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Generative AI in Software Development

Amazon

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.

After completing this course, you’ll be able to:

• Discuss the principles and applications of Generative AI.

Read more

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.

After completing this course, you’ll be able to:

• Discuss the principles and applications of Generative AI.

• Implement Generative AI tools in software development.

• Examine the role of Generative AI in automating repetitive tasks in software development.

• Evaluate the benefits and limitations of using Generative AI in software development.

Enroll now

What's inside

Syllabus

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.
Read more

Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Explores tools like Amazon CodeWhisperer, ChatGPT, and GitHub Copilot, which are currently used to enhance coding efficiency and productivity
Examines the role of AI in automating repetitive tasks, which can free up developers to focus on more complex and creative work
Presented by Amazon, which is known for its cloud computing services and its work in artificial intelligence and machine learning
Requires learners to create a rule-based chatbot, which may require access to platforms and tools not readily available to all learners

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Reviews summary

Generative ai tools for software developers

According to learners, this course offers a solid introduction to using Generative AI tools in software development. Many found the hands-on labs and practical examples, particularly with Amazon CodeWhisperer, to be highly practical and immediately applicable. The course is seen as a great starting point for developers looking to integrate AI into their workflow. However, some students felt the course lacked technical depth needed for more experienced developers and found the initial module on digital transformation somewhat disconnected from the core topic.
Good introduction, may lack depth for experts.
"Expected more technical depth. It's more of a high-level overview. Not suitable for experienced developers looking to dive deep into the mechanics."
"Excellent course for software developers wanting to understand how to use AI tools."
"Provides a solid foundation. I appreciated the focus on practical tools like CodeWhisperer."
"Perfect introduction to GenAI in coding for developers."
Introduces important GenAI tools for coding.
"Good overview of GenAI tools for coding. CodeWhisperer section was great."
"Covers the major players like CodeWhisperer, Copilot, and ChatGPT."
"A good starting point. Covers the major players like CodeWhisperer, Copilot, and ChatGPT. Practical examples were key."
Hands-on activities, labs, and demos are praised.
"The labs with CodeWhisperer were super practical and immediately applicable to my Java projects."
"Loved the hands-on approach. Implementing the chatbot project was a bit challenging but very rewarding."
"The demos were helpful and the content was up-to-date."
"Highly recommend this course! It's a perfect introduction to GenAI in coding for developers. The hands-on labs make a big difference."
Engaging project, but provided code needs work.
"The final project was interesting but the provided code required significant tweaking."
Initial module feels disconnected to core topic.
"Okay course. The first module on digital transformation felt a bit disconnected from the core topic of GenAI in coding."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Generative AI in Software Development with these activities:
Review Core Java Concepts
Strengthen your understanding of Java fundamentals to better grasp how Generative AI tools assist in Java software development.
Show steps
  • Review data types, control structures, and object-oriented principles in Java.
  • Practice coding simple Java programs to reinforce your understanding.
Read 'Building Machine Learning Powered Applications: Going from Idea to Product'
Gain a broader understanding of the machine learning application development lifecycle to better appreciate the role of Generative AI.
View Building Machine Learning Powered Applications:... on Amazon
Show steps
  • Read the book, focusing on the chapters related to model development and deployment.
  • Take notes on the key concepts and examples presented in the book.
Explore Amazon CodeWhisperer Tutorials
Familiarize yourself with Amazon CodeWhisperer through hands-on tutorials to enhance your coding efficiency.
Show steps
  • Access the official Amazon CodeWhisperer documentation and tutorials.
  • Follow the tutorials to learn how to use CodeWhisperer for code completion and bug detection.
  • Experiment with CodeWhisperer in your own Java projects.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Read 'Hands-On Generative AI with Python and TensorFlow 2.0'
Deepen your understanding of the underlying AI principles behind Generative AI tools.
View Putting Knowledge to Work on Amazon
Show steps
  • Read the book, focusing on the chapters related to generative models.
  • Experiment with the code examples provided in the book.
Develop a Simple Java Application with AI Assistance
Apply your knowledge of Generative AI tools to build a practical Java application.
Show steps
  • Choose a simple Java application to develop, such as a calculator or a to-do list.
  • Use Amazon CodeWhisperer or a similar tool to assist with code completion and bug detection.
  • Test and debug your application thoroughly.
Write a Blog Post on Generative AI in Software Development
Solidify your understanding of Generative AI by explaining its role in software development to others.
Show steps
  • Research the latest trends and applications of Generative AI in software development.
  • Write a blog post summarizing your findings and insights.
  • Share your blog post on social media or relevant online forums.
Create a Presentation on the Ethical Implications of Generative AI in Software Development
Explore the ethical considerations surrounding the use of Generative AI in software development.
Show steps
  • Research the ethical implications of using Generative AI in software development, such as bias and security.
  • Create a presentation summarizing your findings and recommendations.
  • Present your findings to a group of peers or colleagues.

Career center

Learners who complete Generative AI in Software Development will develop knowledge and skills that may be useful to these careers:
Software Engineer
A Software Engineer is responsible for designing, developing, testing, and maintaining software systems, and this course is particularly helpful for understanding how to integrate generative AI into these processes. This role often involves automating repetitive tasks, and this course specifically teaches how to use tools like Amazon CodeWhisperer to accomplish this. A software engineer who takes this course will be familiar with the strengths and limitations of such tools and thus will be able to make informed decisions about when and how to use them. This course helps engineers stay updated with modern technologies, thereby making them more competitive and efficient. Understanding how generative AI automates coding accelerates product development and allows engineers to spend time on innovative projects.
See salaries and explore the career path for Software Engineer
Automation Engineer
An Automation Engineer focuses on designing, developing, and implementing automated systems to improve efficiency and reduce repetitive manual tasks. This course provides valuable insight into how generative AI tools can automate tasks in software development, which is highly relevant to the automation engineer's typical day. Understanding how tools like Amazon CodeWhisperer work is crucial for identifying the proper use of AI in automation workflows. The course also covers the benefits and limitations of generative AI, which is helpful to an Automation Engineer when choosing the correct automation solutions for projects. Learning about the limitations of AI solutions is every bit as crucial as learning about their capabilities.
See salaries and explore the career path for Automation Engineer
AI Solutions Architect
An AI Solutions Architect is responsible for designing and implementing AI solutions to address business needs. A key part of their work is to effectively integrate AI into existing software systems, and this course provides a direct education in how these systems can be incorporated into software development workflows. This course offers hands-on experience with tools like Amazon CodeWhisperer, allowing an AI Solutions Architect to understand the practical benefits and limitations of generative AI. This knowledge base helps an architect choose which projects to prioritize, and how to implement the appropriate tool for the task. The practical aspects of this course provide experience in the tools that the architect will be working with.
See salaries and explore the career path for AI Solutions Architect
DevOps Engineer
A DevOps Engineer works to streamline the software development lifecycle by improving communication and collaboration between development and operations teams. This course significantly improves a DevOps Engineer's knowledge by explaining how generative AI tools like Amazon CodeWhisperer can automate tasks and increase efficiency in software development. Understanding the capabilities and limitations of these tools is crucial for integrating them into a DevOps pipeline. DevOps roles require continuous learning and this course is useful in staying current with the latest technology. It provides the practical experience to integrate AI into workflows, improving automation and release processes.
See salaries and explore the career path for DevOps Engineer
Software Development Manager
A Software Development Manager oversees software development teams and projects. Taking this course lets the manager gain an understanding of how generative AI can impact software development, to improve project planning and resource allocation. The course teaches practical skills and provides informed decisions about the implementation of these tools in software development. A manager who completes this course is better able to guide teams on the use of these new technologies. Understanding the capabilities and limitations of generative AI is particularly beneficial when making workflow decisions for a team.
See salaries and explore the career path for Software Development Manager
Technology Consultant
A Technology Consultant advises clients on how to use technology to meet their business goals. They need a firm understanding of emerging technologies. This course introduces generative AI tools and their practical use in software development, which is highly valuable to a consultant. The practical exercises in the course will enable the consultant to explain the benefits and limitations of AI to clients, and therefore provide better recommendations. This course may help a consultant recommend the proper type of AI solution for a particular task. They must know how to integrate these tools into workflows and this course is helpful for that.
See salaries and explore the career path for Technology Consultant
AI Programmer
An AI Programmer writes code to develop AI models and applications. While this course focuses on the application of generative AI in software development rather than the development of the models themselves, it provides a valuable understanding of how programmers can use these tools. This course may be helpful for AI programmers when learning how to integrate generative AI into their workflows. Understanding how tools like Amazon CodeWhisperer work is important when developing AI-powered software. This course may fill in gaps in knowledge in AI programming, particularly if the programmer has not worked with such tools.
See salaries and explore the career path for AI Programmer
Technical Project Manager
A Technical Project Manager is responsible for overseeing technical aspects of projects and ensuring resources and teams are used effectively. This course provides an understanding of how generative AI impacts software development, allowing the manager to make decisions about project planning and team training. The knowledge of tools like Amazon CodeWhisperer helps the project manager understand the technical possibilities and limitations when making project plans. A project manager who takes this course may better understand how best to use team resources. It makes project managers more technically adept.
See salaries and explore the career path for Technical Project Manager
Software Architect
A Software Architect designs the overall structure of software systems. This course may be useful, as it enhances their understanding of using generative AI tools in software development, which allows the architect to make better decisions about technology integration. Software architects must be able to make recommendations for technology adoption; this course provides important insights into the practical applications of using tools like Amazon CodeWhisperer. A software architect may more quickly identify areas of the development cycle where AI can and should be used after taking this course. The architect will be able to make decisions based on the limitations of such tools as well.
See salaries and explore the career path for Software Architect
Data Scientist
A Data Scientist analyzes data to derive insights and make recommendations. This course may be useful for a data scientist who wants to understand how generative AI tools can be integrated into software development. The course provides a foundation in how AI can automate tasks and improve workflows, which may help the data scientist to find new ways to use data in a software environment. Understanding how software engineers use AI tools is useful when collaborating on a project. Practical knowledge, such as that provided by this course, is invaluable.
See salaries and explore the career path for Data Scientist
Research Scientist
A Research Scientist conducts research and develops new scientific knowledge. This course may be useful for a research scientist who aims to explore ways AI can impact software development. The course provides knowledge of how AI tools are used in practice, which may aid research on the topic. The course may also provide experience with the latest tools in generative AI. The research scientist may gain knowledge they did not possess previously, and also begin to think about research topics relevant to software engineering.
See salaries and explore the career path for Research Scientist
Quality Assurance Analyst
A Quality Assurance Analyst is responsible for ensuring software quality through testing and analysis. This course may be useful for a quality assurance analyst, as they will learn how generative AI tools can impact the software development lifecycle. Understanding how developers use tools such as Amazon CodeWhisperer may improve the quality assurance analyst's abilities to design effective test strategies. The course may also provide an overview of the limitations of these tools, which is also helpful. The analyst may decide to focus their efforts on code areas where AI might not be as effective.
See salaries and explore the career path for Quality Assurance Analyst
Database Administrator
A Database Administrator is responsible for managing and maintaining databases. This course, while not directly aligned with the core functions of database administration, may be useful for database administrators who want to understand the broader landscape of AI in software development. This course helps a database administrator understand the tools that engineers are using, and how the development process works. This may help a database administrator design databases that are better aligned with modern software development practices. This course may help provide greater context.
See salaries and explore the career path for Database Administrator
Systems Analyst
A Systems Analyst is responsible for analyzing and designing computer systems. Although the course may not be directly applicable to system analysis, it may still be useful for those who want to understand the implementation of AI in software. This course introduces AI tools used in software design. The course may provide experience with AI tools that are used collaboratively with the systems that the analyst is working with. The analyst may become more well-rounded, and be able to more easily integrate new technology into system design.
See salaries and explore the career path for Systems Analyst
Technical Writer
A Technical Writer creates documentation for technical processes, systems, and products. This course may be useful if the technical writer is documenting tools and processes that include Generative AI in software development. They may seek to document the process of learning how to use tools such as Amazon CodeWhisperer. They might document the benefits and limitations as well. This course may give the technical writer a greater command of the material they will be writing about, and therefore make them a more effective writer.
See salaries and explore the career path for Technical Writer

Reading list

We've selected two books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Generative AI in Software Development.
Cover image
Building Machine Learning Powered Applications
Save
Provides a practical guide to building machine learning applications from start to finish. It covers the entire process, from ideation to deployment, and includes real-world examples and case studies. It is useful for understanding the broader context of how Generative AI tools fit into the software development lifecycle. This book is valuable as additional reading to provide a broader context.
Building Machine Learning Powered Applications:...
Paperback
$$
Building Machine Learning Powered Applications:...
Kindle Edition
$$
Cover image
Putting Knowledge to Work
Save
Provides a practical introduction to Generative AI using Python and TensorFlow 2.0. It covers various generative models, including GANs, VAEs, and autoregressive models. While the course focuses on tools like CodeWhisperer, this book provides a deeper understanding of the underlying AI principles. This book is more valuable as additional reading than as a current reference.
Putting Knowledge to Work
Paperback
Check
Putting Knowledge to Work
Kindle Edition
Check

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Effort
Approximately 24 hours
Level
Introductory
Via
Coursera
Institution
Amazon
Instructor
Amazon
Session
January 20, 2025 - February 17, 2025
Language
English
Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
Explores tools like Amazon CodeWhisperer, ChatGPT, and GitHub Copilot, which are currently used to enhance coding efficiency and productivity
Examines the role of AI in automating repetitive tasks, which can free up developers to focus on more complex and creative work
Presented by Amazon, which is known for its cloud computing services and its work in artificial intelligence and machine learning
Requires learners to create a rule-based chatbot, which may require access to platforms and tools not readily available to all learners
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