Hands-on Data Science
AI in Public Safety and Security
Adrian Dunkley
Adrian Dunkley is the founder and CEO of StarApple AI, Jamaica's first AI and Data Science company, he has a background in fintech, tourism, and sports science. He's held leadership roles in multinational corporations and is the President of the Jamaica Technology and Digital Alliance. Adrian aims to establish a Caribbean Space Agency and is a Data Scientist and A.I Engineer with 15+ years of experience. He holds a double major in Mathematics and Physics and a Masters in Enterprise Risk Management.
3 Days
Duration-
500Per Person
Individual -
200Per Person
Groups of 5+ participants
Course Description:
In this 3-day course, delve into the emerging role of AI in public safety and security. Discover how AI technologies, from predictive policing algorithms to facial recognition systems, can enhance public safety measures. Our AI experts will guide you through ethical considerations, ensuring the responsible and transparent use of these technologies. Learn about the challenges, benefits, and best practices of integrating AI into public safety initiatives to create safer communities.
Syllabus:
- Introduction to AI in Public Safety and Security: Overview of AI technologies and their potential to enhance public safety measures, including predictive policing and facial recognition systems.
- Ethical Considerations in AI Deployment: Examining the ethical implications of using AI in public safety, focusing on privacy, consent, and potential biases.
- AI Technologies for Public Safety: Deep dive into specific AI applications in public safety, including use cases, benefits, and limitations.
- Best Practices for Implementing AI in Public Safety: Strategies for the responsible and transparent integration of AI technologies into public safety initiatives.
- Challenges and Future Directions: Discussion on the challenges faced when deploying AI in public safety and security, and exploring future trends and possibilities in this evolving field.
Prerequisites:
- There are no prerequisites for this course.
Grading Policy:
- 2 exams
- 1 capstone project
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