Generative AI Course In Jaipur- DAAC

Course Feature

Generative AI

Duration 3 Months
Class Timings 1.5 hour a day, 5 days a week
Eligibility

DAAC Artificial Intelligence Course Jaipur

Course Features

Duration: 3 months
Students:Max 10
Skill LeveAdvanced
LanguageEnglish / Hindi
Opening10am to 7pm
ClassesOn System

Generative AI Training Institute in Jaipur

Our Generative AI Training Institute in Jaipur is a leading facility for talent development, geared towards the creation of high-level performers who can effectively harness AI-driven innovation. The program includes a future-ready curriculum covering Large Language Models (LLMs), transformer architectures, diffusion models, prompt engineering strategies, and enterprise-grade GenAI applications. By combining conceptual understanding with systematic skill development, the course equips students with a solid grounding in contemporary AI ecosystems, thus making it a perfect choice for a generative AI course in Jaipur or if you are planning to develop GenAI skills of high market value.

To fast track workforce readiness, trainees are involved in real-world projects, live model deployment experiments, and industry-standard capstone tasks that simulate actual business environments. Such a comprehensive, result-oriented structure of the program allows participants to turn theoretical learning into practical operational impact; hence, they become capable of leading automation, innovation, and digital transformation initiatives in any industry. Due to its cutting-edge training model, skilled instructor-led sessions, and intense hands-on exposure, the institute is consistently ranked among the best generative AI training institutes in Jaipur, thus leading to the setting of a standard for quality GenAI education and skill enhancement.

Why Enroll in DAAC for a Generative AI Course in Jaipur?

DAAC is recognized as a premier platform that people use to develop their next-gen skills in Generative AI. The institute provides a practical curriculum, expert-led training, and exposure to projects that are tailored to the industry. Through state-of-the-art facilities and a robust placement mechanism, DAAC imparts not only technical skills but also professional readiness to the learners. Its steady output ranks it high among the Best Generative AI Training Institutes in Jaipur and hence, it is a reliable option for career progression in GenAI.

1 Industry-Driven Generative AI Curriculum: DAAC features an industry-aligned and future-oriented curriculum that has been designed to meet the rapidly growing demand for GenAI skills. The program consists of modules on LLMs, transformer frameworks, diffusion models, and AI deployment workflows. As a result, the program has become an ideal option for individuals looking for the Best Generative AI Course in Jaipur or a specialized Generative AI Training Institute in Jaipur.

2. Hands-On Training With Real-Time GenAI Projects: The learners accomplish an extensive project that is an immersion into the practical aspect of the content, a live implementation session, and a scenario-based simulation that are all designed to be a part of the industry use cases. Being hands-on, the structure of the program guarantees that the learners get applied proficiency in prompt engineering, LLM fine-tuning, vector databases, and AI automation pipelines, i.e., the key skill set that is required in a GenAI-driven work environment of today.

3. Expert Mentors With Deep Domain Experience: Experienced AI practitioners, data scientists, and GenAI specialists are the course faculty members who lead the sessions and bring their strong domain expertise and real-world insights to each session. Under their supervision, the learners fasten the learning outcomes and also achieve the technical maturity that is necessary for enterprise-level AI frameworks.

4. Career-Centric Training and Placement Ecosystem: DAAC places strong emphasis on gearing up for a career through different activities like classes on job readiness, mock interviews, portfolio work, and placement assistance. The well-structured system of the organization augments the chances of being hired and opens up access to positions such as GenAI Engineer, Prompt Engineering Specialist, AI Automation Analyst, and LLM Integration Expert in leading tech companies.

5. Strong Learning Infrastructure and Market Credibility: By providing cutting-edge AI labs, state-of-the-art learning environments, and high-quality technology training over the years, DAAC has been able to establish itself among the best generative AI training institutes in Jaipur. Learners have the advantage of a solid infrastructure, a highly effective methodology, and a reputation that can be a stepping stone for their future career in the AI field.

Career Opportunities

The Generative AI ecosystem is growing fast and thus, a large number of professionals with skills in technology, automation, analytics, and product innovation are required. Firms in IT, consulting, fintech, healthcare, and digital platforms are recruiting employees who can handle LLMs, prompt engineering, and AI-driven workflows. Winners can open the door to high-growth positions such as Generative AI Engineer, Prompt Engineering Specialist, AI Automation Analyst, and LLM Integration Expert if they have the right capabilities. This field is packed with long-term career security, attractive wages, and the possibility of moving from one industry to another for people with advanced GenAI skills.

Key Career Paths in Generative AI

1. Generative AI Engineer: An engineer who is responsible for the design, training, and optimization of generative AI models, including LLMs, diffusion models, and transformer-based systems for enterprise applications.

2. Prompt Engineering Specialist: They are the experts who develop, improve, and optimize the prompts to produce quality outputs from large models used in automation, content creation, and decision-support tools.

3. AI Automation Analyst: They are the specialists who implement generative AI-powered workflows into business processes, thus driving operational efficiency and cost optimization across functions.

4. LLM Integration Expert: The individuals who are in charge of incorporating large language models into products, platforms, and applications to not only facilitate but also to intelligently system-user interaction.

5. AI Product Strategist: Positions that are directed towards the creation, blueprinting, and administration of AI-fueled products or services within technology-driven companies.

6. NLP and ML Research Associate: Junior and middle-level positions involved in the support of research models, handling data pipelines, fine-tuning models, and performing AI experiments for continuous improvement.

The career transition to such roles as a consequence of enterprise adoption is rapid, and hence, they provide a potent salary increase, flexibility to transfer across different industries, and future-proof career opportunities, which, in turn, makes skill development in GenAI a strategic long-term success investment.

MODULE - 1

Introduction to Generative AI & LLMs

Foundations & Core Concepts

History & evolution of generative models (GPT-4, GPT-5, Gemini, Llama)
Transformers architecture, attention, tokenization, and sequence modeling
Embeddings: what they are and how they power similarity & retrieval
Model types: autoregressive LLMs, encoder-decoder, diffusion & multimodal models
Use-cases: summarization, Q&A, content generation, code assistants, search augmentation

Practical Labs

Calling an LLM API (OpenAI / Gemini) — building your first chat prompt
Experimenting with prompts, system vs user messages, multi-turn context

Minor Lab & Quiz

MODULE - 2

Prompt Engineering

Prompt Design & Advanced Patterns

Basic prompt crafting, constraints, and instruction clarity
Chain-of-Thought prompting and decomposition strategies
Role prompts, templates, and prompt libraries
Function calling & structured outputs (JSON, SQL, CSV)
Prompt-level safety: guardrails, hallucination mitigation, and rate-aware prompting

Practical Labs

Design multi-turn prompts for knowledge-heavy tasks (e.g., product support bot)
Create prompt templates and measure prompt performance

Minor Lab & Project

MODULE - 3

OpenAI, Gemini & Claude — API Development

Working with Provider APIs

OpenAI API fundamentals: chat, completions, function calling, and best practices
Google Gemini API: features, multimodal inputs, and streaming responses
Anthropic Claude basics: safety-first prompts and conversation control
Cost & latency considerations; caching strategies
Secure API usage: keys, rate limits, and monitoring

Practical Labs

Build a small chat application using FastAPI + OpenAI/Gemini backend
Implement function calling and JSON output parsing

Minor Lab & Project

MODULE - 4

LangChain & AI Agents

LangChain Patterns & Agent Design

Introduction to LangChain: chains, tools, memory, and agents
Chains & sequential workflows: LLMChain, SequentialChain, MapReduce
Memory strategies: buffer, summary, and vector memory
Building tools for LLMs (SQL runner, calculators, scrapers)
Creating and orchestrating agents (ReAct, tool-using agents, multi-tool agents)

Practical Labs

Build an agent that answers product & documentation queries using tools + vector DB
Agent testing, sandboxing, and failure modes

Minor Lab & Project

MODULE - 5

Vector Databases & RAG Systems

RAG Architecture & Vector Stores

What is RAG and why it’s crucial for production LLM systems
Document chunking, embeddings, and similarity search
Vector DB options: Pinecone, Chroma, Weaviate, PGVector (pros/cons)
Hybrid search: vector + keyword retrieval & reranking
Context window management, retrieval strategies, and latency trade-offs

Practical Labs

Build a RAG pipeline: ingest docs, embed, store, query, answer
Optimize retrieval prompts and evaluate answer quality

Minor Lab & Project

CAPSTONE

Industry-Grade Projects & Deployment

Capstone Projects (Portfolio Ready)

Project 1 — RAG-Powered Knowledge Assistant (docs + search + chat) using LangChain + Pinecone
Project 2 — AI Agent that automates a business workflow (email summarization + task creation)
Project 3 — Multimodal Q&A (text + images) using Gemini/OpenAI vision models
Project 4 — Deploy LLM App: FastAPI + Docker + CI/CD (basic monitoring & cost controls)
Final demo, code review, documentation & deployment walkthrough

Final Project Assessment & Certificate

Artificial Intelligence Training in Jaipur by DAAC

Why choose DAAC for Generative AI Training In Jaipur

DAAC provides hands-on labs, mentor-led projects, and a job-aligned curriculum focused on building production-ready generative AI systems. Our faculty are industry practitioners who emphasize practical implementation, deployment, and risk-aware AI practices.

Hands-on experience with live projects.
We help you obtain generative AI training, certifications, & jobs in Jaipur.
We offer free demo sessions.
Experienced faculty.
Both practical and theoretical classes are taught.

Artificial Intelligence Classes at DAAC Jaipur

We Will Contact You, At a Time Which Suits You Best

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Benefits of Learning Generative AI Course

Work on high-demand skills: LLMs, RAG, vector DBs, agents.
Build portfolio-ready AI products.
Practical MLOps & deployment experience.
Roles: AI Engineer, Prompt Engineer, RAG Engineer, Agent Builder.
Learn responsible AI & safety best practices.

Professional Artificial Intelligence Course Jaipur DAAC

FAQ

Most Comment Question?

Generative AI uses models (LLMs, diffusion models, multimodal models) to generate text, images, audio, and more. This course is ideal for engineers, data scientists, product builders, automation specialists, and technical managers who want to build production AI applications.

Basic Python knowledge is recommended but we cover practical essentials. The course focuses on applied engineering patterns rather than deep theoretical ML math. Prior programming experience helps but is not strictly required.

You'll work with OpenAI, Google Gemini (APIs), LangChain, Hugging Face, Pinecone/Chroma/Weaviate/PGVector, Docker, FastAPI, and common Python libraries. Optional demo cloud credits or sandbox accounts may be provided for labs.

Yes. The course includes deployment best practices (Docker, FastAPI), cost controls, basic monitoring & logging, and CI/CD for model-backed applications to help you safely ship LLM applications.

Standard program duration is 3 months with flexible batches. The course includes capstone projects, mentor reviews, interview prep, and placement assistance connections.

The program is tailored to students, professionals, people who want to change their careers, and tech-loving people who desire to develop strong skills in AI, LLMs, and GenAI-driven applications. No deep technical background is necessary—just basic computer knowledge and some of your time.

The syllabus is packed with up-to-date projects, real-time model deployment labs, and hands-on exercises in areas like prompt engineering, LLM fine-tuning, and AI automation workflows. In this way, each learner will acquire operational, job-ready skills.

DAAC provides planned placement support to students, such as interview preparations, resume and portfolio building, and helping them to get jobs at tech, consulting, and AI-driven companies. This assistance constitutes a bridge for the learners to move to high-demand Generative AI roles with a feeling of self-assurance.