Course Curriculum

The MSc in Data Science and Analytics curriculum at Toronto Metropolitan University includes a blend of core courses, electives, seminar training, and either a Major Research Project (MRP) or a Thesis. Required courses ensure students gain foundational knowledge in algorithm design (DS8001), machine learning (DS8002), big data management (DS8003), and data mining with prescriptive analytics (DS8004). Thesis stream students also take a Directed Study course (DS8016). Electives allow specialization in areas such as social media analytics, deep learning, graph mining, NLP, Bayesian methods, interactive decision processes, and advanced data visualization. Students also complete two seminar courses: DS8005 (focusing on soft skills, communication, and ethics) and DS8012 (research skills). MRP students must conduct applied research under faculty supervision, present findings in a technical report, and defend their work orally. Thesis students undertake original research, submit a formal thesis, and defend it before an academic committee. Both the MRP and Thesis are milestone requirements and demonstrate a student’s research competence and understanding of advanced data science topics.