Attached are the most recent syllabi of the courses i am planning to register for this upcoming semester (Fall 2023) and was hoping to get an expert to complete those for me.
Untitled Studocu is not sponsored or endorsed by any college or university MGT6203 OMSA Spring 2023 Data Analytics Syllabus v0 data analytics in business (Georgia Institute of Technology) Studocu is not sponsored or endorsed by any college or university MGT6203 OMSA Spring 2023 Data Analytics Syllabus v0 data analytics in business (Georgia Institute of Technology) Downloaded by Claudia Nounous (
[email protected]) lOMoARcPSD|22834647 https://www.studocu.com/en-us?utm_campaign=shared-document&utm_source=studocu-document&utm_medium=social_sharing&utm_content=mgt6203-omsa-spring-2023-data-analytics-syllabus-v0 https://www.studocu.com/en-us/document/georgia-institute-of-technology/data-analytics-in-business/mgt6203-omsa-spring-2023-data-analytics-syllabus-v0/49578007?utm_campaign=shared-document&utm_source=studocu-document&utm_medium=social_sharing&utm_content=mgt6203-omsa-spring-2023-data-analytics-syllabus-v0 https://www.studocu.com/en-us/course/georgia-institute-of-technology/data-analytics-in-business/4527748?utm_campaign=shared-document&utm_source=studocu-document&utm_medium=social_sharing&utm_content=mgt6203-omsa-spring-2023-data-analytics-syllabus-v0 https://www.studocu.com/en-us?utm_campaign=shared-document&utm_source=studocu-document&utm_medium=social_sharing&utm_content=mgt6203-omsa-spring-2023-data-analytics-syllabus-v0 https://www.studocu.com/en-us/document/georgia-institute-of-technology/data-analytics-in-business/mgt6203-omsa-spring-2023-data-analytics-syllabus-v0/49578007?utm_campaign=shared-document&utm_source=studocu-document&utm_medium=social_sharing&utm_content=mgt6203-omsa-spring-2023-data-analytics-syllabus-v0 https://www.studocu.com/en-us/course/georgia-institute-of-technology/data-analytics-in-business/4527748?utm_campaign=shared-document&utm_source=studocu-document&utm_medium=social_sharing&utm_content=mgt6203-omsa-spring-2023-data-analytics-syllabus-v0 Course Syllabus & Schedule Data Analytics in Business MGT 6203 Online Spring 2023 [v0.9 – 18 November 2022] PROFESSORS: Frederic Bien, PhD, MS.QCF Email:
[email protected] Office: 496 (or 4161) in Scheller College of Business Class Time and Location: Online in Canvas and EdX Professor Bien’s Office Hours in Zoom: Wednesdays 8:30-9:30 pm (Eastern Time) for OMSA/Canvas students, and Tuesdays 8:30-9:30 pm for MicroMaster/EdX students, or by appointment. TA Office Hours in Zoom: Monday evening office hours 7:00-8:00 pm (Eastern Time) for MicroMaster/EdX, and 8:30-9:30 pm (Eastern Time) for OMSA/Canvas. TAs office hours provide important guidance and tips for R code, review the past week’s content, cover advanced R-code topics, and questions & answers . TEACHING ASSISTANTS: 1. Ronak Patel (Lead TA) 2. Evan Jones (Assistant Lead TA for OMSA students in Canvas) 3. Maria Fernanda Romero-Creel (Assistant Lead TA for Micromaster students in EdX) 4. Xinyue Zhao (Assistant Lead TA for Vocareum & GitHub Platform) Other TAs : 14 more TAs most of whom worked on our team in previous semesters, so they are well prepared to answer your questions. Please check our Piazza.com Forums in the first week of class for our list of TAs. Check Piazza regularly through the semester. Teaching Assistants are very important in this course, as you will find out in Piazza, and when joining our weekly office hours sessions. You can ask questions at any time in Piazza online forums. TAs will answer your questions, and sometimes other students in the class may answer you. All students are encouraged to participate in online discussions in Piazza for this course. Please note we can see the activity level of students in Piazza. Typically, more active students do better in the course. 1 Downloaded by Claudia Nounous (
[email protected]) lOMoARcPSD|22834647 http://www.piazza.com/ mailto:
[email protected] https://www.studocu.com/en-us?utm_campaign=shared-document&utm_source=studocu-document&utm_medium=social_sharing&utm_content=mgt6203-omsa-spring-2023-data-analytics-syllabus-v0 GUEST LECTURES BY: Prof. Sridhar Narasimhan, Prof. Jonathan Clarke, Prof. Bob Myers from Georgia Tech Scheller College of Business COURSE BRIEF DESCRIPTION The primary objective of this course is to teach the scientific process of transforming data into insights for making better business decisions. This course covers basic methodologies, algorithms, and challenges related to analyzing business data. Then we will study applications of data analysis in: 1) Finance & Investments 2) Marketing & Advertising 3) Operations & Logistics. PREREQUISITE Some Calculus and Linear Algebra: exp and log functions, series expansions Basic Probability and Statistics, especially multilinear regression Some background in programming, esp. R, or willingness to learn quickly Introductory course in Analytics Modeling (not required but helpful) COURSE GOALS After taking this course, students will be able to: approach business problems data-analytically. Students should be able to think carefully and systematically about whether and how data and business analytics can improve business performance. develop business analytics ideas, start projects to analyze data using business analytics software, and generate relevant business insights for decision-making. TEXTBOOKS Required: (ISLR) Introduction to Statistical Learning with Applications in R, by Gareth James, Daniela Witten, Trevor Hastie & Robert Tibshirani. Publ. Springer, New York (2017). ISBN: 978-1461471370. Download the second edition for free in PDF at www.statlearning.com. It is also available for purchase in paper form at Amazon.com, BN.com, Ebay.com, etc. (First edition of the book is pretty similar for our purpose here.) You will need to purchase and download seven case studies from Harvard Business School online library. Here is a link to a package to buy online: https://hbsp.harvard.edu/import/999984 Not required, but a good business analytics book: Data Science for Business: What you need to know about data mining and data analytic thinking, Foster Provost & Tom Fawcett, O’Reilly Media, ISBN-13: 978-1449361327. Available from Amazon, BN.com, EBay, etc. 2 Downloaded by Claudia Nounous (
[email protected]) lOMoARcPSD|22834647 https://hbsp.harvard.edu/import/999984 http://BN.com/ http://www.statlearning.com/ COURSE DESCRIPTION Today businesses, consumers, communities and societies create or manage massive amounts of data as a by-product of their activities. Companies in every industry are using data analytics to add to, or replace, intuition and guesswork in their decision-making. As a result, business managers can use their data troves and analytical skills to discover new patterns and insights, and/or to run controlled experiments to test various hypotheses. This course prepares students to understand business analytics and become leaders in these areas in business organizations. This course teaches the scientific process of transforming data into insights for making better business decisions. It covers the methodologies, issues, and challenges related to analyzing business data. This course will illustrate key processes of analytics by allowing students to apply business analytics algorithms and methodologies to various business problems. (Data collection and definition are also critical steps for understanding of phenomena and predictions. We won’t have time to discuss data collection in this course unfortunately.) The use of carefully selected examples places business analytics techniques in context and teaches students how to avoid the common pitfalls, emphasizing the importance of applying proper business analytics techniques. The course will also show that often there can be more than one “good answer” or one “good choice”. We need to be discerning in the type of data that we choose to analyze and how we analyze it. HARDWARE REQUIREMENTS Please follow GeorgiaTech’s computer ownership guide at http://sco.gatech.edu/. Make sure that you have admin rights on your laptop since occasionally you will need to install R, RStudio, many packages in R, and other software like Radiant, maybe Gephi. Note that tablets, Chromebooks, and old laptops may not work well for this class at this time. (As we move the course toward use of R notebooks, eventually they will work.) SOFTWARE REQUIREMENTS We will be learning business analytics with the help of open-source and free software applications that are provided for educational use. Please follow instructions provided in their respective websites and install the following software in your personal laptop: a. R: https://www.r-project.org/ b. RStudio: https://www.rstudio.com/ There are many resources on how to learn R. We will discuss some in the course. R for Datascience: http://r4ds.had.co.nz/ RStudio Education: https://education.rstudio.com/ Swirl: www.SwirlStats.com DataCamp: www.DataCamp.com/courses/free-introduction-to-r 3 Downloaded by Claudia Nounous (
[email protected]) lOMoARcPSD|22834647 http://www.DataCamp.com/courses/free-introduction-to-r http://www.SwirlStats.com/ https://education.rstudio.com/ http://r4ds.had.co.nz/ https://www.rstudio.com/ https://www.r-project.org/ http://sco.gatech.edu/ https://www.studocu.com/en-us?utm_campaign=shared-document&utm_source=studocu-document&utm_medium=social_sharing&utm_content=mgt6203-omsa-spring-2023-data-analytics-syllabus-v0 c. Some homework can be done using Radiant: https://radiant- rstats.github.io/docs/install.html - a convenient and free web-browser-based user interface for analyzing and visualizing datasets in R. We’ll discuss in office hours. Instructions for installing R, then RStudio, and Radiant on a Mac; similar steps on Windows. 1. Download and run the R installer: https://cloud.r-project.org/bin/macosx/base/R-release.pkg 2. Download and run the RStudio installer: https://rstudio.com/products/rstudio/download/#download 3. Open RStudio. 4. At the prompt, enter exactly this: install.packages("radiant") 5. Wait for the install to complete; it will install a bunch of packages. 6. In the top navigation bar, select Tools → Addins → Browse Addins... Click Radiant 7. When prompted, opt in to install additional packages. 8. Radiant should open in a new tab in your default browser. Now use R from your browser. GitHub For the group project phase of the course, students will be required to use GitHub, a version control platform which can be used entirely within a web browser or used with their application GitHub Desktop. We make this requirement for a couple of reasons. Firstly, knowing how to use and be productive with Git/GitHub is an extremely valuable skill in Data Science and Machine Learning. Version control is an important technology that makes working on code in groups (or individually) practical and efficient. Secondly, GitHub offers the ability to track contributions to a project. Sometimes disputes about a group member participation can arise, and in order to settle these disputes in an unbiased and fair way, we may use GitHub's records of contributions (also known as ‘commits’) to verify and remedy these claims. Additional information about the course’s use of GitHub will be available in the Group Project Instructions page that will be distributed at the start of the group project. If you’ve taken computer science courses at GeorgiaTech, learning GitHub may have been part of that course. If you are not familiar with GitHub or version control, here are two short courses on Lynda.com (you can login via Lynda.gatech.edu) (now owned by LinkedIn but still free to GA Tech Students) that will teach you the basics: Lynda/LinkedIn: Fundamentals of Software Version Control Lynda/LinkedIn: Up and Running with Git & GitHub There is a slightly longer, more in-depth course that will teach you every single feature of Git: Lynda/LinkedIn: Git Essential Training In addition to these courses there are innumerable resources available online and on YouTube that do an excellent job at quickly getting you productive in GitHub and are completely free. Here are some popular ones: Anson Alexander: GitHub Tutorial freeCodeCamp.org Git and GitHub for Beginners – Crash Course 4 Downloaded by Claudia Nounous (
[email protected]) lOMoARcPSD|22834647 https://www.youtube.com/watch?v=RGOj5yH7evk https://www.youtube.com/watch?v=iv8rSLsi1xo https://www.lynda.com/Git-tutorials/Git-Essential-Training/100222-2.html https://www.lynda.com/Git-tutorials/Up-Running-Git-GitHub/409275-2.html https://www.lynda.com/Version-Control-tutorials/Fundamentals-Software-Version-Control/106788-2.html https://rstudio.com/products/rstudio/download/#download https://cloud.r-project.org/bin/macosx/base/R-release.pkg https://radiant-rstats.github.io/docs/install.html https://radiant-rstats.github.io/docs/install.html COMMUNICATION Instructor/TA Communication: All course announcements will be made via Canvas or EdX. You are expected to check Canvas/EdX a few times per week for important course-related information. By following the instructions provided in Canvas/EdX, you can ensure that you do not miss important instructions, announcements, etc. If you want, you can adjust your Canvas/EdX account settings to receive important information directly to your email account or cellphone. To get started, log into the Canvas/EdX, click on this course, and see the section entitled “Before You Begin: Instructions for Getting Started.” Content Questions and Help: Because questions can often be addressed for the good of the group, please do not email your questions directly to the instructor. Instead, course and content questions will be addressed on an online chat platform called Piazza.com. Get an account in Piazza today. These online forums will be a VERY valuable source of information and hints about the course and problem sets. Note that you can set your post to “Private” to ask questions to the instructor and TA about issues unique to you. Office Hours. Office hours will be conducted every week by the instructor and TAs. These sessions will be both an opportunity for you to ask questions and the TAs may discuss course logistics and content. All sessions may not be recorded. The ones that are recorded will be available via Canvas under the “Zoom” tab or via links posted in Piazza (for EdX students). Please note that many students see great benefits for this course in attending online office hours via videoconference. Monday evenings office hours are taught mainly by our TAs, who are particularly helpful to learn programming skills. Office hours with the course instructor/professor (on Tuesday or Wednesday, depending if you are an EdX student or OMSA student) are focused on discussing business ideas and additional material for the course; also to go over topics covered in the video lectures. These videoconferences are part of the course. You’ve already paid for them with your tuition. We recommend you try to attend them as often as you can and PARTICIPATE. You can learn faster by being an active participant in online office hours and in Piazza online forums… You can attend them silently without sharing audio & video. STUDENT EFFORT Students are expected to devote about 10 to 12 hours per week of studying time to complete this course requirements. (That’s about 1.5 to 2 hours per day!) This guideline encompasses all class activities, including reading the textbook and supplementary resources, watching lesson videos, participating in office hours and forum discussions, completing homework assignments, and studying for exams. Of course, students can spend as much time as necessary, but it is important to be careful not to fall behind. 5 Downloaded by Claudia Nounous (
[email protected]) lOMoARcPSD|22834647 http://www.piazza.com/ https://www.studocu.com/en-us?utm_campaign=shared-document&utm_source=studocu-document&utm_medium=social_sharing&utm_content=mgt6203-omsa-spring-2023-data-analytics-syllabus-v0 HOMEWORK ASSIGNMENTS, EXAMS AND GRADING Grades will be assigned on the following basis: Eleven Self-Assessment Quizzes 15% (~1.36% each) Four Homework Assignments 40% (10% each. Note: these require peer grading other students’ work.) One Group Project 25% Midterm Exam – Theory Part 1 5% Midterm Exam – Computation Part 2 7% Final Exam – Theory Only 8% (Your Group