and workflows
- Image generation with diffusion models
- Evaluation, safety, privacy and cost control
Tools & technologies
Tools & Technologies Covered
- Python
- LLM APIs
- LangChain
- LlamaIndex
- Hugging Face
- Vector databases
- Jupyter Notebook
Who should join?
Who Should Join Generative AI Training?
Developers
Build chatbots, assistants and AI features into products.
Data scientists
Extend your ML skills to large language models.
Product & business teams
Identify and prototype generative AI use cases.
Students & graduates
Learn one of the most in-demand skills in technology today.
Prerequisites: Basic Python programming is recommended. Prior machine learning knowledge is helpful but not required.
Career paths
Career Opportunities After Generative AI Training
Common roles for professionals with Generative AI skills:
- 01Generative AI Engineer
- 02LLM Application Developer
- 03AI Product Developer
- 04Prompt Engineer
- 05AI Solutions Architect
Career outcomes depend on your background, practice and the job market. We focus on practical skills and do not promise guaranteed placement.
FAQ
Generative AI: Frequently Asked Questions
What will I learn in the Generative AI course?
The Generative AI training covers how generative models and LLMs work, Transformers, tokens and embeddings, prompt design for reliable outputs, working with LLM APIs from Python, embeddings and vector databases, retrieval-augmented generation (RAG), fine-tuning and model customisation concepts, AI agents, tools and workflows, image generation with diffusion models and evaluation, safety, privacy and cost control.
Which tools are covered in Generative AI training?
You will work with Python, LLM APIs, LangChain, LlamaIndex, Hugging Face, Vector databases and Jupyter Notebook.
Who can join the Generative AI course?
The course suits developers, data scientists, product & business teams and students & graduates. Basic Python programming is recommended. Prior machine learning knowledge is helpful but not required.
What jobs can I apply for after learning Generative AI?
Common roles include Generative AI Engineer, LLM Application Developer, AI Product Developer, Prompt Engineer and AI Solutions Architect. Career outcomes depend on your background, practice and the job market.
How do I get the Generative AI syllabus, duration, fees and batch details?
Contact us on WhatsApp or through the enquiry form and our team will share the current Generative AI syllabus, course duration, fees and upcoming batch details.
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Ready to Start Generative AI Training?
Talk to our team about the Generative AI syllabus, course duration, fees and upcoming batch details.
Generative AI course | GenAI training | LLM course | RAG training