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
Core Principles of Responsible AI
- Defining responsible AI and its significance in the software development context
- Key principles: fairness, accountability, transparency, and privacy
- Case studies of ethical lapses and AI misuse within codebases
Addressing Bias and Fairness in AI-Generated Code
- How LLMs may perpetuate bias through their training data
- Strategies for identifying and correcting biased or unsafe code suggestions
- Understanding AI hallucination and the associated risks of large-scale errors
Licensing, Attribution, and Intellectual Property
- Navigating open-source licenses (including MIT, GPL, and Copyleft)
- Determining if LLM-generated outputs necessitate attribution
- Conducting audits of AI-assisted code for third-party license compliance
Security and Compliance in AI-Assisted Development
- Prioritizing code safety by avoiding insecure patterns generated by LLMs
- Adhering to internal security standards and industry regulatory requirements
- Maintaining auditable records of AI-assisted decision-making processes
Establishing Policy and Governance for Development Teams
- Drafting internal policies for AI utilization in software teams
- Setting clear acceptable use guidelines and identifying warning signs
- Selecting appropriate tools and implementing responsible onboarding for AI assistants
Evaluating and Auditing AI Outputs
- Employing checklists to gauge the reliability of generated content
- Performing both manual and automated reviews of AI-generated code
- Adopting best practices for peer review and approval workflows
Recap and Future Actions
Requirements
- A fundamental grasp of software development processes
- Familiarity with Agile, DevOps, or broader software project methodologies
Target Audience
- Compliance specialists and teams
- Software 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
