IBM
Building Generative AI-Powered Applications with Python
IBM

Building Generative AI-Powered Applications with Python

This course is part of IBM AI Developer Professional Certificate

Taught in English

Some content may not be translated

IBM Skills Network Team
Sina Nazeri

Instructors: IBM Skills Network Team

2,323 already enrolled

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Course

Gain insight into a topic and learn the fundamentals

4.7

(10 reviews)

Intermediate level

Recommended experience

14 hours (approximately)
Flexible schedule
Learn at your own pace

What you'll learn

  • Explain the core concepts of generative AI models, AI technologies, and AI platforms such as IBM watsonx and Hugging Face.

  • Integrate and enhance large language models (LLMs) using RAG technology to infuse intelligence into apps and chatbots.

  • Utilize Python libraries like Flask and Gradio to create web applications that interact with generative AI models.

  • Build generative AI-powered applications and chatbots using generative AI models, Python, and related frameworks.

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Recently updated!

April 2024

Assessments

7 assignments

Course

Gain insight into a topic and learn the fundamentals

4.7

(10 reviews)

Intermediate level

Recommended experience

14 hours (approximately)
Flexible schedule
Learn at your own pace

See how employees at top companies are mastering in-demand skills

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This course is part of the IBM AI Developer Professional Certificate
When you enroll in this course, you'll also be enrolled in this Professional Certificate.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
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There are 7 modules in this course

In this module, you will learn the basics of generative AI models and explore the AI models and data sets using the Hugging Face platform. You will work on a guided project that involves image captioning using Python, the BLIP model, and Gradio. This project will let you build an automated image caption tool using generative AI and implement it for real-world scenarios.

What's included

5 videos2 readings1 assignment2 app items3 plugins

In this module, you will learn to create a simple chatbot with open-source LLMs and integrate your chatbot into a web interface. You will explore the different components of the chatbot application and understand how a chatbot works. In addition, you will learn about selecting the right large language model or LLM for your chatbot. In this project, you will work with Facebook’s Blenderbot model and Hugging Face’s Python library, Transformers.

What's included

1 video1 reading1 assignment2 app items1 plugin

In this module, you will learn the basics of chatbots and their applications. You will set up a development environment to build a chatbot. You will build a chatbot that can take voice input and generate a spoken response using IBM Watson speech-to-text functionality and integrate with OpenAI’s GPT 3 model to incorporate high intelligence within the chatbot. And finally, you will learn to deploy the chatbot to a public server.

What's included

2 videos1 reading1 assignment1 app item1 plugin

In this module, you will work on creating an app that captures audio using OpenAI Whisper and summarize it using Llama 2 LLM. Then, you will learn to deploy the app in a serverless environment using the IBM cloud code engine. This module provides a solid foundation for using LLMs for text generation and summarization tasks.

What's included

2 videos1 reading1 assignment1 app item2 plugins

In this module, you will learn how large language models (LLMs) work and how to use them for data summarization and information extraction. You will work on a project to build your own chatbot that allows you to upload a PDF file and answer user queries based on the PDF. You will learn to use Llama 2 LLM supported by the Retrieval-augmented generation (RAG) technique. Finally, you will work with some of the popular frameworks like LangChain to make an intelligent chatbot.

What's included

2 videos1 reading1 assignment1 app item2 plugins

In this module, you will acquire the necessary skills to create a voice translator assistant leveraging generative AI models like flan-ul2 and AI technologies like IBM Watson® Speech Libraries for Embed. This translator application will convert speech input to text and then provide the output through speech in a specified language. You will implement your Python, Flask, HTML, CSS, and JavaScript proficiency to create the web-based voice assistant.

What's included

1 video3 readings1 assignment1 app item1 plugin

In this module, you will create an AI career coach to help bridge the gap between talent and opportunity. As part of this AI Career Coach, you will build three applications: a resume enhancement tool, a personalized cover letter generator, and a career advisor. You will leverage the Llama-2-70b-chat large language model (LLM) integrated into the IBM watsonx.ai platform to build these applications. You will also leverage Gradio to build the web interface for these applications.

What's included

1 video1 reading1 assignment1 app item

Instructors

IBM Skills Network Team
IBM
57 Courses794,408 learners
Sina Nazeri
IBM
1 Course2,323 learners

Offered by

IBM

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