Unlock Generative AI: LLMs & Creative Applications

What you will learn:

Master foundational concepts of Generative AI and LLMs
Develop practical skills in building and deploying AI applications
Gain hands-on experience with leading AI tools and frameworks
Understand ethical considerations and responsible AI practices
Build a portfolio-ready project showcasing your expertise
Apply AI to diverse tasks including text generation, image synthesis, and code creation
Learn advanced techniques like fine-tuning and prompt engineering
Explore various Generative AI model architectures (GANs, VAEs, Diffusion models)
Utilize vector databases for efficient data management and retrieval
Prepare for a career in the exciting field of Generative AI

Description

Dive into the world of Generative AI and Large Language Models (LLMs) with this comprehensive 8-week course. You'll journey from foundational concepts to advanced applications, learning to build, customize, and ethically deploy these powerful tools. We'll cover everything from the inner workings of transformer architectures and prompt engineering to the practical use of cutting-edge frameworks like Hugging Face Transformers, LangChain, and vector databases. Through hands-on projects, you'll gain the skills to generate text, images, and even code, mastering techniques like fine-tuning and LoRA for specialized tasks. Understand the ethical implications and responsible use of AI, and culminate your learning with a portfolio-ready capstone project.

This course isn't just theory; it's practical application. You'll work with real-world tools and datasets, tackling challenges like text summarization, creative writing, code generation, and data augmentation. Learn to leverage the power of GANs, VAEs, and diffusion models to create innovative solutions. By the end, you'll possess the expertise to confidently apply Generative AI in various fields, from business and research to creative industries. Prepare to transform your understanding of AI and unlock a world of possibilities.

This course offers a blend of theoretical understanding and practical application. You'll explore core concepts like tokenization, attention mechanisms, embeddings, and perplexity, while gaining hands-on experience using tools like Hugging Face Transformers, LangChain, and vector databases (FAISS, Pinecone). You'll also delve into fine-tuning techniques such as LoRA and prompt engineering, learning how to adapt LLMs to specific tasks. The course emphasizes ethical considerations, responsible AI development, and addresses potential risks associated with bias and hallucinations. The capstone project will provide you with a portfolio-ready showcase of your newly acquired skills.

Curriculum

Week 1 – Introduction to the World of Generative AI

This introductory week lays the groundwork for understanding Generative AI. You'll learn the definition of Generative AI, trace its evolution from rule-based systems to sophisticated generative models, explore various generative model types (GANs, VAEs, Diffusion models, and LLMs), and examine real-world applications and examples. The hands-on component will allow you to begin experimenting with the core concepts learned.

Week 2 – Decoding Large Language Models

Week 2 delves into the specifics of Large Language Models (LLMs). You'll explore their inner workings, including the transformer architecture, training data, tokenization processes, and the crucial distinction between pre-training and fine-tuning. The accompanying hands-on exercises solidify your understanding of these fundamental concepts.

Week 3 – Mastering the Core Principles of Generative AI

Week 3 focuses on core concepts integral to Generative AI. This includes a deep dive into Natural Language Processing (NLP) fundamentals, understanding embeddings and vector representations, mastering the art of prompt engineering, and learning how to evaluate the performance of generative AI models using appropriate metrics. Hands-on practice will help solidify your grasp of these essential elements.

Week 4 – Putting Generative AI into Action

This week moves into practical applications. You'll gain hands-on experience using APIs such as OpenAI and Hugging Face to perform tasks like text generation, summarization, and translation. You'll also get an overview of image and audio generation. The hands-on segment involves building simple applications leveraging LLMs.

Week 5 – Fine-Tuning and Personalizing Your AI Models

Week 5 focuses on customizing and fine-tuning your LLMs. You'll explore transfer learning, fine-tuning techniques using domain-specific data, learn about Retrieval-Augmented Generation (RAG), and discover parameter-efficient fine-tuning methods like Low-Rank Adaptation (LoRA). The practical session allows you to put these techniques into practice.

Week 6 – Working with Key Tools and Frameworks

This week introduces essential tools and frameworks for working with Generative AI. You'll gain proficiency in using the Hugging Face Transformers library and various vector databases like Pinecone, FAISS, and potentially Weaviate. The hands-on component will give you practical experience utilizing these technologies.

Week 7 – Ethical Considerations and Responsible AI

Week 7 addresses the crucial topic of ethics and responsible AI development. You’ll explore ethical concerns related to Generative AI, discuss safety measures and responsible AI practices, delve into data privacy and security issues, and examine future trends in AI regulation. The hands-on portion focuses on applying these principles in your projects.

Week 8 – Real-World Applications and Capstone Project

The final week explores real-world case studies of Generative AI across various industries (healthcare, finance, education, and creative industries). You'll contemplate the future of AI and human collaboration and learn about future trends. The week culminates in a course wrap-up, key takeaways, and completion of your capstone project, showcasing your newfound skills.