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 7 hours
Course Outline
Foundations of Responsible AI
- Defining responsible AI and its significance in software development
- Core principles: fairness, accountability, transparency, and privacy
- Case studies of ethical lapses and AI misuse in codebases
Bias and Fairness in AI-Generated Code
- How LLMs may amplify biases present in training data
- Strategies for detecting and correcting biased or unsafe code suggestions
- Understanding AI hallucinations and the potential for large-scale error introduction
Licensing, Attribution, and IP Considerations
- Navigating open-source licenses (MIT, GPL, Copyleft)
- Determining whether LLM-generated outputs necessitate attribution
- Auditing AI-assisted code for potential third-party licensing conflicts
Security and Compliance in AI-Assisted Development
- Safeguarding code integrity and avoiding insecure patterns generated by LLMs
- Aligning with internal security guidelines and industry regulations
- Maintaining auditable documentation for AI-assisted decision-making processes
Policy and Governance for Development Teams
- Formulating internal AI usage policies for software teams
- Establishing acceptable use boundaries and identifying red flags
- Selecting appropriate tools and responsibly onboarding AI assistants
Evaluating and Auditing AI Output
- Utilizing checklists to assess the trustworthiness of generated content
- Performing manual and automated reviews of AI-generated code
- Implementing best practices for peer-review and sign-off workflows
Summary and Next Steps
Requirements
- A foundational grasp of software development workflows
- Familiarity with Agile, DevOps, or broader software project methodologies
Target Audience
- Compliance teams
- Developers
- Software project managers
Testimonials (1)
That i gained a knowledge regarding streamlit library from python and for sure i'll try to use it to improve applications in my team which are made in R shiny
