ITEC-320-003: Business Analytics
Hello, dear friend, you can consult us at any time if you have any questions, add WeChat: daixieit
ITEC-320-003: Business Analytics
Instructor Information
FACULTY NAME: Rexford Trudell
LINK TO FACULTY BIO: https://www.american.edu/kogod/faculty/rtrudell.cfm
E-MAIL: [email protected]
OFFICE HOURS: Zoom, Schedule as needed
EMAIL RESPONSE TIME: Within 24 hours
ASSIGNMENTS FEEDBACK AND GRADING: Within 1 week
TA Information
See information provided in CANVAS
Class Time: Asynchronous
Course Description
Analytics is the process of transforming data into insight for making better decisions. It involves specifying a question, problem, or decision and finding the right answers using data. The process begins with identifying the appropriate data sources (internal and/or external, structured and/or unstructured), and the appropriate models, tools, and methods for analysis. Two areas of analytics are covered in this course: descriptive analytics examines historical data and identifies and reports historical patterns and trends, while predictive analytics predicts future trends and outcomes and discovers new relationships. Students are introduced to models, tools, and methods that are commonly used in each area of analytics. They develop skills in analytics that allow them to present data-driven solutions to problems in different business disciplines and functions. The course emphasizes model development and use of software tools to manage, report, and analyze data to achieve the best outcomes for a business.
Prerequisites: ITEC 200, STAT 202
Learning objectives:
After completing ITEC 320, a student should be able to:
1. Obtain and process data from existing data sources.
2. Use descriptive techniques to summarize data.
3. Build forecasting models to predict future outcomes.
4. Apply clustering techniques to data sets.
5. Apply prediction methods for numerical outcomes to data sets.
6. Apply classification methods for qualitative outcomes to data sets.
7. Recognize opportunities to apply analytics in various functional areas of an organization.
8. Apply several common techniques to visualize data.
ITEC-320 is also part of the AU core, satisfying the Quantitative Literacy II (Q2) requirement, which means students will be expected to:
1. Translate real-world questions or intellectual inquiries into quantitative frameworks.
2. Select and apply appropriate quantitative methods or reasoning.
3. Draw appropriate insights from the application of a quantitative framework.
4. Explain quantitative reasoning and insights using appropriate forms of representation so that others could replicate the findings.
Class structure:
The course is fully asynchronous with an assortment of recorded lectures by various professors and software tutorials. These videos, along with the online textbook, should be watched/read each week so that you can complete the assignments. They are grouped by week on Canvas. It is incumbent on you to read the material and watch the videos to be able to complete your assignments, including quizzes. Failure to complete the quizzes and assignments will have a detrimental effect on your performance on the Mid-Term and Final Exams.
The textbook for the course is Data Mining for the Masses, by Matthew North. A free pdf version is available at: https://docs.rapidminer.com/downloads/DataMiningForTheMasses.pdf. The data sets used by the textbook are also available for free, at https://sites.google.com/site/dataminingforthemasses3e/. In addition, occasional short readings will be provided throughout the semester.
Office hours & interacting with your instructor:
I check email frequently; that’s my preferred method of communication. Please feel free to email me any time if you have a question. My official policy is that I will get back to you within 24 hours.
Due to the class being fully online and students being spread out across time zones, I won’t be holding office hours at a fixed day & time. If you would like to meet, please email me with a few suggested upcoming dates/times that work for you, and I will create a Zoom meeting invite once we find a time slot that works. Generally, I will be unavailable between 8:00 PM and 8:00 AM and on Weekends. However, in extenuating circumstances, I will try to accommodate you – particularly students in another time zone.
Peer-Assisted Student Support (PASS) Program
The Peer-Assisted Student Support (PASS) Program offers free, online tutoring in ITEC-320. The PASS Program also provides tutoring in 20+ courses to students enrolled at AU in information technology, accounting, biology, chemistry, computer science, and several other academic disciplines.
To view the tutoring schedule, see our supported courses, and to meet with PASS Tutors, please visit WCOnline (https://american.mywconline.net/).
Software tools:
We will primarily use Excel (including the Data Analysis add-in) and RapidMiner, which is available for free at https://my.rapidminer.com/nexus/account/index.html#downloads. We will also use Tableau for visualizing data; a free student version is available at https://www.tableau.com/academic/students. You will be expected to bring your laptop to class, and to be able to run the software tool(s) being used that week.
Important Dates: Academic alert deadline is Feb 20; last day to drop the course is Mar 24
Grading:
|
Deliverable |
Percentage |
Composition |
|
HW Assignments |
12% (4 assignments, 3% each) |
Individual |
|
Quizzes |
4% (10 quizzes, 0.4% each) |
Individual |
|
Activities |
10% (6 activities, 1-3% each) |
Team |
|
Exams |
50% (25% midterm, 25% final) |
Individual |
|
Course project |
20% (1% for proposal, 3% for outline, |
Team |
|
Class Participation |
4% |
Individual |
|
TOTAL |
100% |
|
A: 93.0 or above; A-: 90.0-92.9; B+: 87.0-89.9; B: 83.0-86.9; B-: 80.0-82.9; C+: 77.0-79.9;
C: 73.0-76.9; C-: 70.0-72.9; D: 60.0-69.9; F: less than 60.0.
The course grade cutoffs are fixed and non-negotiable. Neither overall grades nor grades for individual deliverables will be curved.
Deliverables:
1. Assignments: The assignments will involve the use of software and will be submitted via Canvas. Discussing the assignments with classmates is encouraged; however, the submitted write-up must be the student’s own work. All submissions are checked automatically by anti-plagiarism software. Late submissions will lose 10% immediately, and an additional 10% for each day that they are late. Submissions 4 days or later will result in a maximum score of 50%.
2. Quizzes: There will be quizzes posted on Canvas for most weeks based on that week’s topic. The quizzes must be completed by the following Friday at 11:59PM EST (due dates are listed on CANVAS). Late submissions will lose 10% immediately, and an additional 10% for each day that they are late. Submissions 4 days or later will result in a maximum score of 50%.
3. Activities: The group activities will require students to address one or more challenges based on a real-world dataset and/or problem using techniques from the course. On weeks with an Activity assigned, they will be due on Wednesdays at 1159PM EST. Activities may be done either individually or in groups of up to five (5). Ensure that group assignments have each member’s name on the submission, so everyone gets the proper credit. All submissions are checked automatically by anti-plagiarism software. Late submissions will lose 10% immediately, and an additional 10% for each day that they are late. Submissions 4 days or later will result in a maximum score of 50%.
4. Exams: There will be a Midterm and a Final, both of which will be completed on Canvas. The exams are open-book and open-note and will require the use of software. Both exams will be time constrained. The time given will be more than adequate to complete each exam. The final exam is not cumulative; it will include only material covered since the midterm.
5. Business Analytics Project: A team with a maximum of 5 students will identify an organization and build models and methods to enhance data-driven decision making in that organization. Students will formulate the problem, identify the right sources of data, analyze data, and prescribe actions to improve both the process of decision making and the outcomes resulting from those decisions. This project will be delivered in four phases: a project proposal, a project outline, an in-class presentation, and a written report. Students may choose their own groups. There will be a fixed period for you to choose your groups; after which, if there are still students not in a group, I will randomly assign these students based on the openings available. If a student desires to work independently, I will consider that on a case-by-case basis – PLEASE contact me early if this is something you desire. NOTE: if there are groups within which there are students who do not contribute to the project, I will consider allowing those members who feel they are doing all the work to create a separate group prior to the due date of the Presentation and Final Report. Those students who have not been contributing will be responsible for submitting their own Presentations and Final Reports and will be graded separately.
6. Class Participation: Participation is measured by your diligence in completing assignments within the prescribed timeframe. The course is based on a model of active learning. Complete all assignments on time.
COURSE OUTLINE (schedule is subject to change)
The date listed in the left column is Monday’s date for that week.
|
Date |
Topics |
Readings & Deliverables |
|
MODULE 1: INTRODUCTION |
||
|
Week 1: 28-AUG |
Course Introduction |
Week 1 Videos Functions: https://tinyurl.com/33s4sywa Data Analysis: https://tinyurl.com/3yk85we5 ***Download/Install RapidMiner and Tableau and Request Student Licenses |
|
Week 2: 04-SEP |
Obtaining & Processing Data Activity: Google Trends due 06SEP 1159PM EST |
Week 2 Videos |
|
Week 3: 11-SEP |
RapidMiner tutorial |
Week 3 Videos |
|
MODULE 2: DESCRIPTIVE ANALYTICS |
||
|
Week 4: 18-SEP |
Clustering Intro |
Week 4 Videos |
|
Week 5: 25-SEP |
Data Visualization
Tableau |
Week 5 Videos |
|
Week 6: 02-OCT |
Association Rules Activity: Recipe Associations due 04OCT 1159PM EST |
Week 6 Videos
|
|
Week 7: 09-OCT |
Midterm Exam |
Mid-Term Review Practice Mid-Term |
|
MODULE 3: FORECASTING |
||
|
Week 8: 16-OCT |
Time Series Forecasting Activity: Capital Bikeshare due 18OCT 1159PM EST |
Week 8 Videos Week 8 Quiz due 20OCT 1159PM EST Moving Averages: https://tinyurl.com/4vp5kr4v Exponential Smoothing: https://tinyurl.com/2wxpcphz |
|
MODULE 4: PREDICTIVE ANALYTICS |
||
|
Week 9: 23-OCT |
Regression refresher |
Week 9 Videos Regression: https://tinyurl.com/5n6r2vnb Project Proposal due 29OCT 1159PM EST |
|
Week 10: 30-OCT |
Intro to Predictive Analytics |
Week 10 Videos |
|
Week 11: 6-NOV |
Decision Trees |
Week 11 Videos |
|
Week 12: 13-NOV |
Prediction vs. Classification |
Week 12 Videos |
|
20-NOV |
THANKSGIVING – NO CLASS |
NO CLASS |
|
Week 13: 27-NOV |
Ensemble Methods Activity: Eagleball Competition due 29NOV 1159PM EST |
|
|
PRESENTATIONS AND COURSE WRAP-UP |
||
|
Week 14: 04-DEC |
Presentations (via Zoom) 06NOV (06:00 AM – 08:00 PM EST) ***Submit presentations in CANVAS prior to your scheduled Zoom presentation. |
Project Written Reports due 08DEC 11:59 PM EST Practice Final Exam |
|
Week 15: 11-DEC |
Final Exam |
TBD on CANVAS |
The Center for Professionalism and Communications
The ProComms Center is Kogod’s in-house resource for improving your written and verbal communications, as well as developing professionalism skills such as building confidence, critical thinking, emotional intelligence, and collaboration. Our staff and peer consultants provide friendly feedback so that your communications style follows the Four C’s: it is Clear, Concise, Credible, and Creative. We also coach your presentations, providing advice on effective delivery, impactful PowerPoints, clear data visualization, and teamwork that showcases diverse, solution-oriented points of view. To make an appointment, go to Center for Professionalism and Communications. For questions, please contact us at [email protected]. For 24/7 access to our videos, guides, links to LinkedIn Learning, and colorful tip sheets to enhance all of your professionalism and communications skills, enroll in our Canvas page.
Business Netiquette
The term "Netiquette" refers to the etiquette guidelines for electronic communications, such as e-mail and discussion forum postings. Netiquette covers not only rules to maintain civility in discussions but also special guidelines unique to the electronic nature of forum messages. Please review Virginia Shea's The Core Rules of Netiquette for general guidelines that should be followed in this course.
Technical Requirements
Browser Information: For best performance, Canvas should be used on the current or first previous major release of either the Chrome or Firefox web browsers instead of Safari or Internet Explorer. Some multimedia objects will require you to enable third-party cookies in order to play them.
Canvas only requires an operating system that can run the latest compatible web browsers. Your computer operating system should be kept up to date with the latest recommended security updates and upgrades.
For more information, please see the Canvas Community's information on browser compatibility.
Canvas Course Access: This online learning course uses technology created by Canvas, a leading provider of Internet infrastructure software for online education. The minimum technical requirements needed to participate in a Canvas course are available on the AU website. Participants will use their AU account to log in at https://canvas.american.edu.
Canvas Support: Participants can get help with Canvas using the Help menu, located at the bottom of your Global Navigation menu after you log in to Canvas. Users can also visit the global Canvas Community website for how-to guides and tutorials.
AU Help Desk (focuses on all other IT issues): Answers to your technology questions are just an e-mail, instant message, or phone call away. Contact the IT Help Desk at 202-885-2550, [email protected], or AskAmericanUHelp to reach one of our professional staff who can answer your questions and provide general troubleshooting assistance. Students can also log on to the Need Help Now portal for support.
AU Policy on Server Unavailability or Other Technical Difficulties: The university is committed to providing a reliable online course system to all users. However, in the event of any unexpected server outage or any unusual technical difficulty that prevents completion of a time-sensitive assessment activity, the instructors may extend the time windows and provide an appropriate accommodation based on the situation.
UNIVERSITY POLICIES
It is our shared responsibility to know and abide by the American University’s policies that relate to all courses, which include topics like:
· Academic integrity
· Emergency Preparedness
· Copyright Violations
· Academic Support Services
· Student Support Services
· Learning Resources
Please visit https://american.instructure.com/courses/9618 for the full list of campus-wide policies and follow up with me if you have questions.
Academic Alerts
My goal as your instructor is to do what I can to support all students and facilitate their success. Academic Alert is one way to support our students. It’s a process by which your instructor can connect you to academic coaches and advisors, and an opportunity for instructors to let you know what changes you can make to achieve success in the course and engage in a learning partnership with you. This is a way to open conversation between you, your instructor, and your advisor so that together you can work out how to achieve your educational goals.
After receiving the emailed alert from me, you might also get an email from your academic advisor. Making a simple decision to reply can often be the small step you need to get back on track.
One of the best steps to take after getting an academic alert is to schedule a 30-minute session with the me so that we can discuss any areas where you are struggling or may need some guidance. Together, with other university academic resources, we can work towards getting you back on track.
DISCLAIMER
The instructor reserves the right to make modifications to this information throughout the semester.
Acknowledgement of Conditions of this Syllabus
I have read, understood, and accepted the conditions and requirements of the syllabus for ITEC-320 (Business Analytics) in Spring 2023. This includes all information regarding course material, attendance and conduct, preparation, exams and grade requirements, technology policies, and the statement and policy on academic integrity.
The syllabus acknowledgement and academic integrity quizzes on Canvas MUST be completed by the end of the second week of class.
2023-09-09