COURSE CURRICULUM

The Master of Engineering in Applied Data Science (MADS) program includes a structured set of core technical, professional, and elective courses designed to build advanced expertise in data science and its applications. Students begin with compulsory core technical courses that provide strong foundations in algorithms, data systems, and machine learning, including Algorithms and Data Models (CSC501), Systems for Massive Datasets (CSC502), Data Mining (CSC503), Optimization for Machine Learning (ECE503), Data Analysis and Pattern Recognition (ECE535), and Applied Data Analysis (ECE537). In addition, students complete compulsory professional development courses such as Professional Foundation (ECE591) and Career Development I and II (ECE592A/B), which focus on communication, teamwork, and career readiness in data-driven industries. These professional courses may be replaced with electives if approved by a supervisor. Students then select 4.5 units of electives from a wide range of advanced topics in computer science, electrical and computer engineering, and statistics. Electives may include areas such as machine learning theory, cryptography, information visualization, operations research, statistical computing, security, and quantum algorithms. The program offers flexibility while maintaining strong technical depth, allowing students to tailor their studies toward specific interests in data science. Overall, the MADS curriculum is designed to prepare graduates for advanced roles in analytics, machine learning, and data-intensive industries by combining theoretical knowledge with practical, applied learning.