Graduate Certificate in Applied A.I. Solutions Development (Co-op) George Brown College - Casa Loma Campus, Canada

As we advance further into this increasingly digital world, Artificial Intelligence and Data Science will revolutionize most industries by optimizing business processes and automating decision-making in many white-collar jobs. The Applied A.I. Solutions Development program will instill graduates with the skills needed to provide existing businesses and emerging startups with the tools required to thrive in the digital revolution.

This three-semester graduate certificate program uses a hands-on, applied approach to the field of A.I., giving students the broad range of skills needed to excel in this rapidly growing industry.

It teaches the development and application of Machine Learning/Deep Learning models and provides a fundamental understanding of the underlying mathematical algorithms that power them. This combination of knowledge and skills will allow graduates to identify and select appropriate algorithms for a given use, build and fine-tune models, and visualize and effectively communicate the resulting data, thereby bridging the traditional roles of Data Scientist, Machine Learning Engineer and Business Translator.

Your Field Education Options

• To be eligible for co-op, a student must complete all Semester 1 and Semester 2 courses. As well, an overall GPA of 3.0 must be achieved.
• During the third semester of the program, students may choose whether to apply for a Co-op position or take a Work Integrated Learning course that includes an industry-sponsored project.

Program Learning Outcomes

• The graduate has reliably demonstrated the ability to:
  • Identify, evaluate and manage relevant data sources to support data analytics and to meet organizational needs.
  • Recommend different systems, architectures and data storage technologies to support data-driven solutions.
  • Develop and deploy complete Machine Learning/Deep Learning production systems for a variety of industry use cases that meet the needs of a specific operational/business process.
  • Assess and apply appropriate mathematical models, algorithms, tools and frameworks to develop A.I.-enabled, industry-specific solutions.
  • Design and present A.I. solutions effectively to stakeholders through the use of data visualizations.
  • Apply legal, ethical, privacy and security-related standards and considerations in data science projects in a manner that protects privacy and confidentiality, addresses data bias and transparency, and ensures data integrity.
  • Implement artificial intelligence systems on time and budget using best practices and strategies in design thinking, project management and lifecycle management.
  • Design artificial intelligence (A.I.) systems through the application of systematic approaches and methodologies to meet growing organizational needs.