Description
This course introduces concepts for obtaining, analyzing, visualizing, and processing data from various sources. Covers image processing and feature identification, streaming data sources, text scraping, and basic elements of data analysis and machine learning.
CoCalc for collaborative activities during lecture
We will be using CoCalc to complete the jupyter notebook activities during lecture.
Students in the class will be assigned to groups from A-G. Each group will have an shared project inside CoCalc (named CS199py_A for example for the students assigned to group A).
Every week we will add a new jupyter notebook to your shared folder. Students must only work on the shared folder during lecture time! In case you want to work on any of the activities outside of lecture time, you have to download the jupyter notebook and run it locally from your machine.
All instructors are added to the group shared folders. We will be looking at your work during lecture time, and also after the lecture is finished. Keep in mind that CoCalc keeps a log of all the work done, so we will know if any line of code was added outside of lecture time.
Grade:
The course grade will be based on attendance, participation, completion of tasks during each class and a final project. Here is how you can earn points towards your grade:
For each lecture: 70 points for attendance + 20 points for participation. A maximum of 630 points will count towards the final score (to account for one possible missed lecture). You are expected to be on time for class. If you are 15 minutes late (or more), you will not get the attendance for that class. You are also expected to participate in the activity. Students that are not working on the given activities will not get the participation points. subtotal = 630
During lecture, the groups will complete the jupyter notebooks from the CoCalc assignments. Students will take turns as “recorders” of the group. We will talk more about group “roles” in the first day of classes. Every student needs to be a recorder at least once during the course, to get 70 points for that role. subtotal = 70
Each activity is worth 20 points (we have a total of 7 activities – one per week – the last week is reserved for the final project). The activity points will be based on “best effort” to complete, instead of focusing on accuracy. subtotal = 140. We will make a small chance on this item, to be announced on week 2
The remaining 160 points will be assigned to the final project. The submitted project is worth 100 points, and the other 60 points will be given for the presentation on the last day of classes. Students can work individually or in teams of 2 or 3. They will choose a topic, and create a jupyter notebook similar to the one we use during lecture, addressing a “real-world” application. The presentation will be very short, about 2-3 minutes per student/team, consisting of only one slide, with the “big-picture” idea of the project. Think of this as practice for your elevator pitch :0) How can you share your cool project with others in a very short time? subtotal = 160
The grade scale is given below:
| Grade | Point Range |
|---|---|
| A | [900,1000] |
| B+ | [800, 900) |
| B | [700, 800) |
| C | [600, 700) |
| D | [500, 600) |
| F | < 500 |
Students that obtain more than 970 points and attend every lecture will receive an A+.
Preparing for the first class:
Before you come to the first lecture, make sure you take a look at the Python tutorials available here (https://notebooks.azure.com/nnytko2/projects/cs199py-lesson0). If you are familiar with Python, you probably don’t need to do anything. These are not required tutorials, but it may be a helpful resource to some of you.
Piazza:
We will be using Piazza online message board for communication (piazza.com/illinois/fall2019/cs199py1/home). The course staff will post important announcements there and it is your responsibility to check often for these announcements. If you have a question or a concern, please post it on Piazza. Please do not email the course staff. This is both to assist other students who may have similar questions and to ensure you receive the fastest response possible by making it visible to the entire course staff.
Office hours:
We will not have pre-defined office hours. If you feel you need to talk to one of the instructors, reach out to us here and we will try to schedule an appointment.