This course teaches developers how to use generative AI tools to enhance software workflows, optimize code quality, and streamline debugging and testing processes. Building on foundational coding and AI concepts, you'll learn to use generative AI as both a troubleshooting aid and a quality assurance assistant. The course emphasizes real-world applications, guiding you through tasks such as test case generation, debugging, code translation, and refactoring using generative AI tools. You'll gain insights into AI-assisted testing, debugging, and code migration while maintaining industry-standard quality and security benchmarks. By the end of the course, you’ll be equipped to apply AI-powered solutions to optimize your development processes and enhance code quality.
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What you'll learn
Describe how to use generative AI tools and platforms to streamline software development
Evaluate the effectiveness of AI-integrated workflows in improving software development efficiency, accuracy, and maintainability
Develop a simple full-stack application using generative AI tools
Design complex, multi-step AI prompts to solve development challenges
Skills you'll gain
Details to know
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There are 5 modules in this course
This module introduces the fundamental principles of code quality and the role of AI in maintaining and improving codebases. You will explore techniques for identifying and resolving code smells, addressing technical debt, and utilizing AI tools to refactor and optimize code for enhanced maintainability and performance. By the end of this module, you will be equipped with the knowledge and skills to effectively apply these concepts in real-world scenarios.
What's included
7 videos4 readings4 assignments5 plugins
This module focuses on how AI tools assist developers in debugging and resolving complex software issues. You will explore the capabilities of AI in identifying root causes, optimizing code for better performance, and addressing challenges in software systems. Through practical exercises and labs, you will gain hands-on experience in using AI tools to streamline problem-solving processes and enhance debugging workflows.
What's included
7 videos1 reading5 assignments1 discussion prompt8 plugins
This module explores how AI tools transform the software testing process, making it more efficient and comprehensive. You will discover how AI automates test case generation, enhance test coverage, validate workflows, and improve the overall reliability of software testing practices. Through hands-on exercises and labs, you will develop the skills to integrate AI tools into your testing workflows for better results and faster iterations.
What's included
4 videos1 reading4 assignments8 plugins
This module focuses on how AI tools assist developers in translating code across programming languages and migrating legacy systems to modern architectures. You will explore AI-driven techniques for multi-language projects, addressing compatibility issues, and optimizing migration workflows. Through practical exercises and labs, you will gain hands-on experience using AI tools to streamline and enhance code translation and migration process.
What's included
5 videos1 reading4 assignments7 plugins
In this module, you will apply the knowledge and skills gained throughout the course to complete a final project that simulates real-world challenges. You will use AI tools to design and implement solutions for complex development scenarios, demonstrating their mastery of course concepts. The module concludes with a final assessment and reflection on how to integrate AI into future projects and workflows effectively.
What's included
1 video2 readings1 assignment1 peer review2 plugins
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