5-Day Training Course Agenda on Generative AI
Course Title: Mastering Generative AI: Techniques, Tools, and Applications
Duration: 5 Days (Full-Day Sessions)
Target Audience: AI Practitioners, Data Scientists, Developers, Digital Creators, and Business Leaders
Day 1: Introduction to Generative AI and Fundamental Concepts
- Morning Session (9:00 AM – 12:00 PM)
- Welcome and Course Overview
- Introduction to the agenda, course objectives, and learning outcomes
- Overview of generative AI and its growing importance
- Understanding AI and Generative Models
- Differences between discriminative and generative models
- Key concepts: supervised, unsupervised, and reinforcement learning
- Introduction to probability distributions and their role in generation tasks
- Afternoon Session (1:00 PM – 4:00 PM)
- Types of Generative Models
- Overview of different models: Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), Transformers, and Diffusion Models
- Use cases and applications of each model
- Generative AI in Action: Real-World Applications
- Content generation (text, image, music)
- Code generation, design, and product innovation
- Industry use cases: Healthcare, Finance, and Entertainment
Day 2: Deep Dive into Generative Models (GANs, VAEs, and More)
- Morning Session (9:00 AM – 12:00 PM)
- Generative Adversarial Networks (GANs)
- Understanding the architecture of GANs (generator vs. discriminator)
- Training GANs: Loss functions, optimization challenges, and techniques
- Hands-on examples: Training basic GANs to generate images
- Variational Autoencoders (VAEs)
- VAE architecture: Encoder, decoder, and latent space
- Applications of VAEs in data generation and anomaly detection
- Comparison of VAEs with GANs: Strengths and weaknesses
- Afternoon Session (1:00 PM – 4:00 PM)
- Hands-On Workshop: Building and Training Generative Models
- Practice training a VAE model using a sample dataset
- Exploring latent spaces and generating new samples from learned representations
- Hybrid and Advanced Models
- Combining GANs and VAEs: How hybrid models work
- Recent advances in generative modeling (e.g., Diffusion Models, Neural Radiance Fields)
Day 3: Generative Transformers and Large Language Models (LLMs)
- Morning Session (9:00 AM – 12:00 PM)
- Introduction to Transformers
- Understanding the transformer architecture and self-attention mechanism
- Sequence-to-sequence models and applications in NLP
- How transformers revolutionized language generation (BERT, GPT, T5)
- Large Language Models (LLMs)
- Overview of GPT-3, GPT-4, and other large pre-trained models
- Fine-tuning and zero-shot/few-shot learning
- Ethical considerations: Bias, misinformation, and over-reliance on LLMs
- Afternoon Session (1:00 PM – 4:00 PM)
- Hands-On Workshop: Text Generation with Transformers
- Building a text generator using GPT models
- Prompt engineering and fine-tuning to create specific outputs
- Evaluation of Generative Models
- Methods for evaluating text generation quality (perplexity, BLEU score, etc.)
- Challenges in evaluating creative AI outputs (subjectivity, coherence)
Day 4: Generative AI for Images, Audio, and Beyond
- Morning Session (9:00 AM – 12:00 PM)
- Generative AI for Images
- Image generation models: StyleGAN, DALL·E, and MidJourney
- Deepfakes: How they work, ethical concerns, and detection methods
- Image inpainting, style transfer, and AI-powered art creation
- Generative AI for Audio and Music
- AI models for music generation (WaveNet, Jukedeck, OpenAI’s Jukebox)
- Speech synthesis, voice cloning, and generative audio tools
- Applications in podcasting, video games, and virtual assistants
- Afternoon Session (1:00 PM – 4:00 PM)
- Hands-On Workshop: Generating Images and Audio
- Using a pre-trained GAN for image generation
- Experimenting with AI-driven music and sound synthesis
- Future of Generative AI in Media and Creative Industries
- How AI is transforming digital art, music production, and video creation
- Monetization of AI-generated content and new business models
Day 5: Ethics, Future Trends, and Practical Applications of Generative AI
- Morning Session (9:00 AM – 12:00 PM)
- Ethical and Societal Implications of Generative AI
- Addressing AI bias, data privacy, and fairness in generative models
- Ethical concerns: Deepfakes, misinformation, and AI misuse
- Responsible AI usage: Ensuring transparency and accountability
- Generative AI and Digital Transformation
- How businesses can leverage generative AI for innovation
- AI’s role in content creation, marketing, and customer engagement
- Case studies: Generative AI driving digital transformation in various industries
- Afternoon Session (1:00 PM – 4:00 PM)
- Hands-On Capstone Project: Building a Generative AI Solution
- Teams work on building a generative AI solution for a specific business case (e.g., text generation for customer service, AI-driven marketing campaigns, generative design)
- Presentations and peer feedback on project outputs
- Wrap-Up and Certification
- Review of key learnings
- Final Q&A and discussions on future trends in generative AI
- Course completion and distribution of certificates
Learning Outcomes:
By the end of the 5-day course, participants will:
- Understand the fundamental principles behind generative AI models such as GANs, VAEs, and transformers.
- Gain hands-on experience in training and fine-tuning generative models for text, images, and audio.
- Learn the practical applications of generative AI across industries like media, entertainment, and business.
- Be aware of ethical considerations and societal impacts of generative AI technology.
- Develop skills in leveraging AI tools for creativity, automation, and innovation in their respective fields.
TO JOIN THE COURSE….MAIL TO
mail@institute-of-it-trainings.com
+91 9811841782