Syllabus: CSCI 127
Spring 2024 Schedule
Note: dates and assignments more than a week out may be adjusted as the semester goes on. Please consider this page to be a living document subject to changes througout the semester.
Week |
Date |
Subject |
Assignments -- see Brightspace (D2L) |
1 |
W Jan 17 R Jan 18 F Jan 19 |
Set up for Python:
|
|
2 |
M Jan 22 W Jan 24 R Jan 25 F Jan 26 |
Lab 1 |
|
3 |
M Jan 29 W Jan 31 R Feb 1 F Feb 2 |
Program 1
Lab 2
|
|
4 |
M Feb 5 W Feb 7 R Feb 8 F Feb 9 |
Lab 3
|
|
5 |
M Feb 12 W Feb 14 R Feb 15 F Feb 16 |
Exam 1 (in class) Program 2 Lab 4
|
|
6 |
M Feb 19 W Feb 21 R Feb 22 F Feb 23 |
Lab 5 |
|
7 |
M Feb 26 W Feb 28 R Feb 29 F Mar 1 |
Program 3
Lab 6 |
|
8 |
M Mar 4 W Mar 6 R Mar 7 F Mar 8 |
Lab 7
|
|
9 |
Mar 11 - 15 |
SPRING BREAK - no classes |
|
10 |
M Mar 18 W Mar 20 R Mar 21 F Mar 22 |
Program 4
Lab 8 |
|
11 |
M Mar 25 W Mar 27 R Mar 28 F Mar 29 |
Lab 9 |
|
12 |
M Apr 1 W Apr 3 R Apr 4 F Apr 5 |
Exam 2 (in class)
Lab 10
|
|
13 |
M Apr 8 W Apr 10 R Apr 11 F Apr 12 |
Program 5
Lab 11 |
|
14 |
M Apr 15 W Apr 17 R Apr 18 F Apr 19 |
Lab 12
|
|
15 |
M Apr 22 W Apr 24 R Apr 25 F Apr 26 |
Lab 13 |
|
16 |
M Apr 29 W May 1 R May 2 F May 3 |
Lab 14 |
|
17 |
W May 8 |
FINAL EXAM8:00 am - 9:50 am |
Exam 3 (in class) |
Course Description
CSCI 127. Joy and Beauty of Data. 4 Credits. (3 Lec, 1 Lab) F,S
COREQUISITE: M 151Q Provides a gentle introduction to the exciting world of big data and data science. Students expand their ability to solve problems with Python by learning to deploy lists, files, dictionaries and object-oriented programming. Data science libraries are introduced that enable data to be manipulated and displayed.
To succeed in this course, it is recommended you have a good math background, some basic computer programming experience; if you are unsure about your readiness, our recommendation is to begin with CSCI 107, which provides a gentle introduction to Python and basic programming concepts.
Class Resources
- Brightspace (D2L Learning Environment)
- A laptop computer is highly recommended. There will be time to work on it in class. Alternatively, the library has laptops they can lend out to students, and the lab rooms have computers you can use.
- The online textbook is free.
- Latest Python and IDLE editor - download site.
Instructor
- Mr. Daniel DeFrance
- Office hours
- Office: Barnard Hall 358
- E-Mail: daniel.defrance@montana.edu
Lectures take place on Mondays, Wednesdays, and Fridays from 9:00 - 9:50 am in Norm Asbhornson Hall (NAH) Room 165 -- the big round classroom. It's recommended you bring your laptop to follow along with in-class coding examples.
Labs
Labs meet in Roberts Hall Room 111 on Thursdays. There is no lab scheduled for the first week of classes. The time of your meeting will depend on the section in which you are enrolled. To find out about more, you can use the Schedule of Classes to filter for CSCI 127, which provides a list of all the sections, and at what the times they meet. It should take you an hour or two if you are well prepared (labs generally open at 8 pm the evening before the lab day so you can get a sneak preview), but you will have until midnight on the day of the lab to submit your work to D2L for grading.
A Teaching Assistant (TA) will be in the room to answer questions, provide guidence, and grade the assigments. Each section will have a different TA, so get to know yours early, and take note of their office hours to visit them outside of lab time.
Teaching Assistants (TAs)
Teaching Assistants are advanced computer science students who are hired to work for course, and they are responsible for grading, helping with assignments, and proctoring lab sessions. You will meet your TA for the first time during Lab 1 in Roberts Hall. You may reach out to your TA with any questions regaurding grading, lab attendance, and help with assignments. Your TA will have office hours scheduled in the Student Success Center (Barnard Hall room 259).
For CSCI 127, you can meet with any TA in the Student Success Center to get help with your homework -- it doesn't neccessarily have to be your lab TA. Even TAs for other classes can help with CSCI 127 during their office hours.
Section | Name | From | To | Day | ||||
1 | Kaden Bach | 8:00 AM | 9:50 AM | Thursday | kadendabach@gmail.com | |||
2 | Jared Matury | 10:00 AM | 11:50 AM | Thursday | jmmaturyta@gmail.com | |||
3 | Nathan Ritchlin | 12:15 PM | 2:05 PM | Thursday | nsrgy22@gmail.com | |||
4 | Alex Stergios | 2:15 PM | 4:05 PM | Thursday | ahstergios@gmail.com | |||
5 | Ryan Johnson | 4:15 PM | 6:05 PM | Thursday | rjohnson924@outlook.com |
More Help
Programming Assignments
Programs are take-home assignments that are meant to take a bit more effort than the labs. Subsequently there are fewer of them you will have more time to finish. Programs are generally assigned every other week, and opening Monday morning, and closing late the following week. It is strongly recommended you make every effort to finish the programs before the deadline, early in the week if possible. As you are no doubt aware, zeros are a lot worse than a plain old bad grade. If you get your program together enough that you think it would be worth some points, go ahead and submit it early with D2L -- you can always improve it and resubmit right up until the deadline.
Your TA will be familiar with the program and will grading it when your are finished, so they're a great resource to ask for help, but during lab times they will be focused on the lab. To get help with the programs, it's better visit the Student Success Center inBarnard Hall Room 259. Your TA will hold office hours there, but really anyone working there at the time you drop in should be able to sit down with you and help you with your program, even if they are a TA for a completely different class.
Exams
There are three exams over the course of the semester, including the final exam during finals week. The exams take place in the NAH class room during regular class hours (except for the final exam, which has its own schedule at the end of the semester.) These exams are all weighted evenly.
Grading
Note: Practicums must be taken at the regularly scheduled time at the designated place and will not be given early or late.
- Weekly Labs - 42% (evenly weighted)
- Programs - 25% (evenly weighted)
- Practicums - 33 % (evenly weighted)
Grades are determined based on your score in the class as follows:
Letter Grade | % Score |
---|---|
F | 0 |
D- | 60 |
D | 63 |
D+ | 67 |
C- | 70 |
C | 73 |
C+ | 77 |
B- | 80 |
B | 83 |
B+ | 87 |
A- | 90 |
A | 93 |
Course Outcomes
By the end of this course, students should be be able to:
- Utilize lists, files, dictionaries and arrays to solve problems in Python.
- Utilize fundamental object oriented principles such as classes, objects, methods and inheritance to solve problems in Python.
- Utilize data science libraries to solve data science problems in Python.
- Understand the broad area of data science and its relevance.
Course Policies
See the policies page for expectations and consequences on subjects like collaborating with others, what constitutes cheating, copyright responsibilities, using tools like ChatGPT, lateness, and what to do in case of emergencies.
CSCI 127 Late Pass - You will be given one late pass (valid for up to one week) that you may use at your discretion for a LAB assignment. This will be tracked by your TA. The the late pass cannot be used for a program -- there is approximatley one week to complete the programs so submit those EARLY and OFTEN (any subsquent submitals will replace the previous one.) There is no point penalty for using the late pass on a lab.
CSCI 127 Attendance - Attendance is highly encouraged, and students who regulaly attend class tend to do much better and obviously have a richer, more engaged college experience than those who do not. Still, I will generally make an effort to record the lectures during class and post a video to D2L under the Content section. There are no gaurantees with the quality and reliability of the video recording.