DATA 301 Introduction to Data Analytics

Spring (Winter Term 2) 2018 - University of British Columbia Okanagan

Overview

DATA 301 provides an introduction to data analytics to train students with practical industrial techniques for data manipulation, analysis, reporting, and visualization. Industrial skills covered include Excel, Excel VBA, databases and SQL, Linux command line, programming/scripting with Python, data analysis with R, GIS, and data visualization including using Tableau.

On-line Resources

• Syllabus

Student Performance

Of the 166 registered students who started the course, 155 got a D or above. The average GPA was 3.48. Charts showing the mark breakdown are below.

Comments

The course content is good but this offering grew to 166 students (including 15 graduate students) from previous 90. With the increased class size, engagement during lectures is harder such as trying to provide feedback (and candy) for answers. There was also increased plagiarism due to the labs being used previously. Future offerings will reduce the marks for the lab (especially bonus marks) which skewed the marks higher than expected. The course content is still very well liked (instructor rating: 4.87). The labs are very practical hands-on, and many students found Excel valuable. Class time is spent doing clicker questions and practice questions on the computer as much as possible. Students in many disciplines (business, arts, science) were able to learn the content even with highly variable backgrounds in computers. There is about 50% of the population in Computer Science. Handling the diverse backgrounds is important.

Strengths of the Course

• "This course was exceptional! I feel as though I have learned applicable skills that I will continue to develop and use in whatever career path I chose. Class participation and attendance was encouraged and classes were enjoyable so I wanted to attend either way. Dr Ramon is an exceptional lecturer and he makes his expectations clear so long as you go to class. Thank you for the excellent semester!"
  


• "The unparalleled engagement with peers and the instructor during class. Dr. Lawrence absolutely fostered an environment where you could not help learning."
  


• "One of the best teachers I've ever had the pleasure of taking a class with. Highly important material for any STEM major, Ramon exemplifies the importance without dulling the content. Every STEM major should be required to take this course, as it is highly applicable in the real world and employers are looking for computer literacy. Guy really knows his stuff but has a fun attitude about it, give him a raise!"
  


• "Even with a massive class room, Ramon manages to teach in such an elegant manner. Making the course content much more comprehensible."
  

Weakness of the Course

• "Sometimes I felt the lab questions required knowledge exceeding what was learned in class. I could ask the TA but made it at times things difficult and overwhelming."
  


• "This course was said to be for students with NO computer science background, but I think it was too difficult for that category. I eventually preferred not going to class because his clicker questions were SO hard, if I went I would feel bad about getting them wrong. You would have to STUDY before going to class in order to understand the questions which I found a little unfair. This course already has a lab which takes a LOT of extra time, I feel like it's just too much to expect students to do the labs AND continuously study and teach themselves the class material before even going to class. I think it could have been made more accessible for people who don't know anything about programming."
  

Most Enjoyable Part of the Course

• "The lectures involved a good mix of in-class activities, lecture content, clickers, and discussion. This is literally the ONLY class I never had an issue staying awake through!"
  


• "I most enjoyed the breadth of the material. It really gave me some great ideas on how to approach my own data problems. I also very much liked the graduate project, focusing on the analysis made for an interesting way to present my work."