Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Duration 14 hours
Course Outline
Introduction to AIASE
- Overview of AI's role in software engineering.
- Historical context and the evolution of AIASE.
- Core concepts and essential terminology.
AI Technologies in Software Development
- Fundamentals of machine learning.
- Natural language processing (NLP) applications for code.
- Neural networks and deep learning models.
Automating Software Development with AI
- AI tools for generating boilerplate code.
- Automated code refactoring and optimization techniques.
- Generation of functional and unit test code.
- AI-assisted design and optimization of test cases.
Enhancing Code Quality with AI
- Leveraging AI for bug detection and code reviews.
- Predictive analytics for software maintenance.
- AI-powered static and dynamic analysis tools.
- Advanced automated debugging techniques.
- AI-driven fault localization and repair methods.
AI in DevOps and Continuous Integration/Continuous Deployment (CI/CD)
- Optimizing builds and deployments with AI.
- AI applications in monitoring and log analysis.
- Implementing predictive models for CI/CD pipelines.
- AI-based test automation within CI/CD workflows.
- Real-time error detection and resolution using AI.
AI for Documentation and Knowledge Management
- Automated creation of docstrings and documentation.
- Extracting knowledge from codebases.
- Utilizing AI for code search and reuse.
Ethical Considerations and Challenges
- Addressing bias and ensuring fairness in AI tools.
- Navigating intellectual property and licensing issues.
- Prospects for the future of AI in software engineering.
Hands-On Projects and Case Studies
- Practical work with popular AI tools in software engineering.
- Analysis of AIASE implementations in the industry.
- Capstone project: Building an AI-augmented software application.
Summary and Next Steps
Requirements
- Familiarity with software development processes and methodologies.
- Practical experience programming in Python.
- Fundamental understanding of machine learning concepts.
Target Audience
- Software developers.
- Software engineers.
- Technical leads and managers.
Testimonials (1)
Shane had everything prepared well beforehand which made sure that we were able to follow up and do some hands on practice as well.
