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Generative AI - 45 Days Internship Training Program

Join 45 Days Generative AI Internship Training Program at NextVision Infotech. Learn LLMs, prompt engineering, RAG, LangChain, fine-tuning. ₹649 only with certificate.

45 Days
Anywhere in India • Patna • (Offline & Online)
INT-AIDS-GENAI-45D
Generative AI - 45 Days Internship Training Program Banner

Program Description

NextVision Infotech presents a comprehensive Generative AI Internship Training Program spanning 45 days. This intensive program is designed for students across all disciplines - B.Tech, B.E., BCA, MCA, B.Sc., Diploma, and other technical streams - who want to build a strong foundation in generative AI and large language models. The program covers the complete generative AI lifecycle from fundamentals to advanced applications. Students will learn generative AI fundamentals, large language models, prompt engineering, transformers, diffusion models, GANs, VAEs, fine-tuning, RAG, LangChain, and AI application development. Over six weeks, the program progresses from fundamentals to advanced generative AI. Week 1 introduces generative AI and LLM fundamentals. Week 2 covers prompt engineering and LLM APIs. Week 3 focuses on transformers and attention mechanisms. Week 4 covers diffusion models, GANs, and VAEs. Week 5 is dedicated to fine-tuning, RAG, LangChain, and live projects. Week 6 covers deployment, documentation, viva, and certification. The program follows industry-standard workflows used by professional AI engineers across India. Students work on real-world projects including chatbots, content generators, image generators, and AI assistants. The curriculum draws inspiration from premier technical institutions across India and follows professional generative AI standards used in the tech industry. Students gain practical skills that prepare them for careers in generative AI, LLM engineering, and AI product development. This program is delivered both online and offline, allowing students from any state or city across India to enroll and benefit. The institute is ISO 9001:2015 certified, and the internship certificate is accepted by universities, colleges, and companies throughout the country. Upon successful completion, students receive an Internship Certificate, Industrial Training Certificate, Project Completion Certificate, and an Offer Letter. Learning outcomes include mastering generative AI, prompt engineering, LLM fine-tuning, RAG, LangChain, and building AI applications.

Skills You'll Learn

Generative AI
Large Language Models
Prompt Engineering
Transformers
Attention Mechanisms
Diffusion Models
GANs
VAEs
Fine-Tuning
LoRA
PEFT
RAG
LangChain
LlamaIndex
Vector Databases
OpenAI API
Hugging Face
Streamlit
Gradio

Projects You'll Work On

Complete Generative AI Project

Students will complete a full generative AI project including LLM integration, prompt engineering, RAG implementation, vector database setup, LangChain agents, fine-tuning, deployment, and complete project documentation as per industry standards.

Program Modules

1

W1: Week 1: Generative AI and LLM Fundamentals

Introduction to generative AI, discriminative vs generative models, history of generative AI, applications of generative AI - text, image, audio, video, code generation, generative AI landscape, large language models (LLMs), LLM architecture, GPT, BERT, T5, LLaMA, Claude, Gemini, Mistral, open-source vs closed-source LLMs, tokenization, embeddings, context window, temperature, top-k, top-p, hallucination, LLM limitations, ethics in generative AI, responsible AI.

2

W2: Week 2: Prompt Engineering and LLM APIs

Prompt engineering fundamentals, prompt design principles, zero-shot prompting, few-shot prompting, chain-of-thought prompting, tree-of-thought, self-consistency, role prompting, instruction prompting, prompt templates, prompt optimization, prompt injection, prompt security, LLM APIs - OpenAI API, Anthropic API, Google Gemini API, Hugging Face API, API authentication, API parameters, API rate limits, API cost optimization, streaming responses, function calling, structured outputs, JSON mode.

3

W3: Week 3: Transformers and Attention Mechanisms

Transformer architecture, encoder-decoder architecture, self-attention, multi-head attention, positional encoding, feed-forward networks, layer normalization, residual connections, BERT architecture, GPT architecture, T5 architecture, encoder-only models, decoder-only models, encoder-decoder models, attention visualization, transformer variants, efficient transformers, long-context transformers, Hugging Face Transformers library, model loading, tokenizer, model inference, model fine-tuning basics.

4

W4: Week 4: Diffusion Models, GANs, and VAEs

Generative models overview, autoencoders, variational autoencoders (VAEs), generative adversarial networks (GANs), GAN architecture, generator, discriminator, GAN training, GAN variants - DCGAN, WGAN, StyleGAN, CycleGAN, Pix2Pix, diffusion models, denoising diffusion probabilistic models (DDPM), stable diffusion, latent diffusion, diffusion model architecture, text-to-image generation, image-to-image generation, inpainting, outpainting, upscaling, controlnet, LoRA, DreamBooth, image generation tools - Stable Diffusion, DALL-E, Midjourney, Leonardo AI.

5

W5: Week 5: Fine-Tuning, RAG, LangChain, and Live Projects

Fine-tuning fundamentals, full fine-tuning, parameter-efficient fine-tuning (PEFT), LoRA, QLoRA, adapter layers, prefix tuning, prompt tuning, fine-tuning datasets, fine-tuning evaluation, retrieval-augmented generation (RAG), RAG architecture, document loading, text splitting, embeddings, vector databases - Pinecone, Weaviate, ChromaDB, FAISS, Qdrant, retrieval, re-ranking, generation, RAG evaluation, LangChain fundamentals, chains, agents, tools, memory, callbacks, LangChain expressions (LCEL), LlamaIndex, live projects - chatbot, document Q&A, content generator, code assistant, image generator, complete documentation.

6

W6: Week 6: Deployment, Documentation, Viva, and Certification

Model deployment, LLM deployment, API deployment, Streamlit, Gradio, FastAPI, cloud deployment - AWS, GCP, Azure, Hugging Face Spaces, Docker, MLOps for generative AI, LLMOps, model monitoring, cost optimization, project documentation, resume building, interview preparation, viva-voce examination, feedback session, certificate distribution.

Key Features

45 Days Comprehensive Training
Industry-Standard Curriculum
Live GenAI Projects
Professional Portfolio Development
ISO 9001:2015 Certified Institute
Offer Letter Provided
Internship Certificate Included
Industrial Training Certificate
Project Report Guidance
Viva-Voce Preparation
Online & Offline Mode
Pan-India Enrollment

What You'll Learn

Master generative AI and LLM fundamentals
Apply prompt engineering techniques
Understand transformer architecture
Work with diffusion models and GANs
Fine-tune LLMs using PEFT and LoRA
Implement RAG systems
Build applications with LangChain
Deploy generative AI applications
Build a professional GenAI portfolio
Prepare for generative AI jobs across India

Examination Details

Exam Name Full Marks Pass Marks
Module-wise Assessment 100 40
Project Evaluation 100 50
Final Presentation 50 25
Viva-Voce 50 25
Generative AI - 45 Days Internship Training Program

Internship Details

Duration 45 Days
Location Anywhere in India • Patna • (Offline & Online)
Available Seats 100
Course Code INT-AIDS-GENAI-45D
Apply Now — ₹649

Prerequisites

  • Pursuing or completed B.Tech/B.E./BCA/MCA/B.Sc. in Computer Science, IT, or related field
  • Basic knowledge of Python programming
  • Basic knowledge of machine learning concepts
  • Interest in generative AI

Who Can Enroll ?

  • B.Tech Computer Science students (1st to 8th semester)
  • B.E. IT students
  • BCA students (1st to 6th semester)
  • MCA students
  • B.Sc. Computer Science students
  • AI enthusiasts
  • Working professionals wanting to upskill
  • Students from all over India seeking practical training

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