Unsyllabus
Contents
Unsyllabus#
Important Details#
Name |
Description |
|---|---|
Course |
DATA 530 |
Term |
2021 Winter Term 1 |
Instructor |
Dr. Firas Moosvi (he/his/him) |
Lectures |
Monday, Wednesday from 9:30 - 11:00 AM: Online Via Zoom |
Labs |
Tuesdays 8:30 am - 9:30 am and 13:30 pm - 15:30 pm: Online Via Zoom |
Student Hours |
To get live 1 on 1 help in the course, use Zoom at various times (see below for schedule). |
Canvas URL |
|
Course Discussion |
To ask any course-related questions, use private (personal, not useful for anyone else) or public (helpful for other) messages on Slack |
What do I need to purchase for this course?#
Being very conscious of the high tuition and technology costs, we have made efforts to remove the additional cost of taking this course. All course content, references, and resources provided in this course are free and open source, and can be considered open educational resources (OER).
Contact Us#
Team Member |
Pronounce as |
Contact |
Student Hour |
|---|---|---|---|
Dr. Firas Moosvi (he/his/him); Instructor |
Contact via Slack |
TBD |
|
Corey Bond |
Contact via Slack |
TBD |
Evaluation#
The grading scheme for this course is:
Item |
Weight |
Frequency |
|---|---|---|
Learning Logs |
10% |
Weekly on Fridays |
Labs |
50% |
Weekly on Tuesdays |
Quiz 1 |
20% |
Once on October 4th |
Quiz 2 |
20% |
Once on October 6th |
Attention
All (non-quiz) deadlines in this course have an automatic 48 hour grace period after the due dates listed above. Any submissions submitted past the grace period will not be graded.
Note
Important: The maximum mark you can get on each item is 100%. Any available bonus marks are not transferrable to other assignments.
Passing requirements#
Yes. To pass this course, you must:
Achieve an average of 60% in the quizzes.
Achieve an average of at least 60% across all labs
If students do not satisfy the appropriate requirements, the student will be assigned the lower of their earned course grade or, a maximum overall grade of 45% in the course.
Please refer to the UBCO Calendar for additional details for program-wide passing requirements.
In particular:
60% is the minimum passing grade for master’s students; however, only 6 course credits with grades from 60-67% may be counted toward a master’s program. For all other courses, students must obtain a minimum of 68%.
Schedule#
Schedule#
Class # |
Date |
Course Topics |
|---|---|---|
1 |
Wednesday September 8 |
Course and Platform Introduction |
2 |
Monday September 13 |
Data Formats |
3 |
Wednesday September 15 |
Introduction to Excel |
4 |
Monday September 20 |
Excel Data Analysis |
5 |
Wednesday September 22 |
Excel Macros and Automation |
6 |
Monday September 27 |
Online Services |
7 |
Wednesday September 29 |
Debugging |
8 |
Monday October 4 |
Quiz 1 - Timed, online |
9 |
Wednesday October 6 |
Quiz 2 - Take-home |
Course Learning Outcomes#
Course and Platform Introduction
understand MDS structure and goals
list the different software used and their purpose
define command line and list some of its uses
know how to open the command line window on Mac OS and Windows
define: file system, folder, file
explain the difference between an absolute and relative path
define Git/GitHub and explain why they are useful for analysts
access the web interface of GitHub
using command line clone repository, add files, commit changes, and push to origin
view and edit text files directly on GitHub
Data Formats
define: computer, software, memory, data, memory size/data size, cloud
explain “Big Data” and describe data growth
compare and contrast: digital versus analog
briefly explain how integers, doubles, and strings are encoded
explain why ASCII table is required for character encoding
explain why Unicode is used in certain situations instead of ASCII
explain the role of metadata for interpreting data
define: file, file encoding, text file, binary file
discuss the time-versus-space tradeoff
Introduction to Excel
explain what a spreadsheet is
explain how cells are addressed in a spreadsheet
list some of the ways to select cells in a spreadsheet
define and explain: formula, function, argument, concatenation
use these functions: concatenate, lookup, index
explain the difference between an absolute and relative address
explain how an aggregate function works and list examples
Evaluate and create conditions. Use IF() to make decisions.
Explain how to use conditional formatting.
Excel Data Analysis
explain how spreadsheets can be used as a database
use sorting and filtering
create and edit charts and use chart features: trendlines, sparklines
explain the usefulness of: what-if scenarios, goal seek, solver
use and create pivot tables and charts
use the Analysis ToolPak including computing a regression
Excel Macros and Automation
list some reasons to use Excel VBA
define macro and explain the benefit of using macros
be able to record and execute a macro
explain the security issues with macros and how Excel deals with them
list and explain the use of the four main windows of the Visual Basic Editor
explain the role of the object browser
use the Range object to select a group of cells
create user-defined functions and use them in formulas
understand that Excel structures everything as objects with methods and properties
Online Services
explain motivation for a data analyst to use cloud services for their work.
list some of the cloud service companies and the services they provide.
use Slack for group communication.
use Google Apps for collaborative document editing
list some trade-offs of using cloud services versus building using in-house tools such as R and Python
explain the role of Google Analytics and Google AdWords. Compare and contrast what these two services provide.
Debugging, Libraries, and Documentation
define: debugging
list and explain the 4 key steps of debugging.
list and identify three types of program errors: syntax errors, logic errors, and exceptions.
be able to debug Python and R code.
understand different resources and techniques for getting help in R and Python.
read and apply standard documentation for R and Python.
understand the importance of using libraries to improve code development efficiency and reliability.
practice finding a library, reading its documentation, and applying its methods to solve a problem.
The best way to get personalized help in this course is to attend the labs and student hours we have scheduled for this course. They are all done on Zoom and this is time the TAs have set aside to help you! You may also use this time to talk to us about anything else related to data science as well. We would love to hear about you, what your interests are, and if you need any career advice.
A few other notes:
We will be using Slack for Announcements in this course.
For all course-related questions you can reach out to the teaching team including instructors and TAs via Slack.
You are encouraged to post questions publicly whenever possible so others can benefit. For private and personal issues, you can send private messages on Slack.
Any student may visit the student hour for any member of the teaching team (TA or instructor)! In other words, you can go to the student hour of ANY TA, not just the one whose lab/tutorial you are registered in.
Unsyllabus changes#
In this section, I will outline any changes that have been made to the unsyllabus as we go through the course. We will do our best to follow the plan outlined in this unsyllabus, but in case things go south, I will need to make adjustments to the contents and the schedule.
Any major changes to the syllabus (this page) will be documented here, as well as the date the change was made.
Change Date |
Summary |
Rationale |
|---|---|---|
N/A |
N/A |
N/A |
Link your Canvas account to Gradescope#
You should then be guided through a series of steps to create an account, set a password, and link it to our course.
On the left sidebar in Canvas, click on Gradescope.
This is very important for you to do as it’ll be our primary mechanism for delivering you feedback in this course.
Teaching Philosophy#
For a detailed description of my teaching philosophy and values (including a list of references and citations), you can read it here. Here are the key principles I intend to apply in this class:
Student learning is vastly improved through active learning
Learning technologies must be leveraged to scale instructor effort across multiple classes.
Inter-disciplinarity is the future of education.
Effective teaching is inclusive teaching.
How will this course be taught ?#
This course will be taught as a Blended Learning classroom where some elements of a flipped classroom will be mixed with a more traditional coding classroom with live demos, clicker questions, and worksheets. Briefly, this requires students to watch videos and engage with the assigned reading prior to the classroom meeting (knowledge transfer). During the class meeting, the instructor guides students through clicker questions, worksheet problems, and other activities to help the students make sense of the material (sense-making). See Fig. 1 for a mental model of how learning works :cite:`Ambrose2010`.
Fig. 1 To develop mastery in a concept, students must first acquire the necessary skills, then practice integrating them, and finally know when to apply what they have learned. This figure was adapted from Figure 4.1 of the book “How Learning Works”. The terms “knowledge transfer” and “sense-making” applied in this context is generally attributed to Dr. Eric Mazur.#
What does this mean in practical terms?#
Fig. 2 shows a handy table to help guide you and organize your learning in this course:
Fig. 2 This table describes how I think each course activity should be classified between knowledge transfer and sense-making.#
Academic Integrity#
How do I go through this course with integrity?#
I want to be proud of your work in this course, and I want YOU to be proud of yourself as well! That cannot happen if you make unethical decisions, including (but not limited) to cheating or plagiarism. According to the scientific literature, the most common reasons students cheat are:
Fear of failure and life consequences
Peer pressure, including an inability to say no to help others cheat
Perceived societal acceptance of cheating (Lance Armstrong, Barry Bonds, Enron, Wall Street & the The Big Short)
Desire for success without the time/desire to put in the work needed
Strict deadlines and due-dates
Requirement from instructors to memorize facts, figures, equations, etc…
High-stakes exams with no recompense for “having a bad day”
Peers cheating with no consequences or penalties
Unclear expectations on what constitutes academic dishonesty
Inadequate support from instructor and teaching team
Though I sympathize with students and the stresses of your busy lives - in my opinion, there is no good reason to cheat. I have tried extremely hard to make this course focused on learning rather than grading, and where grading is needed, to have policies that are as student-friendly as possible. In particular, I hope (and expect) that the following features of the course should eliminate your temptation to cheat or plagiarize:
48 hour grace-period on all due dates and deadlines.
Long testing window so you can start the tests whenever you’re comfortable.
Weekly learning logs, homework and reading reflections to make you think about your learning (metacognition).
Each test has a “bonus test” available one week later; for each test, we will take the better score of the pair.
No high-stakes exams (the single largest assessment item is the final exam).
All course assessments are completely open book, open notes, and open web (except for cheating websites like Chegg, CourseHero, Slader, Bartleby, etc…)
Plenty of TA and instructor student hours and several outside of normal business hours.
Class website that outlines exactly what you should do when to help you manage your time.
Tonnes of supplemental materials including other instructional videos in case you want a different perspective.
Weekly prompt to accept the integrity pledge to keep you accountable.
A true willingness from the instructor (me) to help you learn and succeed in this course!
With these features, and several other little things, I sincerely hope that you will consider completing this course with maximum integrity so that you never have to feel guilty, ashamed, or disappointed in yourself and your actions!
A more detailed description of academic integrity, including the University’s policies and procedures, may be found in the Academic Calendar.
What is considered academic dishonesty in this course?#
To make it even easier for you to decide what isn’t allowed, below is a list of things that I definitely consider to be academic dishonesty:
Asking others for their work in the course (whether question by question, or all at once)
Sending others your work in the course
Doing tests collaboratively (tests must be done by yourself and alone)
Sending others your test questions and/or answers
Sharing any course material onto Chegg, Course Hero, Slader, or other similar sites
Searching for solutions to course material on Chegg, Course Hero, Slader, or other similar sites
Blindly googling the question in hopes of finding someone who had a similar question and then copying their answer
Note, googling to find resources to understand specific concepts or general ideas is highly encouraged!
Having a tutor/friend/nemesis complete and submit your work for you
Copying and pasting code, equations, text explanations, prose, etc… without attribution
Manipulating the learning platforms we use to reverse engineer the randomization algorithms, hacking the timer functionality, or other similar technical malfeasance.
Course Accommodations#
What if I miss labs, tests, or the exam due to an illness, health, or other personal situations?#
Normally, most deadlines in this course have a generous grace period. If you require an extension beyond the grace period, please contact the instructor on Slack (ideally before the deadline passes) to discuss your options.
Students who, because of unforeseen events, are absent during the term and are unable to complete tests or other graded work, should normally discuss with their instructors how they can make up for missed work. If ill health is an issue, students are encouraged to seek attention from a health professional. Campus Health and Counselling will normally provide documentation only to students who have been seen previously at these offices for treatment or counselling specific to conditions associated with their academic difficulties.
Tip
If you miss a course component due to an illness, health, or other personal situation, please reach out to me as soon as you are comfortable, and I’ll work with you to get you back on track.
What if I have dependents that rely on me for care and unpredictable emergencies may arise?#
Let’s talk, send me a private message and we can discuss it. I do not necessarily need to know all the personal details, just a high-level summary of your situation and what you think an ideal solution would be.
I’m sure we will come to some agreement, generally the earlier you let me know of any special circumstances or accommodation, the more I’ll be able to do for you!
What if I have to miss a deadline because of a wedding, birthday, funeral, religious holiday, or personal event ?#
No problem! There’s not even any need to tell me, or ask for permission to miss deadlines. The course is designed to give you maximum flexibility:
Every deadline has a 48 hour grace period that is automatically applied.
There is no late penalty if you use the grace period
You can use the grace period an unlimited amount of time in the course (though if it happens every week and for every assignment, I might check in with you and gently encourage you not to leave things to the last minute)
If you miss a deadline by more than the grace period, the general course policy is that you will not be able to get full credit for it, and in many cases, may even get a 0 for it. In the cases of Tests, it is not possible to get partial credit, or complete it at times other than within the scheduled windows. In some cases, I reserve the right to grant an extension or make alternate accommodations as needed.
What should I do if I need accommodations to be successful in this course?#
Accommodations are intended to remove barriers experienced by individuals with disabilities. As a matter of principle, UBC is committed to promoting human rights, equity and diversity, and it also has a legal duty under the BC Human Rights Code to make its goods and services available in a manner that does not discriminate. Policy 73 (Accommodation for Students with Disabilities) sets out principles and processes governing the accommodation of students with disabilities.
All accommodations for this course are handled through the Disability Resource Centre and I encourage you to contact them to book an appointment.
Compassion#
As I’m sure you’re aware, there is (still) a global pandemic happening right now and we could all use some extra compassion and humanity. If you’re going through something that is affecting you (course or otherwise), you are always welcome to come and talk to me about it. If I am not able to help you myself, then I can probably direct you to the right person or resource. If you need extra help, or extra time to deal with something you’re going through, just ask. You will never owe me an explanation about your physical health, mental health, or those of your family members, friends, etc… I will believe you, and I will trust you. I will not judge you, nor think any less of you. I will do everything in my power to work out something that is both reasonable and fair. This, I promise!
Acknowledgements#
The syllabus was constructed and adapted from many other templates and examples. Below is the list of resources I have used to put this syllabus together:
Physics 117 (Instructor: Dr. Simon Bates)
Psychology 417A-951 (Instructor: Dr. Catherine Rawn)