Welcome
- Introduce yourself
- Introduce co-instructors/TAs
- Depending on class size have students introduce themselves
Course goals
- Data and how to work with it
- Data entry -> Data storage -> Data manipulation -> Data visualization
- Not statistics
Teaching methods
- Flipped classroom
- You don’t learn how ride a bike just by listening to someone talk about it and the same is true for computing
- Reading or videos before class
- I do, we do, you do
- I will demo an idea using live coding
- We will work on an associated exercise together in class
- You will work on additional exercises on your own (both in & out of class)
- Peer instruction
- Interact with each other during the we do and you do parts
- You are at least as likely to learn from your peers as from me
- Introduce yourself to one of your neighbors you don’t know
Course structure
- Weekly assignments
- Practice is really important for learning skills like this
- Work on exercises in class
- Will require additional programming time after class
- Due end of the day on Monday
- 75% of grade
- Projects
- Designed to let you learn about bigger computing efforts
- Ideally related to your research
- Can related to any aspect of the class or involve many of them
Website
Walk through the website showing the following items
- Schedule
- Walk through schedule (quickly)
- Readings
- Read before relevant class
- No need to do any challenges or exercises in readings
- Lectures
- Lectures notes used in class
- Not expected to read in advance; may be useful for review
- May not match lecture precisely
- Assignments
- Answers provided
Syllabus
- Grading
- 100/90/50/0
- Give it a read and let me know if you have any questions
Office Hours
- Monday: 2-3:15 in NZ 203
- Wednesday: 11 in NZ 203
Canvas
- Handle assignment submission and grading through Canvas
- Chat
First day demo
- With the little time we have left I just want to do a quick demo of some of the things you’ll be able to do by the time we’re half way through the class