CS 69099 Capstone
Project - Data Science
Spring
2023
Instructor: Xiang Lian
Office Location: Mathematics and Computer Science Building, Room 264
Office Phone
Number: (330) 672-9063
Web: http://www.cs.kent.edu/~xlian/index.html
Email: xlian@kent.edu
Course: Capstone Project - Data Science
CRNs:
19977
CS 69099 Prerequisites: Graduate standing; and special approval..
Time: 9:55 am - 11:50 am, F
Classroom Location: Henderson Hall, Room 108
Course Webpage: http://www.cs.kent.edu/~xlian/2023Spring_CS69099.html
Instructor's Office
Hours: By
Email Appointment Only (preferably 10:00am - 12:00pm, MW; xlian@kent.edu).
Graduate Assistant: TBD
Office: TBD
Phone: N/A
The official
registration deadline for this course is 01/23/2023. University policy requires all
students to be officially registered in each class they are attending. Students
who are not officially registered for a course by published deadlines should
not be attending classes and will not receive credit or a grade for the course.
Each student must confirm enrollment by checking his/her class schedule (using
Student Tools in FlashLine) prior to the deadline indicated. Registration errors must
be corrected prior to the deadline.
https://www.kent.edu/academic-calendar
For registration deadlines, enter the requested information
for a Detailed Class Search from the Schedule of Classes Search found at:
https://keys.kent.edu:44220/ePROD/bwlkffcs.P_AdvUnsecureCrseSearch?term_in=201680
After locating your course/section, click on the
Registration Deadlines link on the far right side of
the listing.
Last day to
withdraw: 04/03/2023
Online Resources
Library: https://www.library.kent.edu/
Google: http://google.com/
Datasets and Source Code:
v
Spatial
data sets and index source code: http://chorochronos.datastories.org/
v
Road
network and stream data: https://www.cs.utah.edu/~lifeifei/datasets.html
v
NYC OpenData: https://opendata.cityofnewyork.us/data/
v
New
York Taxi Data Description [pdf]
v
Spatial
data: http://chorochronos.datastories.org/
v
U.S. Government's open data: https://www.data.gov/
v
DBpedia
data: http://www.dbpedia.org
v
Freebase
data: https://developers.google.com/freebase/
v YAGO1, YAGO2s, YAGO3 RDF data: https://www.mpi-inf.mpg.de/departments/databases-and-information-systems/research/yago-naga/yago/archive/ (YAGO2 paper: https://people.mpi-inf.mpg.de/~kberberi/publications/2010-mpii-tra.pdf)
Apache Hadoop: http://hadoop.apache.org/
Amazon AWS: https://aws.amazon.com/
Video Tutorials: https://www.linkedin.com/learning/
(Sign in with the organization
portal)
Catalog Description
The course is an integrative experience
that brings together all components of the Masters nonthesis graduate program
in an applied, hands-on real-world setting.
The students work together to complete a
computer project under the supervision of the instructor. The course is a
writing intensive class in which the student writes regular reports describing
his/her progress toward completing the project.
Course Learning Objectives
Demonstrate the ability to work in teams
to analyze a problem, produce a development plan, and implement a computer
solution for the problem. Communicate effectively about the progress and
difficulties of the project.
Course Requirements
Students
will work in groups of 3-5 team members. Each group will work on a semester
project (related to Data Science), design, implement and demonstrate the
project software.
Each
group (i.e., project team) will submit an initial report describing the
project's goals, use cases and a time line for its
implementation. This will be the initial 2 deliverables for the semester
project. Over the course of the rest of the semester that report will be
updated with completed software and documentation.
After
the initial design phase, every week, each team will present a progress report
(i.e., additional deliverables) to the class discussing what they have
accomplished and discussing any revisions in project timelines and goals.
The
class time is for planning, trouble shooting, and problem solving, not for
project coding. Students are expected to do most of their development work
outside of classes. When project development has started, evidence of weekly
code development is required.
Groups:
Group
#1: Visualizing and Querying New York Taxi Data
Group
#2: Guide of the Course Selection
Group
#3: Parsing and Visualizing the Bibliography
Group
#4: Crawling and Querying Social Networks
Tentative Schedule
|
Week |
Topics
|
Notes1 |
|
Week 1 (Jan. 20) |
|
|
|
Week 2 (Jan. 27) |
Getting Started: a. Problem Definition: Importance of Requirements b. Definition of Functional/Non-functional Requirements c. Software Development Life Cycle Overview d. Use Cases |
A list of potential projects [pdf] |
|
Week 3 (Feb. 3) |
Feb 3:
deadline to form a group of 3-5 members
(Please send Name, ID, and email of each group member to xlian@kent.edu) |
|
|
Week 4 (Feb. 10) |
|
Progress Report, Iteration (1) (Due on Feb. 10) |
|
Week 5 (Feb. 17) |
Submit the Group's Project Description Q/A |
Progress Report, Iteration (2) (Due on Feb. 17) |
|
Week 6 (Feb. 24) |
v Submit Functional Requirements project timeline via Canvas v Start Systems Architecture and Software Design |
Progress Report, Iteration (3) (Due on Feb. 24) |
|
Week 7 (Mar. 3) |
v Submit Systems Architecture & Software Design via Canvas v Continue working on implementing your software project |
Progress Report, Iteration (4) (Due on Mar.
3) |
|
Week 8 (Mar. 10) |
|
Progress Report, Iteration (5) (Due on Mar.
10) |
|
Week 9 (Mar. 17) |
|
Progress Report, Iteration (6) (Due on Mar.
17) |
|
Week 10 (Mar. 24) |
|
Progress Report, Iteration
(7) (Due on Mar. 24) |
|
Week 11 (Mar. 31) |
-- |
Spring break: Mar 27-Apr 2, 2023; No Classes |
|
Week 12 (Apr. 7) |
1. Submit the first draft of project description, including user guide
documentation via Canvas 2. Submit initial version of the software project via Canvas (Please submit the two items above associated with
the progress report for Iteration (8)) |
Last Day to Withdraw: 04/03/2023 Progress Report, Iteration (8)
(Due on Apr. 7) |
|
Week 13 (Apr. 14) |
|
Progress Report, Iteration (9)
(Due on Apr. 14) |
|
Week 14 (Apr. 21) |
Group Presentations (20-min presentation&demo
+ 5-min Q/A) v PPT slides (15-20 slides) of the project v Demo software project |
|
|
Week 15 (Apr. 28) |
|
Course Evaluation Final Project Report (hard deadline: Due on May 3; Submit Project
Report, source code, software, readme files, project presentation slides, individual
report, peer evaluations, and any related documentation) |
|
Week 16 (May 4-10) |
|
No Final Exam |
Academic calendar: https://www.kent.edu/sites/default/files/academic-calendar-2014-2018_0.pdf
Final exam schedule: http://www.kent.edu/registrar/spring-final-exam-schedule
NOTE: Presentation dates and deadlines are
tentative. Exact dates will be announced in class!!!
60%
- Group Project
30%
- Final Presentation & Q/A
10%
- Peer Evaluation (rated by other group members)
Total: 100%
A = 90 or higher
B = 80 - 89
C = 70 - 79
D = 60 - 69
F = <60
Guidelines
for Projects/Classes
All
projects will be submitted electronically only. Instructions are given
separately.
Ø Assignments (e.g., project reports, presentation slides, code, etc.) must be submitted to Canvas by the due date. Note that, for group projects, only one group member can represent your group to submit the assignments (otherwise, it is not traceable which submission is the correct version).
Ø A project assignment turned in within two weeks after the due date will be considered late and will lose 30% of its grade.
Ø No assignment will be accepted for grading after two weeks late.
Ø The late submission needs prior consent of the instructor.
Group Project (60%): Each student is required to participate in a Group Project with other classmates. Each group will comprise of 5 students. The instructor may change the group size depending on the course enrollment. Each group will develop functional requirements and design document; implement and demonstrate the project software. Each group is required to submit their final project documentation and complete software project via Canvas.
There will be a group basic score (i.e., the same score for all members in the
group) that will form the basis, from which individual grades for the project
will be determined. The workload should be distributed evenly to each group
member. Individual scores within a project may vary, if a person's contribution
to the project is deemed to have been significantly more or less than the
group's score. The group project deliverables will account for 60% of the overall grade.
v Weekly group reports and progress: 18%
v Final project result (code/documentation): 30%
v Final individual report (at least 1,000 words): 12%
* Please send the full names, student IDs, and emails of all team members to the course instructor (Xiang Lian, xlian@kent.edu) by Feb. 3, 2023, and I will confirm your team by replying you with your group number.
Final
Project Presentation (30%): Students
will be required to make presentations of their software project to the class.
The Final Project presentation will consist of PowerPoint slides to illustrate
the goals and use cases of the software project; users'
guide and a demonstration of the software project. The Final Project Presentation will
account for 30% of the overall grade. The individual grades will be determined
based on each student's participation and performance in the presentation.
Peer Evaluations (10%): Each student is required to complete and submit the
Peer Evaluation template via assignment folder in Canvas. The
peer evaluation assignment will account for 10% of the overall grade, which will be rated
by other group members about your performance in the team
work.
Please
use the following criteria to rate yourself and each member in your group:
1. Effort/Active Participation: Following through on the project
and being accountable to group members.
2. Contribution: Improving quality of work, being creative,
bringing unique skills and abilities that aid in the quality of the final
product, and providing leadership.
3. Attendance: Attending team meetings and or group activities.
4. Supported Group Process: Eliciting and valuing input of others,
mediating arguments and relieving tension, lending a positive attitude, and
other maintenance roles that enhance group social climate.
5. Communication: Checking in with the Group before missing a
meeting, clarifying expectations, keeping communication channels open,
facilitating others' participation, and "speaking" and "listening"
effectively.
Attendance in the lecture is
mandatory. Students are expected to attend lectures, study the text, and
contribute to discussions. You need to write your name on attendance sheets
throughout the course, so please attend every lecture.
Students are expected to attend all
scheduled classes and may be dropped from the course for excessive absences.
Legitimate reasons for an "excused" absence include, but are not
limited to, illness and injury, disability-related concerns, military service,
death in the immediate family, religious observance, academic field trips, and
participation in an approved concert or athletic event, and direct
participation in university disciplinary hearings.
Even though any absence can
potentially interfere with the planned development of a course, and the student
bears the responsibility for fulfilling all course requirements in a timely and
responsible manner, instructors will, without prejudice, provide students
returning to class after a legitimate absence with appropriate assistance and
counsel about completing missed assignments and class material. Neither
academic departments nor individual faculty members are required to waive
essential or fundamental academic requirements of a course to accommodate
student absences. However, each circumstance will be reviewed on a case-by-case
basis.
No make-up presentation will be given except for university sanctioned excused absences. If you miss a presentation (for a good reason), it is your responsibility to contact me before the presentation, or soon after the presentation as possible.
The University expects a student to
maintain a high standard of individual honor in his/her scholastic work. Unless
otherwise required, each student is expected to complete his or her assignment
individually and independently (even in the team, workload should be
distributed to team members to accomplish individually). Although it is encouraged
to study together, the work handed in for grading by each student is expected
to be his or her own. Any form of academic dishonesty will be strictly
forbidden and will be punished to the maximum extent. Copying an assignment
from another student (team) in this class or obtaining a solution from some
other source will lead to an automatic failure for this course and to a
disciplinary action. Allowing another student to copy one's work will be
treated as an act of academic dishonesty, leading to the same penalty as
copying.
University policy 3-01.8 deals with
the problem of academic dishonesty, cheating, and plagiarism. None of these
will be tolerated in this class. The sanctions provided in this policy will be
used to deal with any violations. If you have any questions, please read the
policy at http://www.kent.edu/policyreg/administrative-policy-regarding-student-cheating-and-plagiarism and/or ask.
No food or beverages (except bottled water) are allowed in the classroom. Tobacco, etc. is not allowed in class at any time. Please turn off cell phones prior to the beginning of class. The use of cell phones, iPods, MP3 players, etc. is prohibited during lecture.
University policy 3-01.3 requires that students with disabilities be provided reasonable accommodations to ensure their equal access to course content. If you have a documented disability and require accommodations, please contact the instructor at the beginning of the semester to make arrangements for necessary classroom adjustments. Please note, you must first verify your eligibility for these through Student Accessibility Services (contact 330-672-3391 or visit www.kent.edu/sas for more information on registration procedures).
This course may be used to satisfy the University Diversity requirement. Diversity courses provide opportunities for students to learn about such matters as the history, culture, values and notable achievements of people other than those of their own national origin, ethnicity, religion, sexual orientation, age, gender, physical and mental ability, and social class. Diversity courses also provide opportunities to examine problems and issues that may arise from differences, and opportunities to learn how to deal constructively with them.
This course may be used to satisfy the Writing Intensive Course (WIC) requirement. The purpose of a writing-intensive course is to assist students in becoming effective writers within their major discipline. A WIC requires a substantial amount of writing, provides opportunities for guided revision, and focuses on writing forms and standards used in the professional life of the discipline.
This course may be used to fulfill the university's Experiential Learning Requirement (ELR) which provides students with the opportunity to initiate lifelong learning through the development and application of academic knowledge and skills in new or different settings. Experiential learning can occur through civic engagement, creative and artistic activities, practical experiences, research, and study abroad/away.
The instructor reserves the right to alter this syllabus as necessary.