Education
At the AI Centre for Decision Analytics, we engage undergraduate and graduate students with AI and analytics courses as well as innovative research and opportunities to explore scenarios outside the classroom through experiential learning and innovative research.
AI + Analytics Courses
Application of predictive statistical models extends across critical domains, including insurance risk management, credit risk evaluation, targeted advertising, appointment scheduling, hotel and airline overbooking, and fraud detection. This course equips students with the essential skills to extract data from relational databases, prepare it for analysis, and construct predictive models using machine learning algorithms. The emphasis is on the practical application of analytical tools to enhance decision-making, prioritizing real-world impact over intricate algorithmic details.
Prescriptive analytics involves the use of data, mathematical models, and algorithms to identify optimal solutions for achieving organizational goals. This process builds on descriptive and predictive analytics, going beyond the interpretation of past events and the forecasting of future scenarios to also provide advice on the most effective actions to meet business objectives. Students acquire the skills to convert complex business problems into mathematical models, and employ Python programming and commercial solvers to derive optimal decisions.
Visual displays of quantitative information include charts, tables, maps, dashboards, animations, and more. Such displays can be used to understand, to inform, and to convince. This course will focus on strategies for carefully and clearly communicating analytical findings to the people who need to take action based on them. Students learn to use both basic tools (MS Excel) and advanced tools (Tableau and R) to create visual displays.
Application of database concepts in organizations. A comprehensive introduction to the design and development of relational databases from a logical data model. The relational database access language SQL is used along with a number of key-software development tools. Effective data administration techniques for enforcing integrity and security as well as enhancing performance are discussed. Topics of special current interest include data warehousing and the object-oriented data model.
Undergraduate students
For undergraduates, AI4DA facilitates consulting projects where students work on real-world problems and data sets from our industry partners. These projects give students hands-on experience applying AI and analytics approaches to complex business challenges across diverse sectors. Students gain exposure to the practical implementation of cutting-edge techniques covered in their coursework. Our industry partners benefit from fresh perspectives and innovative solutions.
Opportunities
- OM 468: Students enrolled in OM 468 will have the opportunity to dive into a substantial group consulting project that addresses quantitative approaches to real-world business problems.
Graduate students
At the graduate level, AI4DA offers unparalleled opportunities for master’s and PhD students to engage in cutting-edge research. Our students immerse themselves in real-world challenges initiated by our esteemed industry partners. This hands-on approach allows them to apply their theoretical knowledge to tangible, industry-specific problems, providing invaluable experience. Moreover, it opens doors to an extensive network of professionals, fostering connections that extend beyond the academic realm. AI4DA is not just a learning environment; it's a launchpad for students to make a meaningful impact and build lasting connections in their field.
Opportunities
- AI4DA hosts seminars, workshops and networking events where students can interact with faculty, researchers and industry leaders. These activities facilitate knowledge sharing and foster meaningful connections. Students may participate as volunteers to gain valuable organizational experience.