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IBM

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.

状态:LLM Application
状态:Retrieval-Augmented Generation
中级课程小时

精选评论

MM

5.0评论日期:Dec 1, 2024

Amazing hands on learning and exposure to various tech

BI

5.0评论日期:Sep 18, 2024

The course was well-structured with practical and insightful projects.

BL

5.0评论日期:Jan 19, 2025

Really enjoyed this project based course. A lot nicer to learn and interesting to follow than some other IBM courses. Definitely recommend this one

MS

4.0评论日期:Apr 9, 2026

Great course but it needs to update all the labs with the latest library versions. some of them do not work

IA

5.0评论日期:Jun 2, 2024

Lab access and code implementation, explanation make this course unique.

MM

5.0评论日期:May 7, 2024

Excellent and up to date course. Highly recommended.

CH

5.0评论日期:Aug 12, 2025

Very Practical, balanced with theories, It was fun!

KA

5.0评论日期:Jul 22, 2024

Quick overview of lots of things. Needs to be done in two iterations, first rapid read, and copy-paste, second slow, deliberated, and less copy-paste.

BM

5.0评论日期:Aug 17, 2024

Excellent examples as you complete the lab work to reinforce the lesson objectives.

AK

5.0评论日期:May 15, 2025

Great course with foundational learning on AI. Will be taking the AI engineer course soon

FA

5.0评论日期:Nov 28, 2025

well curated, presented and carefully planned. with hands-on practical cases

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Michel
4.0
评论日期:Aug 30, 2024
Dan O'Connor
3.0
评论日期:Jun 13, 2024
Ülgen Sarıkavak
2.0
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SURAJ KIRAN AIRI
1.0
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1.0
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Kevin Dubansky
5.0
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Bas Lefeber
5.0
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imtiyaz ansari
5.0
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Leonardo Andrés Koller Vidal
2.0
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Selene Estevez Gamez
5.0
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DESAI FULESH SURESHBHAI
5.0
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Dennis V.
5.0
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andrés felipe morales tabares
5.0
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5.0
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Keshav Singh Attri
5.0
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Bob McManus
5.0
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F. Adeyemo Adeniji
5.0
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Bolatan Adigun Ibrahim
5.0
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Jhon Jairo Parra Rodriguez
5.0
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