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Develop Generative AI Applications: Get Started

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Develop Generative AI Applications: Get Started

This course is part of multiple programs.

Instructors: Hailey Quach +1 more

92,600 already enrolled

Included with

3 modules

Gain insight into a topic and learn the fundamentals.

557 reviews

Intermediate level

Recommended experience

Flexible schedule

1 week at 10 hours a week

Learn at your own pace

90%

Most learners liked this course

3 modules

Gain insight into a topic and learn the fundamentals.

557 reviews

Intermediate level

Recommended experience

Flexible schedule

1 week at 10 hours a week

Learn at your own pace

90%

Most learners liked this course

What you'll learn

Master the basics of GenAI and the LangChain framework, focusing on how prompt engineering and in-context learning to enhance AI interactions
Apply prompt templates, chains, and agents to create flexible and context-aware AI applications using LangChain's modular approach
Develop a GenAI web application with Flask, integrating advanced features such as JSON output parsing for structured AI responses
Evaluate and compare different language models to select the most suitable for specific use cases, ensuring optimal performance and reliability

Skills you'll gain

Category: Generative AI Agents
Category: Large Language Modeling
Category: Software Development
Category: Prompt Patterns
Category: AI Integrations
Category: Tool Calling
Category: Agentic systems
Category: LLM Application
Category: Model Evaluation

Tools you'll learn

Category: LangChain
Category: AI Workflows
Category: Prompt Engineering
Category: Generative AI
Category: Flask (Web Framework)

Details to know

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Assessments

7 assignments

Taught in English

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Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
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There are 3 modules in this course

Get ready to power up your resume with the GenAI development skills employers need. During this course you’ll explore core prompt engineering strategies—like in-context learning and chain-of-thought—and create and manage robust prompt templates. Plus, you’ll follow best practices to handle common errors and experiment with different LLMs and configurations to strengthen your outputs.

You’ll then dive deeper into LangChain, mastering chains, tools, and agents to create smarter, more responsive applications. Through interactive labs, you’ll build a complete generative AI app using Python that accepts user input and processes it through your backend prompt logic. Plus, you’ll explore web-based interfaces using tools like Flask and Gradio, developing real-time user experiences powered by LLMs. By the end, you’ll have the job-ready skills and demonstrable practical experience employers look for to design and implement full-stack GenAI apps that solve real-world problems. Sound good? Enroll today!

This module introduces the basics of generative AI and provides an overview of the most common tools, frameworks, and models used in AI development. You'll learn fundamental prompt engineering principles that help maximize AI model capabilities through thoughtful input design. Special emphasis is placed on the LangChain framework—its features, benefits, and role in designing and writing AI applications. The module covers practical techniques for creating reusable prompt templates that improve consistency, implementing in-context learning strategies, and optimizing AI responses through iterative prompt refinement.

What's included

9 videos7 readings3 assignments1 app item

9 videosTotal 53 minutes

Course Introduction2 minutes
RAG and Agentic AI Professional Certificate Overview6 minutes
Introduction to Generative AI7 minutes
What are Generative AI Models?9 minutes
Video: What is NLP (Natural Language Processing)?10 minutes
Introduction to In-Context Learning6 minutes
Introduction to LangChain4 minutes
Advanced Methods of Prompt Engineering6 minutes
LangChain LCEL Chaining Method5 minutes

7 readingsTotal 88 minutes

Course Overview4 minutes
Helpful Tips for Course Completion5 minutes
About this Optional Lesson2 minutes
Reading: Comprehensive Guide to Generative AI30 minutes
(Optional) Reading: What is Prompt Engineering, and Why Do We Care?15 minutes
Summary and Highlights: Foundations of Generative AI and Prompt Engineering2 minutes
Cheat Sheet: Foundations of Generative AI and LangChain30 minutes

3 assignmentsTotal 51 minutes

Graded Quiz: Foundations of Generative AI and Prompt Engineering21 minutes
Practice Quiz: Generative AI Essentials15 minutes
Practice Quiz: Working with Prompt Engineering and Prompt Templates15 minutes

1 app itemTotal 60 minutes

Lab: Master Prompt Engineering and LangChain PromptTemplates60 minutes

In this module, you will explore LangChain and its advanced features to build generative AI applications. You’ll learn about each core component of LangChain, how to incorporate them to create complex workflows and introduce generative AI into your applications.

What's included

3 videos3 readings2 assignments1 app item

3 videosTotal 18 minutes

LangChain: Core Concepts7 minutes
LangChain Chains and Agents for Building Applications7 minutes
(Optional) LangChain LCEL Chaining Method5 minutes

3 readingsTotal 47 minutes

Recap: Introduction to LangChain 15 minutes
Summary and Highlights: Introduction to LangChain in GenAI Applications 2 minutes
Cheat Sheet: Introduction to LangChain in GenAI Applications30 minutes

2 assignmentsTotal 36 minutes

Graded Quiz: Introduction to LangChain in GenAI applications21 minutes
Practice Quiz: LangChain Core Components and Advanced Features 15 minutes

1 app itemTotal 60 minutes

Lab: Build Smarter AI Apps: Empower LLMs with LangChain60 minutes

In this module, you’ll build a Flask web app that uses the power of generative AI using LangChain. You’ll learn how to integrate AI into your application, leverage LangChain’s JsonOutputParser to produce structured outputs, and fine-tune prompt engineering to generate actionable JSON responses. Along the way, you’ll compare and evaluate different language models—including Llama 3, Granite, and Mixtral—to discover which best suits your needs.

What's included

4 videos7 readings2 assignments1 app item

4 videosTotal 23 minutes

Choose the Right AI Model for Your Use Case4 minutes
From Idea to AI: Building Applications with Generative AI7 minutes
Introduction to Flask 7 minutes
Course Wrap-up 5 minutes

7 readingsTotal 72 minutes

(Optional) Reading: Flask: A Gateway to Web Development in Python15 minutes
(Optional) Reading: Python with Flask for Large Scale Projects15 minutes
Cheat Sheet: Web Development Using Flask5 minutes
Summary and Highlights: Build a Generative AI Application with LangChain 3 minutes
Cheat Sheet: Build GenAI Application with LangChain30 minutes
Congratulations and Next Steps2 minutes
Team and Acknowledgments2 minutes

2 assignmentsTotal 31 minutes

Graded Quiz: Build a Generative AI Application with LangChain21 minutes
Practice Quiz: Application Development Workflow with Generative AI 10 minutes

1 app itemTotal 60 minutes

Hands-on with GenAI: Choosing the Right Model for Your Application60 minutes

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Instructors

Instructor ratings

(114 ratings)

Hailey Quach

IBM

2 Courses93,399 learners

Offered by

IBM

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4 stars
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3.76%
2 stars
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1 star
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Showing 3 of 557

Reviewed on Sep 9, 2025

The content covered is very comprehensive and helpful! Would be good if there was less help with the coding tasks, as that would push the learner to memorize things more!

Reviewed on Nov 10, 2025

Pretty good course, although would have preferred if the online editor and model imports worked properly.

Reviewed on Nov 20, 2025

Very detailed and comprehensive. Despite the amount of topics, explanation by the instructors were very easy to understand and covered all the key concepts.

Frequently asked questions

Skills in building generative AI applications are in demand for roles like AI developer, machine learning engineer, prompt engineer, and full-stack developer with AI experience.

Not necessarily. If you’re a Python developer, you can start building with generative AI using tools like LangChain, Flask, and Gradio—no advanced ML background required.

Generative AI apps require prompt engineering and LLM integration, but you’ll still use familiar web frameworks and developer tools to build and deploy them.

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.