An “H,” or half course, is worth 0.5 credits and normally runs for one term.

Typically, “Y” courses last a full year (two semesters – like MAT137Y/MAT157Y).

CSC110 is a “Y” course, but it’s unique in that it is a full credit course offered in a single term.  This makes it a double course, meaning that you should expect the workload of CSC110 to be equal to two H courses – so in your fall semester, instead of taking five courses you will only take four: CSC110 and three others.

Both MAT137Y1 and MAT157Y1 are theoretical and proof-based approaches to calculus, and both provide excellent mathematical foundations for computer science students. MAT157Y1 is taught at a higher level of abstraction, and is particularly suited for students intending to complete one of the four MAT157Y1-stream Math specialist programs (can be taken alongside a computer science program) or to specialize in the more theoretical or mathematically-intensive aspects of computer science. The Math Department also offers a variety of specialist, major, and minor programs available to students who complete MAT137Y1. For more information about choosing between these courses, check out this advice page from the Department of Mathematics.

One recommendation if you are interested in MAT157Y1 but are unsure about the difficulty level or workload: You have the option to attend both courses in the first few weeks of class and try the assigned homework to get a sense of the style of each course. The Math Department offers the ability to change your course enrollment from MAT157Y1 to MAT137Y1 for a limited time after the regular enrollment dates.

For more information about these courses and programs of study in mathematics, please contact the Department of Mathematics.

Here are some suggestions for other courses you may be interested in completing in your first year. None of these are required for your first-year in computer science, but you may find them particularly interesting and/or useful for your long-term academic planning:

• STA130H1: An Introduction to Statistical Reasoning and Data Science. Note: This course is required to apply to the Data Science Specialist program (see here for details).

• MAT223H1: Linear Algebra I or MAT240H1: Algebra I. Despite the 200-level code, it is fairly common to see first-year computer science students taking these courses, and they are prerequisites for additional math courses that can be taken in your second year.

• CSC240H1: Enriched Introduction to the Theory of Computation. This course is offered in the winter semester only, and replaces CSC236H1, which you normally take in the first semester of your second year. Like MAT157Y1, students should consider taking CSC240H1 if they are interested in a deeper theoretical look at computer science and are comfortable with more complex proofs and mathematical rigour.

• A First-Year Foundations (FYF) course in Computer Science. FYF courses are designed to offer a small seminar-style learning experience to first-year students, and are a great way to meet other first-year students and your professor.

One of the advantages of being an Arts & Science student is that you have a huge range of courses and programs to choose from. Whatever you're interested in, there's probably a course in it! We strongly encourage you to take a broad range of elective courses in your first year, and explore your interests outside of computer science. The computer science course load gets heavier after your first year, and so now is the time to choose courses in other areas based on your interests, to to fulfill the breadth requirements you'll need to graduate.

A great way to get started to look at the different Program Areas in Arts & Science and look for subjects that interest you. Every program area page contains both courses and programs offered in that area. Many computer science students end up choosing a minor or major in a completely different field, so don't think that you must study only CS during your time at U of T.

If you’re curious about the intersection of technology and society, there are several courses open to first-year CS students with no prerequisites. These courses explore the cultural, social, historical and philosophical dimensions of technology, complementing your computer science studies:

• HPS202H: Technology in the Modern World

• NEW103H: Digital Technology and Society

• NEW113H: Unpacking Digital Technology

• PHL256: Philosophy of the Internet

The Computer Science Undergraduate Office academic advisors are here to help you with questions about CS courses and programs. To connect with them, please visit our academic advising page.

You may also want to consider connecting with your College Registrar's Office for academic advising, especially regarding overall degree planning or non-CS courses.

We have prepared a course on Quercus, U of T’s learning management system, to help you prepare for your first year Computer Science courses: First-Year Computer Science Summer Prep (log in with your JOINid and password).

You’ll be hearing from us, your college, and the Faculty of Arts & Science throughout the summer, so keep checking your U of T email regularly. Check out the New Student Guide for helpful information about enrolling in courses, getting to know your college, and more.

Your courses in first year rely heavily on PyCharm and Python 3. The system you purchase should be able to install and run both of these softwares. Here are some specifications that we recommend:

Operating System: Microsoft Windows 10/11 or macOS 10.15 (or later)
Memory: At least 4 GB of RAM (8 GB recommended)

The other specifications will depend on your budget. Avoid computers with limited capabilities, such as Chromebooks, iPads, etc. Courses in 2nd year and beyond will ask you to install more types of software depending on the topics being taught, which will likely be impossible with something like a Chromebook. Finally, it would be a good idea to invest in a laptop with a good processor - the types of processors out there vary, so brush up on reviews before picking a laptop.

No, we’ve designed CSC110 to be accessible to everyone regardless of programming experience. We have students coming in with a wide variety of backgrounds and knowledge, including no programming knowledge at all, and that’s okay!

If you have time this summer, here are some resources for learning the basics of programming in Python, which is the programming language we’ll use in our first-year courses. This is not required, but could be useful preparation to ease your transition to university life and academics this fall. The content below is based on CSC108, our department’s main introductory programming course, and CSC110 will cover similar content, albeit with different presentation and style.

• (Coursera) Learn to Program: The Fundamentals

• (Coursera) Learn to Program: Crafting Quality Code

• (textbook) Practical Programming, 3rd edition

We've actually spent a lot of time preparing some notes for the course that we'll make available online. These notes will make up the required reading for the course, and there's no required textbook outside of them.

If you are interested in textbooks for supplementary reading, for Python we recommend: Practical Programming, Third Edition - An Introduction to Computer Science Using Python 3.6 by Paul Gries, Jennifer Campbell, and Jason Montojo (https://pragprog.com/titles/gwpy3/practical-programming-third-edition/).

For the mathematical side of things, you can check out Discrete Mathematics: An Open Introduction, 3rd Edition by Oscar Levin (http://discrete.openmathbooks.org/dmoi3/).

There will be many opportunities to practice what you've learned in lecture through weekly prep, exercises, weekly tutorials, and assignments. Staying on top of all the materials and not falling behind is one of the best ways to be prepared for a term test. While you complete assessments, keep a written notebook of the concepts and questions you've struggled to understand. This gives you an idea of what you need to re-visit before a term test so that you can improve your weaknesses.

One of my (Sadia's) favourite ways to study for an exam was reviewing all the material as thoroughly as I could, and then doing as many past exams as I could from the UofT old exams repository. I would print the exams out, put on a timer, and complete the past exam closed-book to really test my understanding, and try to simulate a “test environment”. Once time was out, I would grade myself – typing up my solution to coding questions and running it on the computer to test their correctness. The “grade” I earned on the past exams gave me a good idea of how prepared I likely was for the exam, as well as helped me pinpoint areas or types of questions I was struggling with (which I could then discuss with my professors/TAs during office hours prior to the actual exam!).

While you are proving different kinds of statements in the CS and math courses, you will find that there are similarities in how you approach proofs. Proving something true is a skill that you will get plenty of practice in. In Computer Science, our proofs will focus on the correctness and efficiency of algorithms. But a lot of the mathematics you learn in your first two years act as a foundation for future computer science courses. For example, there is a strong link between linear algebra and computer graphics.