Applied Generative AI and its Applications

Description

Objective:
This program provides an immersive and hands-on journey into the fast-evolving field of
Generative Artificial Intelligence (GenAI). Students will explore the foundations of generative
models, understand how to build, and fine-tune them using modern frameworks, and create
real-world applications across art, language, music, design, and product innovation. The Applied
Generative AI and its Applications (GenAI) program delivers an immersive, hands-on learning
experience in the rapidly evolving field of Generative Artificial Intelligence. Students will explore
the theoretical foundations and practical applications of generative models across multiple
domains including art, language, music, design, and product innovation.
Through a combination of lectures, labs, projects, and real-world deployments, students will
learn to build, fine-tune, and operationalize generative models using cutting-edge tools such as
TensorFlow, PyTorch, Hugging Face, LangChain, and popular generative platforms like DALL·E,
Stable Diffusion, and ChatGPT.
The program emphasizes the development of skills in multimodal AI (text, vision, audio),
LLMOps, Retrieval-Augmented Generation (RAG), voice cloning, autonomous AI agents, and
ethical governance of AI systems. Students will gain experience in deploying real-world
applications using Streamlit, FastAPI, Hugging Face Spaces, and cloud-based MLOps workflows.
Graduates will be prepared for careers as Generative AI Engineers, LLM Application Designers,
Creative AI Developers, AI Researchers, and Prompt Engineers, with the ability to drive
innovation across industries such as technology, media, gaming, e-commerce, and creative arts.

Preparation for Job Market & Entrepreneurship
Graduates will be equipped for roles such as:
• Generative AI Engineer
• Creative AI Developer
• LLM Application Designer
• AI Researcher / AI Artist
• Prompt Engineer for GenAI Workflows
Students will gain hands-on experience in:
• Python, TensorFlow, Keras, PyTorch, Hugging Face, Google Colab, LangChain
• GANs, VAEs, Diffusion Models, DALL·E, Stable Diffusion, Midjourney, ChatGPT
• Multimodal AI – including Text-to-Image, Text-to-Video, and Speech synthesis
• LLMOps, RAG, Prompt Engineering, Agentic Workflows
• Deployment using Streamlit, FastAPI, Gradio, Hugging Face Spaces

Emerging & Future Skills
This course includes exploration and projects in:
• Prompt Engineering & Prompt Tuning
• LLMOps & Retrieval-Augmented Generation (RAG)
• Real-Time Speech-to-Text & Multilingual Generation
• Multimodal AI (Text + Vision + Audio)
• Voice Cloning, Emotion Detection & Sound Synthesis
• AI Agents using ReAct, CrewAI, LangGraph
• AI Content Safety & Ethics in Generative Systems
• AI for Storytelling, Game Design, Creative Media, and UX
• Low-code/No-code AI tooling (Uizard, Galileo, RunwayML)

Learning Modality
• In-person Instructor-led: $4,999
• Virtual Live Instructor-led: $3,199
• 1-on-1 Personalized Mentorship: $5,999

Admissions Requirements
• High school diploma or GED
• Familiarity with Python programming
• Creative/technical interest in AI tools
• Completion of NVIT admissions interview