Course Title:
Mastering Generative AI: From Foundations to Applications
Duration:
3 Months (12 Weeks)
Mode:
Online/Offline with Hands-on Projects
Objective:
Equip students with theoretical and practical knowledge of Generative AI, enabling them to create AI models for text, images, audio, and video generation.
Course Outline
Module 1: Introduction to Generative AI (Weeks 1–2)
Objective: Build a foundational understanding of Generative AI and its applications.
- Week 1:
- What is Generative AI?
- Overview of Machine Learning & Deep Learning
- Types of Generative Models (GANs, VAEs, Transformers)
- Ethical Considerations and Bias in AI
- Week 2:
- Introduction to Python for AI
- Setting up AI Development Environment (Jupyter, Colab)
- Basic Data Preprocessing Techniques
- Introduction to TensorFlow & PyTorch
Module 2: Natural Language Processing (NLP) & Text Generation (Weeks 3–5)
Objective: Learn NLP fundamentals and build text-generating models.
- Week 3:
- Basics of NLP (Tokenization, Lemmatization, POS Tagging)
- Intro to Pre-trained Models (GPT, BERT, ChatGPT)
- Fine-tuning Text Generation Models
- Week 4:
- Building a Chatbot using OpenAI API
- Text Summarization and Sentiment Analysis
- Prompt Engineering and Response Optimization
- Week 5:
- Hands-on Project: Create an AI Blog Writer
- Feedback Session & Model Optimization
Module 3: Image Generation & Manipulation (Weeks 6–8)
Objective: Develop skills to create and manipulate images using Generative AI.
- Week 6:
- Introduction to Generative Adversarial Networks (GANs)
- Types of GANs: DCGAN, StyleGAN
- Training Your First GAN for Image Generation
- Week 7:
- Image-to-Image Translation (Pix2Pix, CycleGAN)
- Introduction to DALL·E & MidJourney
- Fine-Tuning Pre-trained Image Models
- Week 8:
- Hands-on Project: Create AI-Generated Artwork
- Ethical Implications of AI-Generated Art
Module 4: Audio and Video Generation (Weeks 9–10)
Objective: Explore the generation of audio and video content using AI models.
- Week 9:
- Audio Synthesis using AI (WaveNet, Jukebox)
- Voice Cloning and Speech Synthesis Techniques
- Week 10:
- Introduction to DeepFake Technology
- Video Generation using GANs and AI Tools
- Hands-on: Generate AI-powered Podcasts or Videos
Module 5: Real-World Applications & Deployment (Weeks 11–12)
Objective: Apply learned skills to real-world projects and prepare models for deployment.
- Week 11:
- Integrating AI Models into Web Applications
- Cloud Deployment (AWS, Azure, Google Cloud)
- API Development for AI Models
- Week 12:
- Final Project Presentation & Peer Review
- Best Practices for Maintaining AI Models
- Course Recap and Future Trends in Generative AI
Assessment & Certification
- Assignments: Weekly assignments to reinforce learning.
- Projects: Two major hands-on projects (Text and Image/Audio Generation).
- Final Exam: A comprehensive assessment covering all modules.
- Certification: Awarded upon successful completion of the course.
Prerequisites:
- Basic programming knowledge (preferably Python)
- Familiarity with Machine Learning basics (optional but recommended)
Resources & Tools
- Software: Python, TensorFlow, PyTorch, OpenAI API, DALL·E, Jupyter Notebook
- Hardware: Access to GPU-enabled cloud services (optional for large models)
This course is designed to prepare students for roles in AI development, research, and creative industries involving AI-driven innovations.
Coming Soon…