Graduate Certificate in Artificial intelligence

As artificial intelligence (AI) continues to rapidly transform the way organizations and their people work, a shortage of skilled professionals remains the single most significant challenge facing AI adoption by industry. With a focus on enterprise AI, including both off-the-shelf solutions and proprietary AI, this graduate certificate program – the first and only one of its kind in Canada – will prepare you to meet this demand for AI-literate practitioners.

Students will have the opportunity to work with industry demanding programming languages such as Python, while interacting with cutting-edge Machine Learning and Deep Learning libraries such as SKLearn and TensorFlow to create various practical AI applications. The curriculum also touches on theoretical concepts surrounding Computer Vision, Natural Language Processing, Recommender Systems, Data Visualization, and Reinforcement Learning. As a graduate, you will know how to leverage AI to extract data and use data-driven intelligence to guide decision-making, solving complex enterprise problems with state-of-the-art solutions, all while creating efficiency and quality gains for small and medium-sized enterprises up to the largest of corporations. Additional emphasis will be put on data governance, including data management to ensure its integrity. Students will also benefit from multiple opportunities for experiential learning, including access to the college’s AI Hub, completion of two diverse capstone projects and an optional work term. Graduates will be prepared to enter this high-growth field, which currently sees the Greater Toronto Area home to the highest per-capita concentration of AI companies in the world.

Graduates of the Artificial Intelligence Analysis, Design, and Implementation program will enter the workforce with a specialized skill set that includes the ability to:

• Analyze, design, and implement artificial intelligence (AI) systems through the application of systematic approaches and methodologies to meet organizational needs.
• Develop AI models and agents that use enterprise data to identify patterns, provide insights, recommend actions or perform tasks autonomously on behalf of stakeholders.
• Prepare and communicate analysis, reports, and recommendations, in a variety of formats, for various audiences, stakeholders and purposes.
• Conduct research, data analysis, model development, and solution deployment in an ethical manner that protects privacy, confidentiality, addresses data bias and transparency and ensures data integrity.
• Apply project management tools and lifecycle management strategies to implement AI systems on time and budget.
• Implement AI solutions in compliance with corporate policies, ethical standards, and industry regulations.

The AI Hub

Students will also benefit from and contribute to the Durham College Hub for Applied Research in Artificial Intelligence for Business Solutions (the AI Hub), which offers industry partners access to technical expertise, state-of-the-art facilities and platforms, and student talent, to help uncover business insights while providing intelligent and autonomous solutions that increase their companies’ productivity and growth.

Admission Requirements

• Ontario College Diploma, Ontario College Advanced Diploma or a degree, or equivalent.

OR

• An acceptable combination of related work experience and post-secondary education.
• Proof of English language proficiency required.
• Applicants whose first language is not English or who are internationally educated in a non‐English speaking country must meet Durham College’s English Language Proficiency Policy.

Note: A comfort in mathematics, statistics, computer software, computer programming, and enterprise systems is recommended.

Costs

Courses

Semester 1

• Introduction to Artificial Intelligence Development
• Applied Mathematics for Artificial Intelligence Systems
• Studies in Artificial Intelligence
• Visualization and data storytelling
• Artificial Intelligence Algorithms
• Capstone Term I

Semester 2

• Applied Machine Learning and Advanced Artificial Intelligence Systems
• Knowledge and Expert Systems
• Careers and the Digital Portfolio
• Consulting and Professional Communications
• Artificial Intelligence in Enterprise Systems
• Capstone Term II

Semester 3

• Optional Work Term

Courses and course descriptions are subject to change.

Career Options

What you could be:

• Data scientist
• AI scientist/analyst/technologist
• Machine learning analyst/technologist
• Business transformation consultant
• Business analyst
• Data Steward
• Data engineer
• AI system developer

Where you could work:

• Technology companies
• Start-up and early-stage entrepreneurial companies
• Research institutes
• Financial services providers
• Telecommunications companies
• Manufacturing organizations

Experiential Learning

Applied Research: Students will be able to engage in applied research opportunities with the Durham College Hub for Applied Research in Artificial Intelligence for Business Solutions, better known as the AI Hub.

Capstone projects: All students will complete two diverse capstone projects – one per semester – to apply their classroom learning to tangible, real-world challenges. In the first, they will use strategy games as a foundation to teach an AI system (an agent in AI terms) to operate in a complex environment and achieve strategic goals. In the second, students will synthesize learned concepts to assess an AI implementation on a commercial platform, such as IBM Watson, Salesforce Einsten or the Amazon Echo with Alexa to solve a practical business problem.

Optional work term: Students who meet all academic requirements will also have the opportunity to complete an optional work term in a formal work environment or entrepreneurial endeavor. The work term will be similar in length to an academic semester and typically involves full-time work hours that may be paid or unpaid.

Laptop Requirements

Minimum recommended hardware

• Intel I7 or AMD A10 processor or better with a chipset that must support virtualization
• 16 GB of RAM
• 1 TB hard drive
• Ethernet Network Card
• Wireless Network Card
• One USB 3.0 port (two preferred)

Software requirements

• Windows 10 Professional Edition