Data Ethics & Responsible Ai Training Course: Ethical Data Science

Introduction

Navigate the complex landscape of AI with our Data Ethics and Responsible AI Training Course. This program is designed to equip you with the essential skills to understand the ethical implications of data science, enabling you to develop and deploy AI solutions that are fair, transparent, and accountable. In today's data-driven world, mastering data ethics and responsible AI is crucial for building trust and ensuring the positive impact of AI technologies. Our data ethics training course offers hands-on experience and expert guidance, empowering you to integrate ethical principles into your data science workflows.

This responsible AI training delves into the core concepts of ethical data science, covering topics such as bias detection, fairness metrics, and regulatory compliance. You'll gain expertise in using industry-standard tools and techniques to understand the ethical implications of data science, meeting the demands of modern AI development. Whether you're a data scientist, AI developer, or policy maker, this Data Ethics & Responsible AI course will empower you to build and promote ethical AI practices.

Target Audience:

• Data Scientists
• AI Developers
• Policy Makers
• Data Analysts
• Machine Learning Engineers
• Business Analysts
• Anyone needing data ethics and responsible AI skills

Course Objectives:

• Understand the fundamentals of data ethics and responsible AI.
• Master bias detection and mitigation techniques in data and models.
• Utilize fairness metrics to evaluate AI system performance.
• Implement transparency and explainability in AI applications.
• Design and build ethical data science workflows.
• Optimize AI systems for compliance with ethical guidelines and regulations.
• Troubleshoot and address common ethical challenges in data science.
• Implement privacy-preserving techniques in data analysis.
• Integrate ethical considerations into real-world AI projects.
• Understand how to handle sensitive data and ensure data governance.
• Explore advanced ethical frameworks and regulatory landscapes.
• Apply real world use cases for data ethics and responsible AI.
• Leverage ethical AI tools and frameworks for efficient development.

Duration

10 Days

Course content

Module 1: Introduction to Data Ethics and Responsible AI

• Fundamentals of data ethics and responsible AI.
• Overview of ethical principles, bias detection, and fairness metrics.
• Setting up an ethical data science development environment.
• Introduction to ethical AI tools and frameworks.
• Best practices for ethical data science.

Module 2: Bias Detection and Mitigation

• Implementing bias detection techniques in data and models.
• Utilizing statistical tests and fairness audits.
• Designing and building bias mitigation strategies.
• Optimizing models for fairness and equity.
• Best practices for bias detection.

Module 3: Fairness Metrics

• Utilizing fairness metrics to evaluate AI system performance.
• Implementing metrics such as demographic parity and equalized odds.
• Designing and building fair evaluation frameworks.
• Optimizing fairness metrics for specific applications.
• Best practices for fairness metrics.

Module 4: Transparency and Explainability

• Implementing transparency and explainability in AI applications.
• Utilizing explainable AI (XAI) techniques.
• Designing and building transparent model documentation.
• Optimizing explanations for stakeholder understanding.
• Best practices for transparency.

Module 5: Ethical Data Science Workflows

• Designing and building ethical data science workflows.
• Implementing ethical impact assessments.
• Utilizing ethical guidelines and checklists.
• Optimizing workflows for ethical compliance.
• Best practices for ethical workflows.

Module 6: AI Compliance and Regulation

• Optimizing AI systems for compliance with ethical guidelines and regulations.
• Utilizing regulatory frameworks (GDPR, AI Act).
• Designing and building compliant AI solutions.
• Optimizing compliance for specific industries.
• Best practices for compliance.

Module 7: Troubleshooting Ethical Challenges

• Debugging common ethical challenges in data science.
• Analyzing ethical implications of AI models.
• Utilizing troubleshooting techniques for problem resolution.
• Resolving common ethical dilemmas.
• Best practices for troubleshooting.

Module 8: Privacy-Preserving Techniques

• Implementing privacy-preserving techniques in data analysis.
• Utilizing differential privacy and federated learning.
• Designing and building privacy-focused data pipelines.
• Optimizing privacy for data security.
• Best practices for privacy.

Module 9: Integration with Real-World Projects

• Integrating ethical considerations into real-world AI projects.
• Utilizing case studies and ethical frameworks.
• Designing and building ethical AI solutions for specific domains.
• Optimizing integration for societal impact.
• Best practices for integration.

Module 10: Sensitive Data and Data Governance

• Understanding how to handle sensitive data and ensure data governance.
• Utilizing data anonymization and de-identification techniques.
• Designing and building data governance policies.
• Optimizing data handling for ethical compliance.
• Best practices for data governance.

Module 11: Advanced Ethical Frameworks

• Exploring advanced ethical frameworks and regulatory landscapes.
• Utilizing ethical AI principles and guidelines.
• Designing and building ethical AI strategies.
• Optimizing advanced frameworks for specific applications.
• Best practices for advanced frameworks.

Module 12: Real-World Use Cases

• Implementing ethical AI in healthcare and finance.
• Utilizing ethical AI in criminal justice and social services.
• Implementing ethical AI in marketing and advertising.
• Utilizing ethical AI in autonomous systems.
• Best practices for real-world applications.

Module 13: Ethical AI Tools and Frameworks Implementation

• Utilizing ethical AI tools and frameworks (AIF360, Fairlearn).
• Implementing bias detection and mitigation with tools.
• Designing and building ethical AI pipelines.
• Optimizing tool usage for efficient development.
• Best practices for tool implementation.

Module 14: Ethical Model Evaluation and Monitoring

• Implementing ethical model evaluation and monitoring.
• Utilizing ethical metrics and dashboards.
• Designing and building monitoring systems for bias and fairness.
• Optimizing evaluation for ethical compliance.
• Best practices for evaluation.

Module 15: Future Trends in Data Ethics and Responsible AI

• Emerging trends in data ethics and responsible AI.
• Utilizing AI for ethical auditing and compliance.
• Implementing ethical AI in emerging technologies.
• Best practices for future applications.

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: info@skillsforafrica.org, training@skillsforafrica.org  Tel: +254 702 249 449

Training Venue

The training will be held at our Skills for Africa Training Institute Training Centre. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, training materials, two break refreshments, and buffet lunch.

Visa application, travel expenses, airport transfers, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Skills for Africa Training Institute certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: info@skillsforafrica.org, training@skillsforafrica.org  Tel: +254 702 249 449

Terms of Payment: Unless otherwise agreed between the two parties’ payment of the course fee should be done 7 working days before commencement of the training.