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Software Engineer AI Alumni Course

Course description

The AI content for Software Development combines guided sessions with hands-on practice to help learners build confidence in using AI tools. Practical skills will be developed through hands-on labs and projects to ensure real-world application readiness. Learners will gain foundational skills in using AI for software development tasks including: Prompting, Generating and refining code, Testing, debugging and automating tasks, Applying ethical principles while using AI, Collaboration in AI-assisted environments, and Continuous learning to stay updated on evolving AI technologies.

They will develop a Weather App using their new AI skills.

Tools you will explore

  • ChatGPT
  • Copilot
  • Qodo Gen
  • Roo Code
  • Chatbase
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Modules

➤ Introducing: Artificial Intelligence in the IT World (35 min)

  • Understand the basics of artificial intelligence and its key concepts
  • Distinguish between the different types of artificial intelligence, such as chatbots and agentic AI
  • Test previous knowledge of AI concepts to identify knowledge gaps

➤ Analytical Thinking & Productivity in the Age of AI (40 min)

  • Understand the structure of the analytical thinking process
  • Identify how AI can be used at various stages of the analytical thinking process
  • Understand the use of AI in IT roles to increase productivity
  • Evaluate the appropriateness of AI tools for solving specific problems

➤ Communicating with AI (45 min)

  • Recognise the limitations and risks of AI use in professional settings
  • Evaluate examples of ethical vs non-ethical use of AI in professional settings
  • Explore different approaches to prompting to communicate effectively with AI
  • Practise drafting a README file with the help of AI

➤ Introduction & Project Setup (1 hour)

  • Identify the core capabilities of AI-assisted development tools
  • Define the scope and objectives of an AI-assisted coding project
  • Configure a basic environment conducive to AI-driven development

➤ Prompt Engineering for Coding (1 hour)

  • Differentiate between effective and ineffective prompts for AI code generation
  • Apply prompt-refinement techniques to request or retrieve relevant data
  • Construct a basic function using AI-generated code to interact with an external service or API

➤ AI-Assisted Debugging & Testing (1 hour)

  • Incorporate error logs or test failures into AI prompts for effective debugging
  • Generate basic test cases guided by AI-based recommendations
  • Evaluate the correctness and reliability of AI-suggested fixes

➤ Documentation & Code Review with AI (1 hour)

  • Generate preliminary documentation leveraging AI suggestions
  • Assess AI-based code review feedback for potential improvements
  • Refine docstrings or other project documentation for clarity and comprehensiveness

➤ Advanced Feature Implementation (1 hour)

  • Integrate an advanced feature informed by AI-suggested recommendations
  • Appraise the viability of AI-driven refactoring or feature additions in real-world scenarios

➤ Ethics & Security in AI-Generated Code (1 hour)

  • Recognise common ethical and security considerations in AI-generated code
  • Discuss licensing and data-privacy implications related to AI-driven development
  • Formulate strategies to mitigate risks and maintain responsible AI usage

➤ Capstone and Final Reflection (1 hour)

  • Present a completed AI-assisted coding project that integrates the techniques learned
  • Reflect on individual and collaborative learning experiences throughout the process
  • Identify potential next steps or future projects building on AI-based development skills
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