Build in-demand skills in generative AI application development and get hands-on experience creating intelligent chatbots and apps using popular LLMs, RAG technology, and IBM watsonx.
What you'll learn
Job-ready generative AI app development skills in 6 weeks, supported by practical experience and an industry-recognized credential.
How to integrate and enhance large language models (LLMs) using RAG technology to build intelligent apps and chatbots.
How to use Python libraries like Flask and Gradio to create web applications that interact with generative AI models.
How to use different frameworks and AI technologies to build AI-powered applications.
How to build generative AI-powered applications and chatbots using generative AI models, Python, and related frameworks.
This is CS50W, CS50's Web Programming with Python and JavaScript. Register for free at https://cs50.edx.org/web. Slides and source code at https://cs50.harvard.edu/web. This course picks up where Harvard University’s CS50 leaves off, diving more deeply into the design and implementation of web apps…
Stanford CS25: Transformers United Since their introduction in 2017, transformers have revolutionized Natural Language Processing (NLP). Now, transformers are finding applications all over Deep Learning, be it computer vision (CV), reinforcement learning (RL), Generative Adversarial Networks (GANs)…
Natural language processing (NLP) is a crucial part of artificial intelligence (AI), modeling how people share information. In recent years, deep learning approaches have obtained very high performance on many NLP tasks. In this course, students gain a thorough introduction to cutting-edge neural n…
Language models serve as the cornerstone of modern natural language processing (NLP) applications and open up a new paradigm of having a single general purpose system address a range of downstream tasks. As the field of artificial intelligence (AI), machine learning (ML), and NLP continues to grow,…