Mastering AI Tools for Software Engineers

Upon completion of this course, students will be able to:

• Delve into the role of AI in code troubleshooting, simplification, pattern enforcement, and the analysis of best practices, aiming to elevate code quality and adherence to industry standards
• Implement a fully constructed and populated database complete with constraints by using only carefully constructed prompts
• Create complex scripts for various artifacts in different database management systems
• Explore the use of AI tools in automating code creation and generating comprehensive documentation, focusing on improving code quality and developer productivity
• Understand how AI tools can be integrated into Integrated Development Environments (IDEs) and other platforms, enhancing coding efficiency and providing on-demand assistance across various programming tasks
• Understand the fundamentals of the OpenAI API and its applications in automation
• Develop skills to integrate AI capabilities into Microsoft Office applications (Word and Excel) and the Visual Studio IDE
• Create and deploy automation scripts and add-ins that leverage AI for enhanced productivity and decision-making
• Learn about the application of AI tools in game development, focusing on narrative generation, character development, and gameplay optimization

Software Engineers
 

• Successful completion of DSAI-101 Introduction to Mastering AI Tools and DSAI-102 Mastering AI Tools: Implementation and Practical Applications or equivalent knowledge

Code Troubleshooting, Simplification, and Best Practices with AI

• AI-Assisted Debugging: Identifying and Fixing Code Issues

Code Simplification Using AI: Refactoring Code for Better Performance and Readability

• Enforcing Coding Patterns and Standards with AI Tools
• AI in Analyzing and Implementing Best Programming Practices
• Real-World Scenarios: Improving Legacy Code with AI Assistance
• Labs:
  • Debugging a Codebase with AI Support
  • Refactoring and Simplifying Code Using AI Recommendations
  • Implementing and Enforcing Best Practices in a Sample Project with AI Guidance

Database Design and Development

• AI-Assisted Debugging: Identifying and Fixing Code Issues
• Code Simplification Using AI: Refactoring Code for Better Performance and Readability
• Enforcing Coding Patterns and Standards with AI Tools
• AI in Analyzing and Implementing Best Programming Practices
• Real-World Scenarios: Improving Legacy Code with AI Assistance

Labs:

• Debugging a Complex Codebase with AI Support
• Refactoring and Simplifying Code Using AI Recommendations
• Implementing and Enforcing Best Practices in a Sample Project with AI Guidance

Code Creation and Documentation with AI

• Automating Code Creation with AI: Techniques and Tools
• Generating Documentation Using AI: From Code Comments to Full Documentation
• Enhancing Code Readability and Maintainability with AI-Generated Documentation
• Integrating AI Tools into the Development Workflow for Efficient Coding

Case Studies: Examples of AI-Assisted Code Creation and Documentation

• Labs:
  • Creating a Simple Application Using AI-Generated Code
  • Generating Documentation for Existing Codebases with AI Tools
  • Evaluating AI-Generated Code and Documentation for Quality and Clarity

IDE Other Integration Points

• Overview of Popular IDEs and Their Compatibility with AI Tools
• Setting Up ChatGPT and Other AI Tools within IDEs
• Using AI for Code Completion, Debugging, and Refactoring
• Custom Integrations: Extending IDE Capabilities with AI
• Beyond IDEs: AI Tools in Notebooks, Online Forums, and More
• Security and Privacy Considerations in IDE AI Integration
• Labs:
  • Configuring ChatGPT in Visual Studio Code and JetBrains IDEs
  • Building a Custom Plugin for AI-Assisted Coding in an IDE
  • Creating solution workflows
  • Optional Utilizing AI Tools in Jupyter Notebooks for Data Science Tasks

Mastering the OpenAI API and Office Automation using AI APIs.

• Introduction to OpenAI and AI APIs
• Overview of AI APIs and their impact on automation and productivity
• Getting started with the OpenAI API:
• registration, documentation, and API key setup.
• Office Automation Basics
• Introduction to Office automation: VBA, Office Scripts, and Add-ins
• Overview of Python for Office automation.
• Integrating OpenAI API with Microsoft Word
• Automating content creation and summarization.
• Building intelligent Word add-ins using OpenAI API.
• Integrating OpenAI API with Microsoft Excel
• Enhancing data analysis and spreadsheet management with AI.
• Creating Excel functions and macros that call the OpenAI API.
• Utilizing OpenAI API in Visual Studio IDE
• Setting up the OpenAI API SDK in Visual Studio
• Developing applications and tools that leverage AI for coding assistance, code generation, and more
• Best practices for API usage, including rate limits and data privacy
• Labs:
  • Configuring the OpenAI API Environment
  • Setting up the OpenAI API key in Postman and testing basic API calls.
  • Automating Tasks in Word and Excel
  • Creating a Word document automation script for content generation.
  • Developing an Excel macro that uses the OpenAI API to analyze spreadsheet data.
  • Building an AI-Powered Add-in for Word
  • Designing and developing a Word add-in that integrates OpenAI API for real-time content suggestions.
  • Application Development with OpenAI API in Visual Studio
  • Creating a simple .NET application that uses the OpenAI API to generate code snippets based on user input.

AI in Game Development

• AI-Generated Narratives and World-Building
• Using AI for Character Development and Dialogues
• Balancing Gameplay with AI Insights
• Player Behavior Analysis with AI
• Future Trends: AI's Role in Immersive Gaming Experiences

Labs:

• Creating a Storyline for a Game with ChatGPT
• Developing AI-Generated Characters and Dialogues
• Analyzing Player Data to Optimize Game Design

Day Summary This immersive exploration of AI in the world of software development provides a solid understanding and firsthand experience in using AI Tools to aid the planning, development and testing of software applications while ensuring design patterns and best practices are enforced. Students are exposed to various ways in which AI can make them a powerhouse of efficiency and productivity not just as a software developer but a project lead, database designer or technologies specialist.