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Duration 14 hours
Course Outline
Introduction to Artificial Intelligence (AI) Coding Assistance Tools
- Definition and function of AI-based programming aids
- Historical progression of AI integration in software engineering
- Evaluation of operational advantages and inherent constraints
Foundational Technologies Supporting AI Coding Assistants
- Fundamental concepts of machine learning and natural language processing
- Mechanisms underlying automated code generation
- Interoperability with existing development environments
Examination of Standard AI Coding Assistant Platforms
- Review of established solutions such as GitHub Copilot and IntelliCode
- Practical application of core functionalities
- Comparative assessment of available toolsets
Integration into Standard Development Workflows
- Configuration of AI assistants within Integrated Development Environments (IDEs)
- Application of AI tools to routine programming tasks
- Tailoring assistant settings to specific operational requirements
Ethical Frameworks and Responsible Utilization
- Analysis of bias mitigation and fairness in algorithmic outputs
- Standard protocols for accountable and responsible deployment
- Data privacy protections and security risk management
Applied Project Exercises
- Implementation of AI assistance in a scoped development project
- Peer evaluation and constructive feedback processes
- Review of project outcomes and key operational lessons
Concluding Summary and Recommended Next Steps
Requirements
- Foundational knowledge of software development principles
- Proficiency in at least one programming language (e.g., Python, JavaScript)
Target Audience
- Software developers
- Product managers
- Technical team leaders
Testimonials (1)
The way you use the copilot, more rule more close to what you need.