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Course Outline
Introduction to AIASE for Government
- Overview of Artificial Intelligence (AI) in Software Engineering for Government
- Historical Context and Evolution of AIASE for Government
- Key Concepts and Terminology for Government Use
AI Technologies in Software Development for Government
- Fundamentals of Machine Learning for Government Applications
- Natural Language Processing (NLP) for Code Generation in Government Systems
- Neural Networks and Deep Learning Models for Government Use
Automating Software Development with AI for Government
- AI Tools for Generating Boilerplate Code in Government Projects
- Automated Code Refactoring and Optimization for Government Systems
- Functional and Unit Test Code Generation for Government Applications
- AI-Assisted Test Case Design and Optimization for Government Workflows
Enhancing Code Quality with AI for Government
- AI for Bug Detection and Code Reviews in Government Software
- Predictive Analytics for Software Maintenance in Government Systems
- AI-Powered Static and Dynamic Analysis Tools for Government Use
- Automated Debugging Techniques for Government Applications
- AI-Driven Fault Localization and Repair for Government Systems
AI in DevOps and Continuous Integration/Continuous Deployment (CI/CD) for Government
- AI for Build Optimization and Deployment in Government Projects
- AI in Monitoring and Log Analysis for Government Systems
- Predictive Models for CI/CD Pipelines in Government Workflows
- AI-Based Test Automation in CI/CD Workflows for Government
- AI for Real-Time Error Detection and Resolution in Government Applications
AI for Documentation and Knowledge Management for Government
- Automated Generation of Docstrings and Documentation for Government Systems
- Knowledge Extraction from Codebases for Government Use
- AI for Code Search and Reuse in Government Projects
Ethical Considerations and Challenges for Government
- Bias and Fairness in AI Tools for Government Applications
- Intellectual Property and Licensing Issues for Government Use
- Future of AI in Software Engineering for Government
Hands-On Projects and Case Studies for Government
- Working with Popular AI Tools in Software Engineering for Government
- Case Studies of AIASE in Industry and Government
- Capstone Project: Developing an AI-Augmented Software Application for Government Use
Summary and Next Steps for Government
Requirements
- A comprehensive understanding of software development processes and methodologies for government use.
- Practical experience with programming in Python.
- Foundational knowledge of machine learning concepts.
Audience
- Software developers
- Software engineers
- Technical leads and managers
14 Hours
Testimonials (1)
Lecturer's knowledge in advanced usage of copilot & Sufficient and efficient practical session