About CIS4020

Welcome to CIS4020 – Data Science.

This course is an elective fourth-year course for students studying Computer Science or Software Engineering in the School of Computer Science at the University of Guelph. However, it is quite typical that students in this course come from other degrees (such as Engineering, Mathematics & Statistics, or Business), and have had a varied set of experiences that includes on-the-job training, co-op semesters, or possibly internships. For some of you, this will be your first exposure to data science.

Whatever your background training and experience, you can expect this course to provide you with an introductory overview of many different methods and tools that can be used to help you understand the story of data.

Further, you should expect everything that we do in this class to contribute in some way to the course deliverables. Almost every classroom activity will provide you with the opportunity to develop your assignments and final project. Use your time wisely.

How To Use What You Learn

While we will learn about and practice many different methods in CIS4020, it is important to realize that outside of this classroom, you will likely pick and choose from the available methods depending on the data you are working with and the questions you are attempting to answer. You likely won’t use all of these methods on a single project.

CIS4020 has been set up so that it will allow you to explore many different methods, and then select from those to best answer questions posed by our community partner. Think of yourself as a consultant, and your job is to find the best methods to answer the questions of your client. With this in mind, you’ll spend much of your time applying the methods you learn while working on a project for a community partner.

How Is CIS4020 Taught?

CIS4020 is an active experiential learning-based interdisciplinary and community-engaged classroom. But what exactly does this mean?

Active Experiential Learning

CIS4020 is taught in a way that provides you with time to practice and hone your skills in data science. This means that we will have some lecture-based components during class, followed by periods where you and your team will play with data and code to answer questions. The things you discover during these periods of active and experiential learning will be discussed as a class.

To ensure that we get as much as we can out of our classroom activities, and to guarantee that our discussions are as robust and rich as possible, it is your responsibility to review the necessary course materials before you arrive at class. This will also be your opportunity to clarify the concepts that you will have covered in your pre-class readings.

This does not mean that every class is going to be completely active. There will be times when some or all of our class time will be lecture-based. Even in these cases, however, efforts will be made to present examples that are structured around our classroom project.

During most class meetings and labs, however, you can expect CIS4020 to be a very active space – with elements of improvisation, team-based research, reflection, and more.

Finally, the classroom activities have been developed to help you achieve specific discipline-based learning outcomes of the course, but also to help you develop foundational skills. Foundational skills are those skills that are not specific to a single discipline but have been ranked more and more often by industry as skills they want their new employees to have – even above the discipline-specific skills.

To support our learning journey, you might want to participate as a class in developing a set of class notes. Specifically, you can use this link to add notes and comments pertaining to our community partner’s project, or about topics covered in class that you can all access, edit, and share. Click here to access the document.

If you are ever unsure of the purpose behind an activity, make sure to ask.

Interdisciplinary & Community Engaged

CIS4020 is an interdisciplinary classroom.

At the most basic level, our classroom will include students from several different disciplines. While the majority of students will come from Computer Science or Software Engineering, it is possible that we will have students who are studying Mathematics and Statistics, Business, or Computer Engineering in the class.

However, we will also have a community partner in the classroom who will be our client and will provide a semester-long challenge for us to solve. In the past, our community partners have included the Co-operators, the Guelph Community Health Center, and various on-campus research collaborators.

What is common about our community partners?

• In all cases, our community partners are actively involved in the development and delivery of your specific version of CIS4020 for up to 4 months prior to you ever walking through the classroom door.
• In all cases, our community partner is prepared to continue working on the project beyond the confines of the CIS4020 classroom. This means that our community partner is in this for the long haul; and is willing to continue working with students who want to continue development after CIS4020 ends.
• In all cases, the community partner is a domain expert for the types of services they provide. They are an incredible resource for us.
• In all cases, the community partner is giving their time to contribute to your education even though they know that the project you are working on for them likely can’t be completed in a single semester. Often this means they are volunteering time to help you master the learning outcomes of the course – including the time it takes to 1) visit the class several times throughout the semester, 2) review documents you’ve developed, and 3) provide answers to questions that arise throughout the semester.
• In most cases, the community partners have limited computer science, software design, or data science knowledge. More specifically, they don’t speak the same lingo that we speak.

Our community partners are critical to the success of the course, and it is important to recognize how fortunate and privileged we are to have them. It is essential that we treat our community partners with the respect and dignity that they deserve.

We will explore more about community-engaged learning and working with community partners in future chapters.

The Wil Wheaton Law

Since some of you have worked in industry already, it is very likely that you have learned some of the methods that we will present in this course. You may have learned them at a much deeper level than what this course will offer – or perhaps in a slightly different way. You may also have learned about other methods that we won’t present in this course, or have learned about methods that are unique to a particular employer.

All of this is great, as it means that we will have a diverse set of experiences in our classroom on which to draw as we set off over the next semester. However, it also can pose challenges that we should be aware of so that they don’t derail the class or the work we are trying to complete.

Our diverse experiences mean that not everyone in the class has had a chance to learn about some of the methods we will cover. It is important that we provide those students with the opportunity to learn the basics before introducing them to other methods. This doesn’t mean that we can’t share the knowledge we have, but course deliverables must demonstrate that each student has a mastery of the course topics before other methods will be considered.

If you are unsure of the methods you should use, or if you have other ideas on how to implement the course project, you must receive written approval from the instructor before using them.

Additionally, because our community partners have full-time and highly demanding jobs, there will be times when they won’t be able to respond to us as quickly as we’d like. We need to be flexible and open to these sorts of delays. In most situations, we simply need to be patient as we wait for their response, however, we may also – as a class – make certain assumptions to keep things moving, or (in rare situations), the instructor might make an executive decision.

Whatever the case, if you are unhappy that we are using a particular method, if you feel that the community partner isn’t doing enough, or if you have any other concerns – set up a meeting to discuss this with the instructor. At no time should you derail another student’s learning in the classroom, in the lab, or as part of a group meeting because of your potential dissatisfaction with anything related to the course.

This isn’t to say that things can’t and won’t be frustrating, and this isn’t to say that you aren’t allowed to have your own opinions or to feel strongly about something; they can be, they likely will be at some period during the semester, and you are. But you shouldn’t use this as justification for preventing others from learning the required course content.

Of course, most of the challenges we might face in class can easily be avoided by subscribing to the Wil Wheaton Law, and taking the I Am A Gryphon pledge.