Hyderabad, India
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Build practical skills with Eduzek's Generative AI course in India, designed for students, software developers, data professionals and working IT professionals. Learn Generative AI fundamentals, Large Language Models (LLMs), prompt engineering, embeddings, vector databases, Retrieval-Augmented Generation (RAG), LLM fine-tuning and Agentic AI. Gain hands-on exposure to modern AI development frameworks, real-world application workflows and deployment concepts. With structured learning, practical projects and instructor-led training options, this program helps you develop the technical foundation to build AI-powered applications and explore emerging opportunities in artificial intelligence.
Generative AI is transforming how businesses develop software, automate processes, analyze information and build intelligent digital experiences. From conversational assistants and AI-powered search to document processing and workflow automation, Generative AI is creating new possibilities across industries.
Eduzek's Generative AI course in India introduces learners to the technologies and development techniques behind modern AI applications. The training covers Generative AI fundamentals, Large Language Models (LLMs), prompt engineering, embeddings, vector databases, Retrieval-Augmented Generation (RAG), LLM application development, fine-tuning concepts and Agentic AI.
Rather than focusing only on using AI tools, the learning path emphasizes understanding how AI-powered applications are designed and developed. Learners explore frameworks and technologies used to connect language models with data sources, APIs, retrieval systems and task-oriented workflows.
The curriculum also introduces AI agents, multi-agent systems, model evaluation and application deployment concepts. Practical project work helps learners connect theoretical knowledge with real-world development scenarios.
Whether you are a student exploring artificial intelligence, a developer looking to integrate LLMs into applications, or an IT professional planning to expand your technical skills, this Generative AI training program provides a structured starting point.
If you are specifically looking for location-focused instruction, explore Eduzek's [Generative AI Training in Hyderabad](https://www.eduzek.com/generative-ai-training-hyderabad) for course details, syllabus information, training formats and practical learning opportunities.
Build foundational knowledge of Generative AI, Python, machine learning, LLMs and AI application development while developing practical projects for your portfolio.
Learn to integrate Large Language Models into applications, implement RAG pipelines, connect AI models with APIs and build intelligent software features.
Explore how Generative AI can extend existing software development skills through LLM-powered applications, AI assistants, enterprise search and workflow automation.
Develop practical skills in prompt engineering, embeddings, vector databases, LangChain, LangGraph, RAG and AI agent development.
Expand your capabilities into LLM applications, semantic search, retrieval systems, model evaluation, fine-tuning and AI-powered data solutions.
Understand modern Generative AI architectures and learn how AI models, APIs, retrieval systems and intelligent workflows can support business applications.
Explore Generative AI, transformers, LLMs, vector databases, multimodal AI and emerging AI development frameworks through structured training.
Follow a structured learning path from programming and AI fundamentals to LLM application development, RAG, AI agents and deployment concepts.
Develop a conversational application using a Large Language Model, prompt engineering and API integration to generate useful responses to user queries.
Build a document question-answering system that processes files, creates embeddings, retrieves relevant passages and generates context-aware responses.
Create a semantic search solution using text embeddings and a vector database to retrieve information based on meaning rather than exact keyword matches.
Develop a chatbot that connects an LLM with a curated knowledge base to answer questions using relevant source information.
Explore model adaptation workflows, dataset preparation, fine-tuning concepts and parameter-efficient techniques such as LoRA and QLoRA.
Build an AI agent that uses tools and structured workflows to handle a multi-step task, combining model outputs with application logic.
Explore a multi-agent workflow in which specialized agents coordinate research, organize information and prepare a structured result.
Combine LLM integration, tools, retrieval and agent workflows into an end-to-end AI application, with evaluation and deployment concepts.
| Course Name | Generative AI and Agentic AI Training |
|---|---|
| Training Mode | Live Online Group Training; 1:1 and Corporate Training options |
| Course Level | Beginner to Advanced |
| Course Duration | 100–130 hours (indicative; confirm the current batch schedule) |
| Certification | Course completion certificate |
| Prerequisites | Basic programming familiarity is helpful. Python fundamentals are covered as part of the learning path. |
| Who Can Join | Students, freshers, software developers, IT professionals, data professionals and AI/ML enthusiasts |
| Core Technologies | Python, NLP, Large Language Models, prompt engineering, embeddings, RAG and vector databases |
| AI Development Frameworks | LangChain, LangGraph, LangSmith, AutoGen, CrewAI and MCP |
| Fine-Tuning Technologies | LoRA, QLoRA, quantization and Hugging Face ecosystem |
| Deployment and Monitoring | FastAPI, Streamlit, Gradio, Docker and LLM application observability |
| Hands-On Learning | Practical AI applications, RAG workflows, AI agent development and an end-to-end AI agent capstone |
| Training Formats | Group Batch, 1:1 Training and Corporate Batch |
| Course Fees | Contact Eduzek for current fees, batch availability and training-format options. |
Progress from Python, machine learning and NLP foundations to LLMs, RAG, fine-tuning, AI agents and deployment concepts through a structured learning journey.
Connect concepts with hands-on development activities involving LLM-powered applications, retrieval systems, chatbots, AI agents and end-to-end workflows.
Learn through instructor-led sessions designed to explain AI concepts, development techniques and practical implementation scenarios.
Explore both content-generating AI systems and agentic workflows that use tools, context, retrieval and structured execution to perform multi-step tasks.
Explore relevant tools and frameworks, including LangChain, LangGraph, vector databases, Hugging Face, FastAPI and Docker, according to the confirmed course plan.
Build foundational understanding before progressing toward more advanced LLM application development, model adaptation and agent-based systems.
Explore group, 1:1 and corporate training options based on your learning goals, schedule and team requirements.
Receive a course completion certificate and focus on practical projects that can help demonstrate your learning and technical capabilities.
Generative AI is creating new ways to build software applications, automate business processes, work with enterprise knowledge and develop intelligent digital products. As organizations explore Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI assistants and agent-based workflows, professionals with practical AI development skills can explore opportunities across software engineering, artificial intelligence, data and automation.
Completing a Generative AI course can help you understand the technologies behind AI-powered applications and develop skills that complement your existing technical background. Career opportunities depend on your programming experience, practical project portfolio, technical proficiency and the requirements of individual employers.
Career Roles After a Generative AI Course
1. Generative AI Engineer
Work on applications powered by generative models and LLMs. Relevant skills include prompt engineering, LLM integration, RAG pipelines, model evaluation and AI application development.
2. AI Engineer
Develop software solutions that integrate AI models, APIs, retrieval systems and intelligent workflows into existing products and business applications.
3. LLM Engineer
Focus on Large Language Model integration, prompting, model evaluation, application architecture, fine-tuning concepts and efficient model usage.
4. RAG Engineer
Design retrieval-augmented systems that connect language models to external documents, enterprise knowledge bases and structured information. Relevant skills include document processing, embeddings, vector databases and retrieval evaluation.
5. Agentic AI Engineer
Develop AI agents that use tools, context and structured workflows to carry out multi-step tasks. Knowledge of LangGraph, LangChain, multi-agent systems and agentic RAG can support this specialization.
6. AI Application Developer
Build practical applications such as AI chatbots, intelligent document assistants, enterprise search systems, customer-support tools and AI-powered productivity features.
7. NLP and Conversational AI Engineer
Work with natural language processing, text representations, transformers and language models to build conversational interfaces and language-based applications.
8. AI Automation Engineer
Explore opportunities to connect LLMs, APIs, AI agents and business applications to streamline repetitive tasks and support workflow automation.
9. Machine Learning Engineer with Generative AI Skills
Extend existing machine learning knowledge into LLMs, generative models, retrieval systems, fine-tuning and AI-powered application development.
10. AI Solutions Developer
Translate business requirements into AI application designs by evaluating models, retrieval architectures, agent frameworks and integration approaches.
Build the Skills Behind These Career Paths
Preparing for AI-focused roles requires more than familiarity with AI tools. Focus on Python programming, LLM fundamentals, prompt engineering, embeddings, RAG, vector databases, model evaluation, application development and deployment. Practical projects can help demonstrate how these technologies work together to solve real problems.
For learners who want structured, location-specific instruction, explore Eduzek's Generative AI Training in Hyderabad. The program covers LLMs, prompt engineering, RAG, AI agents and application development, with instructor-led training and practical learning opportunities.
Explore Generative AI and Agentic AI Together
Generative AI helps produce content and responses, while Agentic AI extends these capabilities through tools, planning, memory and task-oriented workflows. Learning both areas can help developers understand a broader range of AI application architectures.
Learners interested in building intelligent agents can also explore Eduzek's Agentic AI Course and Training in India to learn more about agent development, LangGraph, multi-agent workflows and related technologies.
Turn Learning into Practical Experience
A course is a starting point, not a guarantee of employment. Strengthen your skills by building a portfolio of practical applications, documenting your design decisions, evaluating model outputs and learning how to deploy reliable solutions.
With a structured Generative AI learning path, you can develop a stronger technical foundation and explore how LLMs, RAG, AI agents and automation are applied to real-world software development.
“I would like to thank Ganesh for his excellent training in PowerApps and Power Automate. Shout out to his patience and knowledge. Ganesh is extremely dedicated, knowledgeable, and professional. He delivered more than what he promised in the demo session and cleared all my doubts. Worth the money!”
“Eduzek is a great platform to learn Power BI, PowerApps, and Power Automate for working professionals. The course tutorial and duration are designed in a perfect way. The teaching staff is very supportive and flexible in terms of class timing.”
“Eduzek helped me in learning Power Automate. I just completed my training and you can reach Ganesh anytime in case of queries and get them resolved, which I liked the best.”
“Excellent training from Ganesh on PowerApps, Power Automate, and SharePoint. I highly recommend Eduzek institute to get trained on these topics.”
“Good training and clearing the doubts with live project examples...”
A Generative AI course teaches the concepts and technologies used to build applications that generate content, understand language and perform AI-assisted tasks. Topics can include Large Language Models, prompt engineering, embeddings, RAG, vector databases, fine-tuning, AI agents and application deployment.
Students, freshers, software developers, IT professionals, data professionals and AI/ML enthusiasts can explore Generative AI training. Basic programming familiarity is helpful, while Python fundamentals can be learned as part of the training path.
Basic programming knowledge is helpful. Prior professional experience in Generative AI is not necessarily required for a beginner-friendly learning path. Learners should confirm the current batch prerequisites with Eduzek before enrolling.
Eduzek lists an indicative duration of 100–130 hours for its Generative AI and Agentic AI training. The actual schedule, session frequency and completion timeline may vary by batch and training format.
Generative AI course fees depend on the training provider, curriculum, duration, trainer availability and training format. Contact Eduzek for current fees and a quote for group, 1:1 or corporate training.
Eduzek lists a course completion certificate for its Generative AI and Agentic AI training. Confirm the current certification requirements and completion criteria with the training team.
The proposed learning path includes Python and AI foundations, NLP, Large Language Models, prompt engineering, embeddings, vector databases, RAG, LLM fine-tuning concepts, LangChain, LangGraph, AI agents and deployment. Exact modules and projects should be confirmed with Eduzek for the selected batch.
Eduzek offers live online group training for its Generative AI and Agentic AI program. The provider also lists 1:1 and corporate training options, with delivery arrangements depending on the selected format.
LLMOps focuses on the practices used to evaluate, deploy, monitor and maintain applications powered by Large Language Models. Relevant areas include testing, observability, performance monitoring, deployment workflows and responsible AI practices. These topics complement practical LLM application development.
An LLM fine-tuning course explores how pretrained language models can be adapted for particular tasks or datasets. Topics may include dataset preparation, supervised fine-tuning, parameter-efficient methods such as LoRA and QLoRA, quantization and model evaluation.
Generative AI training can be valuable for learners who want to understand LLM-powered applications and develop practical AI engineering skills. The value depends on the quality of the curriculum, hands-on experience, your existing background and how consistently you apply your learning to real projects.
Depending on your existing experience and demonstrated skills, Generative AI knowledge can support career paths such as Generative AI Engineer, AI Engineer, LLM Engineer, RAG Engineer, AI Application Developer and AI Automation Engineer. Completing a course alone does not guarantee a particular job or salary.
Eduzek's published Generative AI curriculum includes Retrieval-Augmented Generation (RAG), embeddings and vector database technologies such as Pinecone, FAISS and Milvus. These technologies are used to retrieve relevant information for LLM-powered applications.
Eduzek's Generative AI and Agentic AI training includes AI agent development, agent workflows and frameworks such as LangGraph, AutoGen and CrewAI. The published course information also describes an end-to-end AI agent capstone project.
Yes. Software developers can use Generative AI training to learn how to integrate LLMs into applications, build RAG pipelines, connect APIs, develop AI assistants and explore agent-based workflows. These skills can complement existing programming experience.
Visit Eduzek's Generative AI Training in Hyderabad page for location-specific course information, syllabus details, training formats and enquiries: https://www.eduzek.com/generative-ai-training-hyderabad.