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Generative AI for Software Development
Beginner
Topics
AI Coding
AI Frameworks
AI in Software Development
Chatbots
Data Processing
Document Processing
GenAI Applications
NLP
Prompt Engineering
Task Automation
Congratulations on completing this course. Over the past three modules, you've gained valuable skills to enhance your coding capabilities, and you learned how to work with an LLM like ChatGPT as your reliable pair programmer. In the first module, you saw how an LLM can help you think through data serialization and its role in a software design paradigm called configuration-driven development. You saw how JSON files can be used to externalize the configuration of an app so that settings that might change are separated from the core logic of the app itself. You also saw how you could use something like Pickle to serialize complex objects or preserve application states. You leveraged ChatGPT's deep knowledge of these concepts to implement a prototype configurable app that generates images using DALI. The second module took you into the world of databases. You discovered how to design robust and efficient databases using ChatGPT to design your schema and implement CRUD operations. Using an LLM as a database expert gives you a powerful tool to build and manage databases that are both scalable and maintainable. GPT's ability to offer real-time insights and suggestions helped you navigate complex database challenges, making you a more proficient database developer. And while the example you worked on used SQL, Alchemy, and Python, the prompting skills you learned will apply to other implementations like PostgreSQL, MySQL, or indeed any other database management system. In the final module, you looked into the realm of design patterns, focusing on those from the Gang of Four. You worked with an LLM to build out a financial services application and you applied patterns like Singleton, Factory, and Template methods to improve the app design and solve real-world problems. GPT was there to guide you through each step, providing examples and clarifications to solidify your understanding. You now have a strong foundation in using an LLM to think through design patterns and to create flexible, reusable, and maintainable code. As you move forward in your coding journey, remember that the skills and knowledge you've gained here are just the beginning. LLMs like ChatGPT, Cloud, or Gemini will continue to be powerful allies, helping you tackle new challenges and refine your craft. But I will encourage you to remember this. Don't let the LLM dictate your code. I'm seeing increasing sentiment about junior developers taking code from an LLM and just using it without fully understanding it. The more senior developers then have to take on the technical debt of fixing the bugs and issues that arise. Remember, someday you might be that more senior developer. When we see lots of code generated for us, it's tempting to use it and then just move on to the next problem. But please don't. It's sacrificing the future to save the present. Instead, keep experimenting, keep learning, and most importantly, keep coding. Your future as a proficient and efficient developer looks bright. Thank you for being a part of this course and happy coding.
