AI Program

The Artificial Intelligence in Certificate program at CPA is designed for educators and professionals who want to integrate artificial intelligence into educational settings. This program provides a comprehensive understanding of AI's role, ethical implications, and practical applications in education and training. Participants will gain hands-on experience through projects and case studies, equipping them with the skills to implement AI effectively in their work.

AI Management Maximization Certificate

The curriculum outlined for the AI Management Maximization subject area embodies the key knowledge, skills, values, and attitudes that students are required to develop at Certificate level.

The design of this curriculum is based on the principles and standards in the field of Artificial Intelligence and Machine Learning, as well as industry best practices and frameworks. The curriculum outlined for the AI Management Maximization subject area embodies the key knowledge, skills, values, and attitudes that students are required to develop at Certificate level. It forms the basis on which instructors can plan their individual course content and design appropriate learning, teaching, and assessment activities. Courses which can be taken at Certificate level may also form part of Recognized Prior Learning (RPL) and credited as University undergraduate subjects. The Academy may require additional electives and/or upgrade material to be taken to ensure that the course load is appropriate for the certificate level in these cases.

The design of this curriculum is based on the principles and standards in the field of Artificial Intelligence and Machine Learning, as well as industry best practices and frameworks from leading organizations such as IEEE, ACM, and major tech companies.

Key Features:

  • Online delivery with interactive workshops and case studies
  • Practical assignments based on real-world scenarios
  • Integration of both predictive and agile methodologies
  • Alignment with current AI industry standards
  • Focus on both technical and interpersonal skills
  • Designed to meet certification requirements in Canada and select USA states
COURSE DESCRIPTION NOTES
Introduction to AI and Machine Learning
Covers basic AI concepts, types of machine learning (supervised, unsupervised, reinforcement), and their applications
Practical Component: Hands-on projects using Python and libraries like TensorFlow and Scikit-learn to build simple AI models
Data Science and Analytics
Focuses on data collection, cleaning, and analysis techniques crucial for AI
Practical Component: Use real-world datasets to practice data manipulation and visualization using tools like Pandas and Matplotlib
AI Strategy and Governance
Develops strategies for AI implementation and discusses governance frameworks and ethical considerations
Practical Component: Case studies on AI ethics and governance to explore best practices and potential challenges
Big Data and AI Integration
Explores the integration of big data technologies with AI to enhance decision-making
Practical Component: Projects using Hadoop or Spark to process large datasets and apply AI algorithms
AI in Business Operations
Examines AI applications in automating business processes across various functions
Practical Component: Develop AI solutions for business challenges, focusing on efficiency and innovation
AI Product Management
Teaches how to manage AI product development, from ideation to deployment
Practical Component: Simulations of product lifecycle management, including market analysis and user feedback integration

Substitute and additional courses could be made available in the following areas:

  • Natural Language Processing and Chatbots
  • Computer Vision and Image Recognition
  • AI in Cybersecurity
  • Robotics and Automation
  • AI Ethics and Responsible AI
  • AI for Internet of Things (IoT)
  • Project Management Office (PMO) Fundamentals
  • AI in Healthcare and Bioinformatics
  • Reinforcement Learning and Game AI
  • AI for Social Good and Sustainability