Posted in: Special Course

3-Month Computer Course Syllabus: Generative AI


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
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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…

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