Class Image Processing

The objectives of this course unit are: Teach students skills that enable them, in the role of a software developer, to responsibly delegate parts of software development work to LLMs and other Generative AI tools. Examples include: requirements, small functions/classes, and possibly tests. Develop critical thinking regarding these new tools and others of the same kind (evaluate, question results, compare, draw conclusions, etc.). Foster clear and unambiguous communication skills (e.g., providing examples, contextualizing, etc.). Promote ethical and responsible use of these tools.

Not applicable

Generative AI Literacy Introduction to Large Language Models Ethics and Copyright Ethical implications of using LLMs (ethics, intellectual property, security, …) Techniques to improve LLM outputs: fine-tuning, RAG, prompt engineering Systematic code reading and analysis Debugging with the IntelliJ debugger Critical Thinking and Skeptical Thinking Introduction to both types of thinking Key differences between the two types of thinking The importance of both types of thinking in the LLM era Problem decomposition and modularization Software Testing Test types (e.g., manual, automatic, integration, unit, etc) Unit testing with JUnit Test Driven Development (TDD) Introduction to Code Review/Verification Exploring existing code with the help of LLMs Integrating LLMs into software via API Retrieval-Augmented Generation  

Use of "Custom GPTs" configured to introduce errors that students must find in the code. Guided interaction with LLMs (i.e., ChatGPT, etc.). Presentation of real-world use cases in which LLMs caused problems.

Vladimir Khorikov – Unit Testing: Principles, Practices, and Patterns. 2.ª edição. Shelter Island, NY : Manning Publications, 2020. 1 volume (xx + 300 p.) : il. ISBN 9781617296277.   Roy Osherove – The Art of Unit Testing: With Examples in .NET. 2.ª edição. Shelter Island, NY : Manning Publications, 2013. 1 volume (xx + 320 p.) : il. ISBN 9781617290893.