The course provides a comprehensive exploration of how generative AI is reshaping software development by accelerating coding, improving debugging, and enhancing automation. It is designed for aspiring software engineers, developers, and professionals who want to integrate AI into modern development workflows to build efficient, scalable, and error-free applications.


您将学到什么
Apply generative AI to code generation, debugging, and testing for faster, error-free development workflows.
Build expertise in AI-powered developer tools like GitHub Copilot, ChatGPT, and CodeWhisperer for software engineering.
Implement embeddings, retrieval-augmented generation (RAG), and fine-tuning to optimize AI-driven applications.
Evaluate ethical issues, collaboration models, and future trends in AI-powered software engineering.
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7 项作业
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该课程共有2个模块
This module introduces learners to the fundamental concepts of Generative AI and its applications in software development. It covers key AI technologies, including Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning, explaining their differences and real-world use cases. Learners will explore the evolution of Generative AI, comparing it with Discriminative AI, and understand how these models contribute to tasks such as content creation, classification, and predictive analysis. Additionally, the module examines the latest AI models, such as GPT, Gemini, and Copilot, showcasing their role in software engineering. By the end of this module, learners will have a strong foundation in Generative AI, preparing them for advanced applications in coding, automation, and AI-driven software development.
涵盖的内容
10个视频2篇阅读材料3个作业1个讨论话题
This module explores the transformative role of AI in modern software engineering. It covers AI-powered code generation, debugging, and optimization, demonstrating how tools like GitHub Copilot, ChatGPT, and CodeWhisperer assist developers in writing efficient, maintainable, and error-free code. Learners will also delve into advanced AI concepts such as embeddings, retrieval-augmented generation (RAG), and fine-tuning, gaining insights into their applications in real-world software development. The module concludes with discussions on the future of AI in software engineering, human-AI collaboration, and the ethical considerations developers must address when integrating AI into their workflows.
涵盖的内容
9个视频1篇阅读材料4个作业
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常见问题
Generative AI in software development automates coding, debugging, and documentation tasks. Tools like GitHub Copilot and ChatGPT enhance developer productivity, reduce errors, and accelerate software delivery.
You will learn how to apply generative AI to software engineering tasks, including code generation, debugging, testing, and optimization. The course also covers advanced topics like embeddings, retrieval-augmented generation (RAG), and fine-tuning, giving you the ability to build AI-driven applications.
The course provides hands-on practice with popular developer tools such as GitHub Copilot, ChatGPT, and CodeWhisperer. You will use these tools to generate code, fix bugs, and accelerate project workflows.
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