Faculty of Applied Science & Engineering · St. George

ESC180H1

Introduction to Computer Programming

Credit0.50

PrerequisiteNone listed

Total contact hours36.6 lecture · 36.6 practical

Evidence2 terms

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What was the average?

B+

3.15 GPA across 2 observed terms. Most recent: Fall 2025.

How is it graded?

Not yet verified

No syllabus we can lawfully use has been verified for this course.

How confident is this?

Med

A small number of terms, so read it as a range.

From the calendar

Official source · Faculty of Applied Science & Engineering

The first of two courses that introduce students to programming and computational thinking. Students will learn to use the Python programming language to implement computational solutions to problems, and will be introduced to the design and analysis of algorithms and data structures. Runtime analysis and searching and sorting algorithms will be introduced. Some computational problems will be drawn from other 1F courses.

Prerequisite: None listed
Exclusions: APS105H1APS106H1CSC192H1
Contact hours: 36.6 lecture · 36.6 practical; Total scheduled hours for the course, not per week.

What people actually got

Last observed Fall 2025

B+

3.15 GPA

2 terms observed

n = 2student contributedSt. George offerings only

This is a student-contributed aggregate, not an official University of Toronto record. It is also not a measure of how hard the course is — a course average moves with who enrols in it, not only with the material.

This rests on 2 reported terms. It is shown because hiding it would not make it less true, but one or two results are a datapoint, not a distribution — a single unusual cohort moves this number a long way.

What we don’t have yet

Assessment weightingNo syllabus we can lawfully use has been verified for this offering. Contribute yours and the breakdown appears here.

Per-term breakdownHeld back deliberately. Splitting 2 observations across terms would be false precision.

Instructor-level detailAverages are not split by instructor. At these sample sizes the difference between sections is noise, not signal.

Archive coveragePyko holds no past paper for this course. We do not host or distribute course files in any case; the archive is what lets these pages describe how a course is assessed.

Source ledger

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Sources behind every claim on this page
Claim	Source	Captured	Status
Course description, prerequisites, exclusions, contact hours	Faculty of Applied Science & Engineering	2026-07-25	public fact
Historical average across 2 terms	Student contributions, consented	2026-07-25	user contributed aggregate

Page last verified 2026-07-25. A claim whose source moves is withdrawn before it goes stale.

What this opens up

13 courses list ESC180H1 as a prerequisite

APS360H1Applied Fundamentals of Deep Learning CSC263H1Data Structures and Analysis CSC311H1Introduction to Machine Learning CSC317H1Computer Graphics CSC318H1The Design of Interactive Computational Media CSC401H1Natural Language Computing CSC485H1Computational Linguistics ESC190H1Computer Algorithms and Data Structures

The other 5 have no page yet. Listing a course here means it names ESC180H1 among its prerequisites — often as one of several ways to satisfy the same requirement, so this is what ESC180H1 makes available, not what it alone guarantees.

Around this course

APS105H1Cannot be taken with this course APS106H1Cannot be taken with this course

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