Overview
This extensive course is a gateway to the world of Generative AI, providing participants with a solid foundation and advanced knowledge of Generative AI principles, technologies, and applications. Participants will navigate through modules dedicated to specific aspects of Generative AI, such as image and audio generation, encoder-decoder architecture, and the attention mechanism in transformer models. The course is enriched with hands-on labs and interactive sessions, ensuring participants acquire practical skills and experience in working with Generative AI for real-world applications.
Why this
course?
- Gain a thorough understanding of the fundamentals and advanced concepts of Generative AI.
- Acquire practical skills in working with various Generative AI models including transformer and encoder-decoder architectures.
- Explore the applications of Generative AI in audio and video, with hands-on experience on platforms like Eleven Labs, RunwayML, and PikaLabs.
- Understand the intricacies of image generation techniques, including working with ProGAN, SRGan, CycleGAN, and Diffusion Models.
- Master the art of prompt tuning and learn to effectively utilize Generative AI development tools for optimal results.
- Engage in interactive labs and workshops, enhancing practical skills and gaining insights into real-world Generative AI applications.
This enriched learning journey is tailored to empower participants with the knowledge, skills, and confidence to excel in the dynamic field of Generative AI, driving innovation and creating value in their respective domains.
Curriculum
Lessons:
- Definition of Generative AI.
- How Generative AI Works.
- Overview of Generative AI Model Types.
- Exploring Generative Applications.
- Hands-on session: Exploring the basics of Generative AI.
- Interactive exercises: Understanding different Generative AI models.
- Understand the basic concepts and definitions of Generative AI.
- Gain insights into how Generative AI works and its various model types.
Lessons:
- Definition of Large Language Models.
- Exploring LLM Use Cases.
- Understanding Prompt Tuning.
- Overview of Generative AI Development Tools.
- Hands-on workshop: Working with Large Language Models.
- Interactive exercises: Experimenting with prompt tuning and development tools.
- Understand the concept and definition of Large Language Models.
- Gain insights into LLM use cases and prompt tuning.
Lessons:
- Introduction to Attention Mechanism.
- Understanding Transformer Models.
- Exploring Encoder-Decoder Arrangements.
- Hands-on session: Working with Attention Mechanism.
- Interactive exercises: Exploring its role in transformer models and encoder-decoder arrangements.
- Understand the attention mechanism.
- Gain practical experience with transformer models and encoder-decoder arrangements.
Lessons:
- Overview of Transformer Architecture.
- Deep Dive into the BERT Model.
- Hands-on workshop: Exploring Transformer Architecture.
- Interactive exercises: Working with the BERT Model.
- Understand the architecture of Transformer Models.
- Gain practical experience with the BERT Model.
Lessons:
- Introduction to Approaches in Image Generation.
- Working with Variational Autoencoders.
- Exploring GANs, ProGAN, SRGan, and CycleGAN.
- Understanding Diffusion Models (Stable Diffusion, Clipdrop, LeonardoAI, Midjourney).
- Hands-on workshop: Creating images using different generative models.
- Interactive exercises: Experimenting with various image generation techniques.
- Understand various approaches in image generation.
- Gain hands-on experience with variational autoencoders, GANs, and other generative models.
Lessons:
- Overview of Image Captioning Models Components.
- Training and Evaluating a Model.
- Generating Captions for Images.
- Hands-on session: Working with Image Captioning Models.
- Interactive exercises: Training and generating captions for images.
- Understand the components of Image Captioning Models.
- Gain practical experience in training and generating captions for images.
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Lab:
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After completing this module, students will be able to:
Lessons:
- Introduction to Encoder-Decoder Architecture.
- Training and Generating Text Using Encoder-Decoder Architecture.
- Writing Encoder-Decoder Model Using Keras.
- Hands-on workshop: Working with Encoder-Decoder Architecture.
- Interactive exercises: Writing encoder-decoder models using Keras.
- Understand the Encoder-Decoder Architecture.
- Gain hands-on experience in training and generating text using Encoder-Decoder Architecture.
Lessons:
- Overview of Generative AI in NLP.
- Exploring Text Generation Techniques.
- Understanding Text Summarization.
- Hands-on workshop: Working with text generation techniques.
- Interactive exercises: Experimenting with text summarization.
- Understand the application of Generative AI in NLP.
- Gain practical experience in text generation and summarization.
Lessons:
- Introduction to Generative AI in Audio.
- Exploring Audio Synthesis with Eleven Labs.
- Understanding Audio Modification Techniques.
- Hands-on session: Working with audio synthesis on Eleven Labs.
- Interactive exercises: Experimenting with audio modification techniques.
- Understand the application of Generative AI in audio.
- Gain practical experience in audio synthesis and modification using Eleven Labs.
Lessons:
- Overview of Generative AI in Video.
- Exploring Video Synthesis with RunwayML and PikaLabs.
- Understanding Video Editing Techniques.
- Hands-on workshop: Working with video synthesis on RunwayML and PikaLabs.
- Interactive exercises: Experimenting with video editing techniques.
- Understand the application of Generative AI in video.
- Gain hands-on experience in video synthesis and editing using RunwayML and PikaLabs.
Lessons:
- Introduction to Advanced Generative AI Techniques.
- Exploring Fine-Tuning in Generative AI.
- Understanding Optimization Techniques.
- Hands-on session: Working with fine-tuning in Generative AI.
- Interactive exercises: Experimenting with optimization techniques.
- Understand advanced techniques in Generative AI.
- Gain practical experience in fine-tuning and optimization in Generative AI.
Lessons:
- Overview of Challenges in Generative AI.
- Exploring Potential Solutions.
- Understanding the Future of Generative AI.
- Hands-on workshop: Addressing challenges in Generative AI.
- Interactive exercises: Discussing potential solutions and the future of Generative AI.
- Understand the challenges faced in Generative AI.
- Explore potential solutions to overcome these challenges.
Lessons:
- Overview of Ethics in Generative AI.
- Understanding the Responsibilities.
- Exploring Ethical Dilemmas and Solutions.
- Interactive session: Discussing ethical scenarios in Generative AI.
- Group discussions: Sharing insights on responsibilities and solutions.
- Understand the ethical considerations in Generative AI.
- Explore the responsibilities and potential solutions to ethical dilemmas.
Lessons:
- Introduction to Generative AI in Industry.
- Exploring Industry-Specific Applications.
- Understanding the Impact of Generative AI in Industries.
- Hands-on session: Working on industry-specific Generative AI projects.
- Interactive exercises: Discussing the impact of Generative AI in various industries.
- Understand the application and impact of Generative AI in various industries.
Lessons:
- Overview of the Generative AI Project.
- Exploring Project Requirements and Expectations.
- Understanding the Evaluation Criteria.
- Hands-on workshop: Working on the Generative AI Project.
- Interactive session: Receiving feedback and insights on the project.
- Apply the concepts learned in a practical project.
- Receive feedback and insights on their project.
Lessons:
- Introduction to Future Trends in Generative AI.
- Exploring Upcoming Advancements.
- Understanding Potential Developments in Generative AI.
- Interactive session: Discussing future trends in Generative AI.
- Group discussions: Sharing insights on advancements and developments.
- Understand the future trends in Generative AI.
- Explore the upcoming advancements and potential developments.
Lessons:
- Overview of Course Learnings.
- Exploring Opportunities for Further Learning.
- Understanding the Feedback Process.
- Interactive session: Summarizing the course learnings.
- Group discussions: Providing feedback and discussing further learning opportunities.
- Summarize the key learnings from the course.
- Provide feedback and explore opportunities for further learning.
