Python I

Eight weeksUp to five hours per week

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Online course with independent learning and live drop-in sessions

$599.00 + applicable taxesView available early bird and alumni discounts

Widely used across the technology landscape, Python is one of the most in-demand programming languages, known for its relatively simple syntax and well-supported community. Learning how you can use Python to manipulate data and perform complex tasks efficiently will give you a competitive edge in the job market and provide you with the necessary tools to excel in this rapidly evolving field. This course will help you develop a valuable skill set that is applicable and can be applied broadly in fields such as web development, data science, artificial intelligence, machine learning, automation, and more.

Python I is the perfect course for beginners and professionals looking to enter new industries or advance their careers. With no prior coding or programming experience required, this comprehensive course offers you the chance to work at your own pace each week while learning from an experienced instructor.

Through hands-on exercises and practice, you will learn foundational concepts, problem-solving approaches, and essential programming techniques, such as functions, loops, and string methods. You will also gain hands-on experience with Python's syntax, data structures, and functions relevant to data science roles.

The course covers a wide range of topics, including:

Functions, statements, loops
Creating, documenting robust code
Variable mutation
Boolean expressions
Strings, tuples, lists

This course can be leveraged as a stepping-stone to other technology courses offered by WatSPEED, including Data Science and Python for Machine Learning. It offers an essential starting point for data science, with an approach that is accessible and rooted in practical value. No additional software is required to complete the course, and you’ll be able to download and keep the code you work on.

Learning Outcomes

Solve introductory programming problems in Python: Gain an understanding in the basics of Python such as call functions and arithmetic and learn how to use a variety of Python data structures including strings, tuples, lists, sets, dictionaries, and classes.

Debug code and handle errors: Develop problem-solving skills while using basic imperative programming constructs such as branching and looping.

Document your code: Learn how to make your code readable and robust while documenting it to a well-known standard.

Each course module works through two fully worked real-world examples to reinforce concepts and learning. Examples are across industries and universally applicable.

Module 1: Introduction to Programming in Python	Use arithmetic to solve problems. Call functions with the appropriate parameters. Define functions. Write the design recipe for functions in Python. Using a test module to solve problems.
Module 2: Variables and Conditional Statements	Solve problems with variables. Write Boolean expressions and evaluate their True or False values. Write if, if-elif, and if-elif-else statements to be able to branch behaviour. Write iterative code using while loops.
Module 3: Input/Output and Immutable Data Types Part 1: Strings	Use string methods to solve problems. Print to the screen. Read input from the user. Understand immutable data types.
Module 4: Immutable Data Types Part 2: Tuples and Iteration	Create and manipulate tuples and solve problems involving tuples. Iteration using while and for loops with strings and tuples.
Module 5: Mutable Data Types Part 1: Lists	Use lists, list operations, and list methods to solve problems. Demonstrate a working memory model for lists. Mutate lists using iteration.
Module 6: Mutable Data Types Part 2: Sets, Dictionaries and Comprehension	Use sets and set methods to solve problems. Use dictionaries and dictionary methods to solve problems. Use the built-in sorting function to organize data. Use the abstract list functions map and filter to solve problems. Speed up the execution of code using list/set/dictionary comprehension.
Module 7: File Input and Output	Define files and be able to create new text documents Use the built-in functions chr and ord Explain how strings are stored in the context of files Read and write from and to Python files Explain and identify appropriate uses of advanced modes of Python file reading and writing (append, exclusive creation, seek, tell, binary mode) Handle exceptions using try-except-else-finally Document code using our style guide for files
Module 8: Classes	Create classes, class methods, and functions that consume class objects. Explain the purpose and operation of magic methods. Create magic methods, specifically __init__, __str__, __repr__, __eq__. Save objects using pickle and shelve.

Professionals looking to start their career journey towards a technical role while learning the core concepts of Python.
Newcomers to Canada looking for to upskill and enter the technology workforce.
Learners need to learn Python to enter the field of data science, artificial intelligence, and web development.
Learners interested in enrolling in WatSPEED’s Data Science certificate and Python for Machine Learning.

Learn alongside your team!

WatSPEED provides custom learning experiences tailored for large groups from any single organization. Register three or more employees from the same organization and receive 15 per cent off. Contact our team at watspeed@uwaterloo.ca for details.

Exclusive access to your program author—a University of Waterloo faculty expert in computer science.
Learn at your own pace with weekly independent online learning and hands-on exercises.
Attend a live orientation session before your course starts to get up to speed on the curriculum.
Optional live drop-in sessions twice weekly (time to be determined soon) via Zoom where you can ask questions and receive instructor support on key course concepts.
Engage directly with your classmates through online discussion boards.
Complete multiple choice quizzes each week while achieving a 70 per cent grade to complete the course. Receive immediate feedback on quizzes and interactive course components.
The course consists of texts, visuals, videos, and interactive activities.
Up to five hours each week (including drop-in sessions, hands-on exercises, discussion boards, and independent study).

Academic requirements

There are no academic requirements or pre-requisites for this course.

System requirements

This course is housed in the OpenEdX platform and works best in Google Chrome or Mozilla Firefox. Safari and Microsoft Edge are not recommended.
No software is needed to complete this course as all exercises can be completed within the course itself.
Zoom is used for drop-in sessions.

Receive a certificate from the University of Waterloo

Upon successful completion of this program, you will receive a professional education certificate from the University of Waterloo.

Headshot of Carmen Bruni

Carmen Bruni

Lecturer, Cheriton School of Computer Science | Program Author and Instructor

Dr. Carmen Bruni is a faculty member at the University of Waterloo, David R. Cheriton School of Computer Science.

Before starting at Waterloo in 2015, he obtained his PhD. in Mathematics from the University of British Columbia. He completed his undergraduate and master’s degrees at Waterloo in Computer Science and Pure Mathematics.

From 2015 to 2017, he worked with Waterloo’s Centre for Education in Mathematics and Computing. Since then, he has been teaching in the School of Computer Science. Dr. Bruni has received numerous awards for teaching excellence including a prestigious Killam Graduate Teaching Award in 2013.

His current research interests are in mathematics, education, and pedagogy.

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