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Developing Generative AI Applications using Python
Course
Developing Generative AI Applications using Python
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.
Flexible Schedule
Intermediate Level
Mentor Support
Estimated Time
13 hours
This course provides an opportunity to work on guided projects that provide step-by-step instructions to build generative AI-powered applications. You'll utilize Python, along with related libraries like Flask and Gradio, and frameworks such as Langchain.
In the course, you will work on hands-on projects to build chatbots and apps by utilizing popular large language models (LLMs) such as GPT-3 and Llama 2, hosted on platforms such as IBM watsonx and Hugging Face. Additionally, you'll explore retrieval-augmented generation (RAG) technology, enhancing LLMs by incorporating external information beyond their training data. This course also equips you to build voice-enabled chatbots and apps using IBM Watson Speech Libraries for Embed.
To develop these projects, you'll be using Python, making it essential to have a basic understanding of the language. While knowing some HTML, CSS, and JavaScript can be beneficial, it's not a requirement. The course includes supporting videos and readings to build a foundational understanding of models, frameworks, and technologies used in the projects.
This course comprises six purposely designed modules that take you on a carefully defined learning journey.
It is a self-paced course, which means it is not run to a fixed schedule with regard to completing modules. It is anticipated that you will complete the course in 13 hours. However, as long as the course is completed by the end of your enrollment, you can work at your own pace. And dont worry, youre not alone! You will be encouraged to stay connected with your learning community through the course discussion space.
The materials for each module are accessible from the start of the course and will remain available for the duration of your enrollment. Methods of learning and assessment will include discussion space, videos, reading material, quizzes, hands-on labs, quizzes and final assignment.
Once you have successfully completed the course, you will earn your IBM Certificate.
You will be able to:
- Build and deploy AI-powered voice assistant applications.
- Design and implement conversational chatbots for real-world use cases.
- Write efficient Python code to power AI-driven conversational systems.
Designed for students, developers, and professionals with basic Python skills who want hands-on experience building generative AI-powered apps and chatbots.
This course is suitable for individuals with basic knowledge of Python and generative AI and an interest in developing AI-powered apps and chatbots.
Course Outline
Video: Course Introduction
Reading: General Information
Course Syllabus and Prerequisites
Reading: Helpful Tips for Course Completion
Video: Generative AI Models
Video: Foundation Models
Grading Scheme
Module Introduction and Learning Objectives
Video: Project Overview: Image Captioning with Generative AI (3:12)
Video: Hugging Face (5:03)
Reading: BLIP from Hugging Face Transformers
Reading: Introduction to Gradio
Lab: Give Meaningful Names to Your Photos with IMG Captioning AI
[Optional] Lab: Deploy your App with Code Engine
Module Summary: Image Captioning with Generative AI
Module 1 Graded Quiz: Image Captioning with Generative AI (7 Questions)
Module Introduction and Learning Objectives
Video: Project Overview: Create Your Own ChatGPT-like Website (4:14)
Reading: Flask – A Gateway to Web Development in Python
Lab: Create Simple Chatbot with Open Source LLMs using Python and Hugging Face
Lab: Integrating Your Chatbot into a Web Application
Module Summary: Create Your Own ChatGPT-Like Website
Module 2 Graded Quiz: Create Your Own ChatGPT-like Website (7 Questions)
Module Introduction and Learning Objectives
Video: Project Overview: Create a Voice Assistant
Video: Introduction to Docker (3:30)
Reading: IBM Watson Speech-to-Text and Text-to-Speech
Lab: Create a Voice Assistant with OpenAI's GPT-3 and IBM Watson
Module Summary: Create a Voice Assistant
Module 2 Graded Quiz: Create Your Own ChatGPT-like Website (7 Questions)
Module Introduction and Learning Objectives
Video: Project Overview: Generative AI-Powered Meeting Assistant (3:25)
Video: IBM watsonx.ai (5:33)
Reading: Introduction to Meta Llama 2
Reading: Introduction to OpenAI Whisper
Lab: Business AI Meeting Companion
Module Summary: Generative AI-Powered Meeting Assistant
Module 4 Graded Quiz: Generative AI-Powered Meeting Assistant (7 Questions)
Module Introduction and Learning Objectives
Video: Project Overview: Summarize Your Private Data with Generative AI & RAG (4:21)
Reading: Introduction to LangChain
Video: Enhancing LLM Accuracy with RAG
Reading: Introduction to Llama 2 and RAG
Lab: Business AI Meeting Companion
Module Summary: Summarize Your Private Data with Generative AI
Module 5 Graded Quiz: Summarize Your Private Data with Generative AI (7 Questions)
Module Introduction and Learning Objectives
Video: Introduction to Project: Babel Fish with LLM and STT TTS (3:37)
Lab: Babel Fish (Language Translator) with LLM, STT, & TTS
Module Summary: Babel Fish with LLM and STT TTS
Module 6 Graded Quiz: Babel Fish with LLM and STT TTS (7 Questions)
Glossary: Building GenAI- Powered Apps with Python
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Personalized Mentoring & Support
1-on-1 mentoring, live classes, webinars, weekly feedback, peer discussion, and much more.
Practical Experience
Hands-on labs and projects tackling real-world challenges. Great for your resumé and LinkedIn profile.
Best-in-Class Course Content
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FAQs
Generative AI with Python focuses on building AI models that can create content, respond intelligently, and generate actionable insights. It is crucial for developers looking to build AI-powered chatbots, apps, and other innovative solutions.
It provides hands-on projects to create intelligent applications using Python, LLMs, RAG technology, and IBM watsonx, giving practical exposure to real-world AI problems.
You will learn Python for Generative AI, integrating LLMs, RAG-based knowledge retrieval, building web apps with Flask and Gradio, and deploying AI solutions.
Yes, the training covers similar projects that include step-by-step guidance to create functional AI applications using Python and frameworks like Flask and Gradio.
Aspiring AI developers, Python programmers, and professionals interested in building Generative AI-powered applications and chatbots will benefit the most.
Basic Python knowledge is recommended, while familiarity with LLMs, HTML, CSS, and JavaScript are helpful but not mandatory. Prior exposure to Generative AI concepts will be advantageous.
Yes, the course includes hands-on labs to create chatbots, voice assistants, meeting assistants, and data summarization apps.
RAG technology allows integration of external knowledge with LLMs, improving model accuracy and enabling applications that use private or domain-specific data.
Python, Flask, Gradio, LangChain, IBM watsonx, GPT-3, Llama 2, and other frameworks are leveraged for practical application development.
Yes, learners receive an IBM Certificate demonstrating their proficiency in generative AI with Python and the ability to develop real-world AI applications.
Type of certificate
IBM Certificate
About this course
06 Modules
03 Skills
Includes
Discussion space
08 Hands-on labs
06 Graded quizzes
Create
Simple Chatbot
Voice Assistant
Exercises to explore
Integrating Your Chatbot into a Web Application
Business AI Meeting Companion
Babel Fish (Language Translator) with LLM, STT, & TTS
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