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.
Program Description
Skills You'll Learn
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
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.
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.
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.
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.
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.
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
What You'll Learn
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 |
Internship Details
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
Certificate Preview
Related Internships
You might also be interested in these
Our Students Did It! 🎉 Certified & Proud
A big congratulations to our students who recently completed their courses and earned their certificates. Here's what they have to say! 🎓
Our Certificate Samples
Internship Certificate
Tap to view
Joining Letter
Tap to view
Student ID Card
Tap to view
Student Panel
Tap to view
All certificates are issued by NextVision Infotech & are verifiable upon request.
Ready to Start Your Journey?
Take the first step towards your dream career with our internship programs