DATA 301 Introduction to Data Analytics
Spring (Winter Term 2) 2017 - 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. This was the third course offering. 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
Student Performance
Of the 79 registered students who started the course, 71 got a D or above. The average GPA was 3.40. Charts showing the mark breakdown are below.
Comments
This class was very well received (instructor rating: 4.91). 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.
Strengths of the Course
- "Try it questions in class, when we actually tried to do the things we were learning, it allowed us to practice the basic skills before lab."
- "Ramon was an incredible professor who communicated the course material effectively to everyone, regardless of whether they had previous experience with computer programming. He gave us time to try example problems in class and went around encouraging and helping everyone. He is always friendly and so helpful in class and in his office. Ramon is without doubt one of the best professors I have ever had at any of the institutions I have ever attended."
- "Ramon makes basic computer science non-intimidating and almost even fun. He can take dry, dull (no offense) programming instructions and explain them in a way that is simple and relative to real life (for us non-CS people). Ramon is really the strength of this course,. I can't imagine the course being half as enjoyable with another prof. I was really scared this course was going to be a mistake, but I have learned so much, I'll go far as to use the word empowering. Thanks Ramon!"
Weakness of the Course
- "This course seems to be missing the "why" for many of the concepts and instead focuses almost entirely on the "how". This isn't a negative per se, but I feel a little focus on what information we are actually looking for in the data, and why, would improve this course substantially. I guess it is assumed that this is covered in other classes."
- "I think there was too much to learn, we dipped our toes in a little bit of everything but I personally prefer to focus on a few core subjects than trying to cover a range of subjects."
Most Enjoyable Part of the Course
- "The professor. We covered a lot of great content in a short amount of time, but the thing that made the course what it was is who taught it. It's a good chance for non CS students to have the Ramon teaching experience. The speed of exam marking for one thing is absolutely incredible. Less than 24 hours to mark 80 midterms must be some sort of record. I look forward to taking any other courses he teaches in the future."
- "Ramon made difficult course material understandable to all of his students (especially the non-computer science majors, like myself). He makes it possible for anyone to succeed in this course so long as they put the work in. Ramon's effective teaching skills made me happy to attend every lecture."
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