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Building Generative AI-Powered Applications with Python
Ready for an interactive learning experience to build real-world generative AI applications and chatbots? In this hands-on course, you’ll develop a series of guided projects using Python, Flask, Gradio, and LangChain to create AI-powered applications for practical scenarios, including a voice assistant, a meeting summarizer, a language translator, and a personalized career coach. You’ll work with popular large language models (LLMs) such as GPT-3, Llama 2, and Flan-UL2, hosted on platforms like IBM watsonx and Hugging Face. You’ll also explore advanced concepts, such as retrieval-augmented generation (RAG), to enhance LLM responses with external knowledge, and integrate speech-to-text (STT) and text-to-speech (TTS) using IBM Watson® Speech Libraries and OpenAI Whisper to enable voice interactions. While a basic understanding of Python is essential, knowledge of HTML, CSS, or JavaScript is helpful but not required. The course includes supporting readings and videos to build foundational knowledge of the models and frameworks used. In addition, a comprehensive course glossary will help reinforce your learning.
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Introduction to Project: Build an AI Career Coach
Introduction to Project: Build an AI Career Coach
Introduction to Project: Build an AI Career Coach
Introduction to Project: Babel Fish with LLM and STT TTS
Introduction to Project: Babel Fish with LLM and STT TTS
Introduction to Project: Babel Fish with LLM and STT TTS
Enhancing LLM Accuracy with RAG
Enhancing LLM Accuracy with RAG
Enhancing LLM Accuracy with RAG
Introduction to LangChain
