What you'll learn

Discuss the principles, applications, and role of Generative AI in automating repetitive tasks in software development.
Implement Generative AI tools in software development.
Evaluate the benefits and limitations of using Generative AI in software development.

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

10 assignments

Taught in English

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

Learn more about Coursera for Business

Build your Software Development expertise

This course is part of the Amazon Junior Software 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
Earn a shareable career certificate from Amazon

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV

Share it on social media and in your performance review

There are 3 modules in this course

In this course, you'll explore Generative AI's role in software development. You'll start with an overview to understand its capabilities. Next, you'll dive into specific tools like Amazon CodeWhisperer, where you'll learn to automate tasks such as code completion and bug detection. By the end, you'll evaluate Generative AI's benefits and limitations. This will empower you to make informed decisions about its use in software development.

This module will introduce you to the world of Generative AI and how it can aid in software development, specifically in Java. You'll explore the features and benefits of Amazon CodeWhisperer, ChatGPT, and GitHub Copilot, and learn how these tools can enhance your coding efficiency and productivity.

What's included

14 videos10 readings5 assignments7 ungraded labs

14 videosTotal 78 minutes

Course introduction3 minutesPreview module
Introduction to generative artificial intelligence6 minutes
How generative AI works4 minutes
Generative AI in software development6 minutes
Generative AI in Java development5 minutes
Introduction to Amazon Q Developer 6 minutes
Introduction to ChatGPT3 minutes
Introduction to GitHub Copilot5 minutes
Automating code reviews5 minutes
Bug detection and fixing6 minutes
Automating Java documentation6 minutes
Software design with AI7 minutes
AI for code explanation6 minutes
Module summary: AI and building software4 minutes

10 readingsTotal 95 minutes

Project preview10 minutes
Course syllabus10 minutes
How to be successful in this course10 minutes
Ethical considerations and impact10 minutes
Introduction to prompt engineering10 minutes
Amazon accounts10 minutes
Hands-On with ChatGPT10 minutes
Comparing generative AI tools10 minutes
Automated Java code refactoring10 minutes
Additional resources: Introduction to AI5 minutes

5 assignmentsTotal 90 minutes

Knowledge check: Introduction to AI15 minutes
Knowledge check: Generative AI programming tools15 minutes
Knowledge check: AI for automation15 minutes
Knowledge check: AI software design15 minutes
Module quiz: AI and building software30 minutes

7 ungraded labsTotal 290 minutes

Hands-on with Amazon Q Developer45 minutes
Hands-on with GitHub Copilot40 minutes
Bug detection and fixing60 minutes
Refactoring code40 minutes
Generating documentation45 minutes
Building apps with AI30 minutes
Exploring code30 minutes

In this module, you will explore how AI integrates into digital transformation, with a focus on decision-making models and their practical application in business contexts. You will delve into various AI decision-making models and their pivotal role in driving organizational change through digital transformation initiatives. The module aims to help you understand how AI can effectively tackle business challenges and optimize operational processes to enhance efficiency and foster innovation within modern enterprises.

What's included

13 videos7 readings4 assignments1 ungraded lab

13 videosTotal 79 minutes

AI and machine learning basics6 minutesPreview module
Random forests7 minutes
Neural networks6 minutes
Overview of digital transformation4 minutes
The four domains of digital transformation5 minutes
Technology in digital transformation5 minutes
AI in customer relationship management (CRM)6 minutes
Ethical and regulatory compliance5 minutes
Scalability7 minutes
Interpretability and transparency7 minutes
Integration with existing systems5 minutes
Ethical and regulatory compliance6 minutes
Module summary: Object introduction to AI decision-making models5 minutes

7 readingsTotal 65 minutes

Decision trees10 minutes
Neural network in action10 minutes
Data's role in digital transformation10 minutes
Integration with existing systems10 minutes
Improving model transparency10 minutes
Compliance in action10 minutes
Additional resources: AI and digital transformation5 minutes

4 assignmentsTotal 75 minutes

Knowledge check: Introduction to AI decision-making models15 minutes
Knowledge check: Digital transformation15 minutes
Knowledge check: Business challenges15 minutes
Module quiz: AI and digital transformation30 minutes

1 ungraded labTotal 60 minutes

Creating a recommendation program60 minutes

In this module, you will create a rule-based chatbot tailored to your chosen platform using code that has been provided. Your tasks will include coding the bot's basic design with user inputs, designing a console-based user interface for easy interaction, using IDE tools or external AI to shape the provided code into an assistant, persona, or buddy, and implementing data sources and structures to ensure effective bot responses. Additionally, you will complete a final course quiz to assess your understanding and application of the concepts learned.