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Amazon CodeWhisperer is an artificial intelligence (AI) coding companion that can generate code suggestions in real time based on your comments and existing codet. CodeWhisperer, which works in a variety of Integrated Development Environments (IDE), helps you reduce the time it takes to complete coding tasks and produce more secure code. In addition, CodeWhisperer helps you build faster when using Amazon Web Services (AWS) APIs.

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Amazon CodeWhisperer is an artificial intelligence (AI) coding companion that can generate code suggestions in real time based on your comments and existing codet. CodeWhisperer, which works in a variety of Integrated Development Environments (IDE), helps you reduce the time it takes to complete coding tasks and produce more secure code. In addition, CodeWhisperer helps you build faster when using Amazon Web Services (AWS) APIs.

In this course, you will learn the benefits and technical concepts of CodeWhisperer. If you are new to the service, you will learn how to start interacting with CodeWhisperer through Visual Studio Code, JetBrains PyCharm, and AWS Lambda. You will also learn how the built-in features can help you streamline code writing.

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What's inside

Syllabus

Amazon CodeWhisperer

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Useful for learners who want to increase their productivity while coding on AWS
Introduces learners to Amazon's AI coding companion, CodeWhisperer
Covers how to use CodeWhisperer in different IDEs, including Visual Studio Code and JetBrains PyCharm

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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 Amazon CodeWhisperer - Getting Started with Generative AI with these activities:
Review Object-Oriented Programming Concepts
Strengthen your understanding of OOP concepts to enhance your ability to leverage CodeWhisperer.
Show steps
  • Revisit materials from previous OOP courses or tutorials
  • Focus on concepts such as classes, objects, inheritance, polymorphism, and encapsulation
  • Practice writing OOP code in your preferred language
Follow the AWS CodeWhisperer Tutorial
Gain a thorough understanding of CodeWhisperer's capabilities and how to use it effectively.
Browse courses on Code Generation
Show steps
  • Visit the AWS CodeWhisperer Tutorial page
  • Follow the step-by-step instructions to set up CodeWhisperer and use it in your IDE
  • Complete the exercises and challenges to practice using CodeWhisperer's features
Practice using CodeWhisperer in Visual Studio Code
Become proficient in using CodeWhisperer in an easy-to-use IDE.
Browse courses on Visual Studio Code
Show steps
  • Install Visual Studio Code and the CodeWhisperer extension
  • Open a Python or Java project in Visual Studio Code
  • Start typing code and observe the code suggestions provided by CodeWhisperer
  • Experiment with different prompts and see how CodeWhisperer helps you write code faster
Five other activities
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Assist fellow learners in the course discussion forum
Reinforce your understanding by helping others and fostering a collaborative learning environment.
Show steps
  • Join the course discussion forum
  • Monitor the forum for questions and requests for help
  • Offer assistance by providing clear and concise answers or sharing relevant resources
Build a project using CodeWhisperer and AWS APIs
Apply your knowledge of CodeWhisperer and AWS APIs to create a functional project.
Show steps
  • Choose a project idea that aligns with the course objectives
  • Design the project architecture and identify the AWS services you will use
  • Implement the project using CodeWhisperer to generate code and integrate AWS APIs
  • Test and debug the project to ensure it meets the requirements
  • Deploy the project and demonstrate its functionality
Attend an online workshop on Advanced Features of CodeWhisperer
Expand your knowledge and skills by attending a focused workshop on advanced CodeWhisperer capabilities.
Browse courses on Code Generation
Show steps
  • Find an online workshop or webinar on advanced CodeWhisperer features
  • Register for the workshop and attend the live session
  • Participate actively in the workshop and ask questions to clarify concepts
Share your CodeWhisperer experience in a blog post or article
Solidify your understanding by documenting your journey with CodeWhisperer and sharing it with others.
Show steps
  • Choose a topic related to your experience with CodeWhisperer
  • Write a blog post or article that shares your insights, tips, and lessons learned
  • Publish your article on a relevant platform or share it with your network
Contribute to the CodeWhisperer open-source project
Deepen your understanding and give back to the community by contributing to the CodeWhisperer project.
Browse courses on Code Generation
Show steps
  • Explore the CodeWhisperer GitHub repository and identify areas where you can contribute
  • Fork the repository and create a new branch for your changes
  • Make your contributions and submit a pull request
  • Collaborate with other contributors and maintainers to get your changes merged

Career center

Learners who complete Amazon CodeWhisperer - Getting Started with Generative AI will develop knowledge and skills that may be useful to these careers:
AI Scientist
Artificial intelligence (AI) Scientists work to improve computer systems, develop AI solutions, and solve real-world problems through AI. Amazon CodeWhisperer is a generative AI tool designed to assist developers and AI scientists with coding tasks. The course explores the benefits and technical concepts of CodeWhisperer, and provides hands-on experience using the tool in different IDEs. Taking this course can help AI Scientists enhance their productivity by leveraging CodeWhisperer's capabilities, ultimately enabling them to deliver innovative AI solutions.
Software Development Engineer
Software Development Engineers design, develop, test, and maintain software systems. Amazon CodeWhisperer is an AI coding companion that can generate code suggestions based on comments and existing code. By incorporating CodeWhisperer into their workflow, Software Development Engineers can streamline code writing, reduce development time, and improve code quality. This course provides a comprehensive overview of CodeWhisperer, its features, and its applications. It can equip Software Development Engineers with the knowledge and skills necessary to effectively utilize CodeWhisperer in their daily work, leading to increased productivity and code efficiency.
Machine Learning Engineer
Machine Learning Engineers build and maintain machine learning models to solve complex problems. Amazon CodeWhisperer offers AI-powered code generation and assistance, which can significantly benefit Machine Learning Engineers. This course introduces the concepts and usage of CodeWhisperer, and demonstrates how it can enhance the efficiency and accuracy of ML model development. By leveraging CodeWhisperer's capabilities, Machine Learning Engineers can reduce coding time, improve model performance, and accelerate project delivery.
Data Engineer
Data Engineers design, build, and maintain data pipelines and infrastructure to manage and process large volumes of data. Amazon CodeWhisperer can assist Data Engineers with coding tasks related to data processing, transformation, and analysis. This course provides a practical guide to using CodeWhisperer in the context of data engineering, enabling Data Engineers to streamline their workflow, improve data quality, and enhance the efficiency of data-driven processes.
Data Scientist
Data Scientists analyze and interpret data to extract meaningful insights and make data-driven decisions. Amazon CodeWhisperer can augment the capabilities of Data Scientists by providing AI-assisted coding suggestions for data analysis and modeling tasks. This course provides a comprehensive overview of CodeWhisperer, its features, and its applications in data science. By leveraging CodeWhisperer's capabilities, Data Scientists can accelerate their research, improve the accuracy of their models, and communicate their findings more effectively.
Software Architect
Software Architects design and oversee the development of software systems. Amazon CodeWhisperer can assist Software Architects in creating high-level designs and ensuring the maintainability and scalability of software solutions. This course provides a comprehensive overview of CodeWhisperer, its features, and its applications in software architecture. By leveraging CodeWhisperer's capabilities, Software Architects can enhance the quality and efficiency of their designs, leading to more robust and resilient software systems.
DevOps Engineer
DevOps Engineers bridge the gap between development and operations teams, ensuring the smooth delivery and maintenance of software systems. Amazon CodeWhisperer can assist DevOps Engineers with coding tasks related to infrastructure management, deployment automation, and continuous integration/continuous delivery (CI/CD) pipelines. This course provides a practical guide to using CodeWhisperer in the context of DevOps, enabling DevOps Engineers to streamline their workflow, improve deployment efficiency, and enhance the reliability of software systems.
Cloud Engineer
Cloud Engineers design, build, and manage cloud computing infrastructure and services. Amazon CodeWhisperer can assist Cloud Engineers with coding tasks related to cloud resource provisioning, configuration management, and serverless computing. This course provides a comprehensive overview of CodeWhisperer, its features, and its applications in cloud engineering. By leveraging CodeWhisperer's capabilities, Cloud Engineers can accelerate their cloud deployments, improve infrastructure reliability, and enhance the efficiency of cloud-based operations.
Quantitative Analyst
Quantitative Analysts develop and apply mathematical and statistical models to analyze financial data and make investment decisions. Amazon CodeWhisperer can assist Quantitative Analysts with coding tasks related to data analysis, model development, and risk management. This course provides a practical guide to using CodeWhisperer in the context of quantitative finance, enabling Quantitative Analysts to streamline their workflow, improve the accuracy of their models, and make more informed investment decisions.
Business Analyst
Business Analysts bridge the gap between business and IT, translating business requirements into technical specifications. Amazon CodeWhisperer can assist Business Analysts with coding tasks related to data analysis, process modeling, and requirements management. This course provides a comprehensive overview of CodeWhisperer, its features, and its applications in business analysis. By leveraging CodeWhisperer's capabilities, Business Analysts can streamline their workflow, improve the quality of their deliverables, and enhance the efficiency of their collaborations with technical teams.
Product Manager
Product Managers define and oversee the development of software products. Amazon CodeWhisperer can assist Product Managers with coding tasks related to product design, user experience, and roadmap planning. This course provides a practical guide to using CodeWhisperer in the context of product management, enabling Product Managers to streamline their workflow, enhance the quality of their products, and accelerate product delivery.
Security Engineer
Security Engineers design and implement security measures to protect software systems and data from cyber threats. Amazon CodeWhisperer can assist Security Engineers with coding tasks related to security auditing, threat modeling, and vulnerability management. This course provides a comprehensive overview of CodeWhisperer, its features, and its applications in software security. By leveraging CodeWhisperer's capabilities, Security Engineers can streamline their workflow, improve the accuracy of their assessments, and enhance the overall security posture of their organizations.
IT Consultant
IT Consultants provide advice and guidance to organizations on IT strategy, implementation, and management. Amazon CodeWhisperer can assist IT Consultants with coding tasks related to IT assessment, solution design, and project management. This course provides a comprehensive overview of CodeWhisperer, its features, and its applications in IT consulting. By leveraging CodeWhisperer's capabilities, IT Consultants can streamline their workflow, improve the quality of their deliverables, and enhance the efficiency of their collaborations with clients.
Technical Writer
Technical Writers create and maintain technical documentation, such as user manuals, white papers, and training materials. Amazon CodeWhisperer can assist Technical Writers with coding tasks related to documentation generation, code explanation, and knowledge management. This course provides a comprehensive overview of CodeWhisperer, its features, and its applications in technical writing. By leveraging CodeWhisperer's capabilities, Technical Writers can streamline their workflow, improve the quality of their documentation, and enhance the accessibility of technical information for users.

Reading list

We've selected 14 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 Amazon CodeWhisperer - Getting Started with Generative AI.
Provides a comprehensive overview of deep learning, covering the fundamental concepts, algorithms, and applications of deep learning. It valuable resource for those looking to gain a deep understanding of deep learning and its potential.
Provides a comprehensive overview of generative AI, covering the fundamental concepts, algorithms, and applications of generative AI. It valuable resource for those looking to gain a deep understanding of generative AI and its potential.
Provides a comprehensive guide to TensorFlow, covering the fundamentals of TensorFlow, including tensors, operations, and models. It valuable resource for those looking to gain a deep understanding of TensorFlow and its applications.
Provides a practical introduction to data science, covering the fundamental concepts, algorithms, and tools of data science. It valuable resource for those looking to gain a hands-on understanding of data science and its applications.
Provides a practical introduction to machine learning using Python and the scikit-learn, Keras, and TensorFlow libraries. It covers a wide range of machine learning algorithms, including supervised learning, unsupervised learning, and reinforcement learning. It valuable resource for those looking to gain hands-on experience with machine learning and its applications.
Provides a practical introduction to deep learning using Fastai and PyTorch, covering the fundamentals of deep learning models, training, and optimization. It valuable resource for those looking to gain a hands-on understanding of deep learning and its implementation using Fastai and PyTorch.
Provides a high-level overview of artificial intelligence, covering the fundamental concepts, algorithms, and applications of AI. It valuable resource for those looking to gain a broad understanding of AI and its potential.
Provides a quick introduction to TensorFlow 2.0, covering the basics of TensorFlow, including tensors, operations, and models. It valuable resource for those looking to get started with TensorFlow quickly and easily.
Is considered a classic in the field of reinforcement learning, providing a comprehensive introduction to the fundamental concepts and algorithms. It offers practical guidance on designing and implementing reinforcement learning systems, covering topics such as Markov decision processes, value functions, and policy optimization.
Provides a gentle introduction to machine learning, covering the fundamental concepts, algorithms, and applications of machine learning. It valuable resource for those looking to gain a basic understanding of machine learning and its potential.
Provides a comprehensive introduction to speech and language processing, covering topics such as speech recognition, natural language understanding, and computational linguistics. It offers a solid foundation for understanding the fundamental concepts and algorithms used in NLP.
Introduces the fundamental concepts of deep learning, providing a practical guide to building and training deep learning models using Python. It covers topics such as neural networks, convolutional neural networks, and recurrent neural networks.
Provides a thorough foundation in computer vision, covering topics such as image formation, feature extraction, object detection, and image segmentation. It offers a comprehensive overview of the field, from fundamental concepts to advanced techniques.

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