Code Generation with Amazon Q

This course ‘Amazon Q Developer Essentials: AI-Powered Coding’ will give you a strong grasp of the basics but facilitate your mastery in application. This course begins by introducing learners to Amazon Q Developer and builds up essential skills for integrating AI-powered solutions into their workflows, focusing on software development and troubleshooting. Key aspects include setting up Amazon Q Developer, using it for code enhancements, and optimizing workflows. The course employs short, engaging learner-centric videos of interactive lectures and interesting applications to ensure a comprehensive and practical learning experience. This course is designed for Software Developers, IT Professionals, DevOps Engineers, AWS Solution Architects, and Technical Leads and Managers looking to enhance their workflows using AI tools in AWS environments. It equips learners with the skills to seamlessly integrate Amazon Q Developer into their cloud-based development and operations. Participants should have a basic grasp of AWS services, familiarity with at least one programming language, and a working understanding of AI concepts. These skills ensure readiness to navigate the AWS ecosystem and leverage the AI-driven functionalities of Amazon Q Developer. By the end of this course, learners will be able to recognize and set up Amazon Q Developer within the broader Amazon Q ecosystem, enabling seamless integration with their AWS workflows. They will also be able to identify the key features and capabilities of the tool, leveraging its AI-driven functions to improve code quality and efficiency. Finally, learners will gain hands-on experience applying Amazon Q for code generation, troubleshooting, and optimization, making them proficient in utilizing AI to streamline development processes

• Recognize Amazon Q Developer’s role within the Amazon Q ecosystem
• Identify key features of Amazon Q Developer
• Apply Amazon Q for code enhancements and real-time completions
• Utilize Amazon Q for generation, troubleshooting, and optimization

• Basic familiarity with topic and terminology
• Willingness to practice via applied exercises or case studies