MSDS501 Computational Data Science Bootcamp

This 5-week computational bootcamp is part of the MS in Data Science program at the University of San Francisco and is specifically designed as an introduction to data science programming for those who are not yet skilled programmers.

Writing software is about problem solving, computer languages, algorithms, data structures, libraries, tools, and computing devices. In this bootcamp, I'm hoping to teach you how to approach programming, review the key elements of Python, teach you some of the core libraries, give you an introduction to the command line, and finally introduce you to cloud computing. You will go over algorithms and data structures in more detail in the data acquisition, machine learning, and data structures courses.

Class details

INSTRUCTOR. Terence Parr. I’m a professor in the computer science and data science program departments and was founding director of the MS in Analytics program at USF (which became the MS data science program). Please call me Terence or Professor (“Terry” is not ok).

SPATIAL COORDINATES:<br>

• Class is held at 101 Howard in 1st floor classroom 155-156. Recorded via zoom for remote, asynchronous students in different time zones.
• Exams will likely be online via Canvas at 3:30pm with another opening at midnight for those in different time zones.
• My office is room 525 @ 101 Howard

TEMPORAL COORDINATES. Wed July 7 to Wed Aug 11.

• Lectures: Mon/Wed 10AM - 11:50AM

INSTRUCTION FORMAT. Class runs for 1:50 hours, 2 days/week. Instructor-student interaction during lecture is encouraged and we'll mix in mini-exercises / labs during class. All programming will be done in the Python 3 programming language, unless otherwise specified.

TARDINESS. Please be on time for class. It is a big distraction if you come in late.

LAPTOP POLICY. My policy is that all student laptops must be closed during class unless we are doing a lab or I specifically ask you to follow along as I type into my computer. All materials for the course are available in this repository, which reduces your need to take notes considerably.

Student evaluation

| Artifact | Grade Weight | Due date | |--------|--------|--------| |Image processing| 16%| Wed, July 21 | | Word similarity and relationships | 12%| Wed, July 28 | | Exploration of Enron email data set| 16%| Sat, August 14 @ 11:59PM CA time| |Test 1| 12%| 3:30-4:15pm Wed, July 14 | |Test 2| 12%| 3:30-4:30pm Mon, July 26 | |Test 3| 12%| 3:30-4:30pm Mon, August 2 | |Final exam| 20%| 10:00-11:30am Wed, August 11 (last day of class) |

Tests 1-3 and the final exam are online, there are timeslots for international students and domestic; each student will have one attempt at each exam. Exams are proctored by Honorlock (see below). The exams are available electronically for a fairly long period so that local and different time zones can participate at a reasonable hour. You are strictly forbidden from discussing exam contents with your fellow students until after the final exam deadline. (Remember that helping other students in this way is a violation of the honor code and potentially reduces your own score.)

All projects will be graded with the specific input or tests given in the project description, so you understand precisely what is expected of your program. Consequently, projects will be graded in binary fashion: They either work or they do not. The only exception is when your program does not run on my machine because of some cross-platform issue. This is typically because a student has hardcoded some file name or directory into their program. In that case, I will take off at least 10%, instead of giving you a 0. Please go to github and verify that the website has the proper files and that those files look correct for your solution before the deadline. That is what I will download for testing.

Each project has a hard deadline and only those projects working correctly before the deadline get credit (100%). Late projects are given 0%. My grading script pulls from github at the deadline. All projects are due at the start of class on the date indicated, unless otherwise specified.

No partial credit. Students are sometimes frustrated about not getting partial credit for solutions they labored on that do not actually work. Unfortunately, "almost working" just never counts in a job situation because nonfunctional solutions have no value. We are not writing essays in English that have some value even if they are not superb. When it comes to software, there is no fair way to assign such partial credit, other than a generic 30% or whatever for effort. The only way to determine what is wrong with your project is for me to fix and/or complete the project. That is just not possible for 90 students. Even if that were possible, there is no way to fairly assign partial credit between students. A few incorrect but critical characters can mean the difference between perfection and absolute failure. If it takes a student 20 hours to find that problem, is that worth more or less partial credit than another project that is half-complete but could be finished in five hours? To compensate, I try to test multiple pieces of the functionality in an effort to approximate partial credit.

Each project has a hard deadline and only those projects working correctly before the deadline get credit. My grading script pulls from github at the deadline.

I reserve the right to change projects until the day they are assigned.

Grading standards

I consider an A grade to be above and beyond what most students have achieved. A B grade is an average grade for a student or what you could call "competence" in a business setting. A C grade means that you either did not or could not put forth the effort to achieve competence. Below C implies you did very little work or had great difficulty with the class compared to other students.

Honorlock

All tests use HonorLock via Canvas and have strict time limits. You will be unable to do anything other than take the test; no access to the Internet etc. A proctor will monitor you during exams to ensure you do not communicate with anyone else during the test. Generally speaking, HonorLock will record all your web, computer, and personal activities (e.g., looking at your phone) during the quiz. It will flag suspicious behavior for my review and will save the recordings for 6 months if I need to go back and check it.

Please see the How to use" page for students. Either I or another instructor will launch a practice quiz on Canvas during the first week of class to ensure everything is set up properly.

• Google Chrome and a webcam are required. At the beginning of the quiz, you will be able to add the Chrome extension for Honorlock, then follow the instructions to share your screen and record your quiz.
• You might be asked to change settings on your computer while doing this. You can change the setting and come back to the quiz. This change should only be expected once.
• If you are showing us the side view of your face we don’t know if you’ve got an earbud in your other ear. This is not allowed.
• Make sure you are facing into the camera as Honorlock will shut down the system and force you to restart.
• Make sure that you are not looking down and to the right as if you are looking at notes or using your phone. Honorlock will flag this as cheating.
• You must not start and stop your browser; Honorlock will flag this is cheating.
• You must not use other applications or visit non-Canvas-quiz URLs during the exam unless the exam indicates this is permitted.
• Do not have your phone visible as the proctor will stop the quiz

Side notes:

• Start the quiz with a single Chrome window and single tab in that window.
• When the "share screen button" is grey, you can still click it and it will work.
• HonorLock flags activities other than the allowed ones: for example when you are accessing a website other than canvas or looking at your phone. I will evaluate these cases and make a judgment myself. I will reach out to you when necessary. If you have followed the guidelines, you don’t need to worry.
• If you have an honorlock software issue during the test, you must take a screen picture with your phone or ipad and notify me immediately via private slack to timestamp the situation with the picture and reason why you cannot proceed. Please contact tech support on the screen to resolve (they are very quick). I will check the Honorlock recording and timestamp of your pictures to grade.
• Privacy statement from HonorLock just in case you are worried about privacy. Since access to Honorlock is very limited, and you are expected to only work on the quiz during the proctoring time, the data that Honorlock records is very limited too. The data storage and sharing agreement don’t have a higher risk than your regular school actives (Zoom, email, Canvas, ...).

Syllabus

Timeline

• A bit of motivation (Audio processing) (Day 1)
• Overview of a Python programmer's world (Day 1)
• The terminal command-line and python environments (Day 1)
  • LAB: A first taste of Python tools (Day 2)
  • LAB: Playing sounds (Optional)
• git and github version control (Day 2)
  • LAB: Git and github (Day 2)
• [Intro to Python