One of the most distinguished engineering programs in the world, Engineering Science (EngSci) is designed for students who are looking for an intense academic challenge.In your first two years, you’ll be immersed in engineering, math, science, computing and humanities. In your last two years, you’ll choose from one of eight majors for accelerated, discipline-specific learning. Our students thrive in a close-knit community of exceptional individuals, creating an enriched and unique learning environment.Through discipline-specific specializations, multidisciplinary minors and certificates, and unique professional opportunities, you can customize your U of T Engineering degree to meet your own developing interests at every stage of your academic journey. Academic flexibility combined with a wide range of optional curricular and co-curricular opportunities means that you graduate equipped with the engineering competencies, professional confidence and global perspective to address complex challenges.As a part of your U of T Engineering experience, you will gain a minimum of 600 hours of practical experience. This ensures that you obtain significant experience with professional responsibility before graduation. Your 600 hours may be fulfilled at any point during your degree and can include many facets, from working in industry to conducting research. Successful completion of the Professional Experience Year Co-op Program automatically satisfies this requirement.Machine intelligence is the study, development and application of algorithms that can identify patterns in data and, using these insights, make decisions when confronted with new situations. Engineers trained in machine intelligence work on problems as diverse as finding tumours in medical scans, helping retailers predict which items to stock, and helping self-driving cars to find their way. EngSci's Machine Intelligence major was launched in 2017 as Canada's first undergraduate program in this field. It provides students with a cutting-edge education in the mathematics, computation, computer hardware, and the software engineering behind artificial intelligence, machine learning, and big data analytics.