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Course Outline
Introduction to AI Coding Assistants
- Defining AI coding assistants.
- The historical context and progression of AI in software engineering.
- Advantages and constraints of AI coding assistants.
Core Technologies Underpinning AI Coding Assistants
- Overview of machine learning and natural language processing.
- Introduction to algorithms for code generation.
- Integrating AI with development tools.
Examining Leading AI Coding Assistant Tools
- Overview of prominent tools such as GitHub Copilot and IntelliCode.
- Practical sessions focusing on core features.
- Comparative evaluation of various tools.
Integrating into Basic Workflows
- Configuring an AI coding assistant within an IDE.
- Leveraging AI assistants for straightforward coding tasks.
- Tailoring the assistant to meet specific requirements.
Ethical Considerations and Responsible Use
- Understanding bias and fairness within AI tools.
- Fundamental guidelines for responsible utilisation.
- Privacy and security implications.
Practical Project Work
- Applying an AI coding assistant to a small-scale project.
- Peer review and constructive feedback.
- Dialogue on project enhancements and lessons acquired.
Summary and Future Steps
Requirements
- Foundational knowledge of software development principles
- Prior experience with at least one programming language (such as Python or JavaScript)
Target Participants
- Software developers
- Product managers
- Technical team leaders
14 Hours
Testimonials (1)
The way you use the copilot, more rule more close to what you need.
