Business Analytics in Practice

  • Format: online
This six-week, self-paced course introduces the core principles, methods, and tools associated with data analytics and provides hands-on training in using popular analytical tools. The course covers advanced tools/techniques for data summarization, visualization, predictive modeling, association mining, clustering, and natural language processing. It is organized around the two foundational pillars of data analytics – descriptive analytics and predictive analytics.



PREREQUISITES: There are no prerequisites for this course. 

COURSE COMPLETION CERTIFICATE: This course is part of the Digital Transformation Consortium, which can be reviewed by selecting this link, which offers three online courses available through MU Extension and Engagement: Business Data Analytics, Coding and Programming, and Geographical Information Systems. Individuals will receive a certificate of completion for each completed course. Those who complete all three courses will receive an MU Extension Continuing Education Certificate in Digital Transformation.

CLASSROOM LOCATION & TIME: Online. This is a self-paced course. As this course is delivered entirely online in a self-paced format. In an online environment, participation and engagement are crucial for success.

INSTRUCTORS: Dr. Sharan Srinivas and Dr. Kangwon Seo Department of Industrial and Manufacturing Systems Engineering

COURSE DESCRIPTION: In today’s digital age, all industries depend on data-driven analytical models to analyze historical trends/patterns, improve processes, predict future outcomes, optimize strategies, and uncover business intelligence. Business analytics (BA), a set of methods, tools, and approaches companies use, is one of the most in-demand skills in today’s workforce. It allows a company to gain a competitive advantage, minimize operational costs, and improve customer satisfaction. The demand for professionals with a data analytics skillset remained strong even during the economic disruptions and workforce downsizing caused by the COVID-19 global pandemic. Besides, the BA-related job opportunities are expected to flourish, as the US Bureau of Labor Statistics estimates over 30% growth, one of the highest, during the next 10 years. Currently, there exists a shortage in the supply of professionals with the necessary analytics skills. This course introduces the core principles, methods, and tools associated with data analytics and provides hands-on training in using popular analytical tools. The course covers advanced tools/techniques for data summarization, visualization, predictive modeling, association mining, clustering, and natural language processing. It is organized around the two foundational pillars of data analytics – descriptive analytics and predictive analytics.  This course is based around the idea of active and experiential learning, where students learn the concepts and techniques by participating and engaging in various activities such as hands-on problem solving, tutorials, and case studies.

COURSE OBJECTIVES: The following objectives are for this six-week course. Each assessment will have a list of objectives that are in line with the following. Students who complete this course will be able to:

  • Understand the fundamentals of data analytics and its practical applications.
  • Gain quantitative problem-solving skills applicable to any industry (e.g., healthcare, manufacturing, transportation/logistics, etc.).
  • Develop and deploy state-of-the-art analytical tools for optimizing operational costs, business process efficiency, and service quality.
  • Derive data-driven business intelligence.

REQUIRED TEXT: There are no required textbooks for this course. Students will be asked to view several provided online videos, articles, graphics, etc. that support the module activities, lectures, and assessments hosted on Canvas.

REQUIRED HARDWARE: At a minimum, you will need the following hardware to participate in this course:

  • A stable internet connection with a connection speed of no less than 10 Mbps
  • Although not required, a large and/or multi-monitor display configuration may be useful

REQUIRED SOFTWARE: At a minimum, you will need the following software to participate in this course:

  • A computer with an up-to-date operating system (e.g., Windows, Mac, or Linux) and web browser (e.g., Firefox, Chrome, or Edge) of your choice
  • A PDF reader of your choice (e.g., Adobe, a web browser, etc.)
  • Microsoft Excel
  • R - Data Analytics Software, which can be downloaded by selecting this link
  • An IDE (Integrated Development Environment) of your choice. This course recommends the following IDEs:

COURSE ANNOUNCEMENTS, CANVAS INFO, & ONLINE PARTICIPATION: There is a Canvas site dedicated to this class (obviously). This is where grades will be posted, important announcements will be made (pay attention to these), module instructions and assessments are housed, etc. Content and lessons are divided into several modules. Announcements will be posted at the beginning of the week with a summary of what's to come or if there are any time-specific events you should be aware of. Ensure you have notifications turned on for course announcements, or check announcements regularly if doing so manually. It is your responsibility to stay up to date with all course announcements.



Grades are based on the total points earned divided by the total points possible in the course. There will be 100 total points possible in the course. An ending grade of 60% (60/100 points) is needed to pass the course and receive the course completion certificate. Assessments will be based on instructor material, demonstrations, and lectures. Assessments will be automatically graded with instant feedback.

  • (20%) Quiz 1: This quiz will assess your competencies over Module 1 content.

  • (20%) Quiz 2: This quiz will assess your competencies over Module 2 content.

  • (20%) Quiz 3: This quiz will assess your competencies over Module 3 content

  • (20%) Quiz 4: This quiz will assess your competencies over Module 4 content

  • (20%) Quiz 5: This quiz will assess your competencies over Module 5 content.


LATE WORK: This policy applies to all submissions and assessments unless otherwise noted directly on an assessment page/course announcement. Late submissions will not be accepted. Makeup assignments will be given only in cases of verified illness or in unusual extenuating circumstances approved beforehand by the instructor/support staff.


COURSE SCHEDULE: It is important to note that the schedule may change should the need arise. However, for the time being, the following schedule can be used as a guide of what subjects will be covered, as well as when they will be covered.


Date/Academic Week

Module Topics
Module Description Assessments

Week 1

Module 0 - Course Introduction, Resources, and FAQs


Module 1 - Introduction to Business Analytics

In Module 0, we'll go over the functionality of this class and the tools needed to be successful throughout the course.

In Module 1, we'll provide an overview of business analytics and introduce some fundamental concepts in statistics.

Quiz 1

Week 2

Module 2 - Exploratory Analysis and Visualization In Module 2, we'll cover the first pillar of business analytics called descriptive analytics.  Quiz 2

Week 3

Module 3 - Overview of Predictive Analytics In Module 3, we'll provide an overview of predictive analytics and revisit linear regression from a machine learning perspective. Quiz 3

Weeks 4-5

Module 4 - Supervised Machine Learning In Module 4, we'll cover the principles and implementation of four important supervised machine learning algorithms. In addition, we will also cover dimensionality reduction and process optimization. Quiz 4

Week 6

Module 5 - Unsupervised Machine Learning 


Module 6 - Course Wrap-up

In Module 5, we'll cover popular clustering and association algorithms.

In Module 6, we'll wrap up the course and discuss the remaining steps necessary to obtain the MU Extension Continuing Education Certificate in Digital Transformation.

Quiz 5



The information below also appears in Canvas under “Supports & Policies” > “MU Policies and Expectations,” so that all students in all courses have access to this.

CLASSROOM SAFETY & EMERGENCY PLAN: If you have any classes on campus and there is an active threat in the area I recommend you immediately check your surroundings and take action by running, hiding, or fighting. Learn more by watching Surviving an Active Shooter. Lastly, be sure you are signed up for MU Alert, the University's mass emergency notification system.

MENTAL HEALTH AWARENESS: The University of Missouri is committed to supporting student well-being through an integrated network of care, with a wide range of services to help students succeed. The MU Counseling Center offers professional mental health care and can help you find the best approach to treatment based on your needs. Call to make an appointment at 573-882-6601. Any student in crisis may call or go to the MU Counseling Center between 8:00 – 5:00 M-F. After-hours phone support is available at 573-882-6601. Visit our website at to take an online mental health screening, find out about workshops and resources that can help you thrive, or learn how to support a friend. Download Sanvello, a phone app that teaches skills and strategies to help you maintain good mental health. Log in with your Mizzou e-mail to unlock all the tools available through Sanvello at no cost to you.

STUDENTS WITH DISABILITIES: The goal of the University of Missouri is to ensure an inclusive learning environment for all students. The University of Missouri Disability Center provides services and accommodations for students to participate fully in the learning experience and to experience equitable evaluation of their performance. Students (including online students) with a documented disability can contact the Disability Center to establish an Accommodation Plan. Documented disabilities include hearing, vision, mobility, learning and attention, psychological health, and physical health. Students’ accommodations are implemented with the input of students to maximize the learning experiences. The MU Disability Center keeps the information about a student’s disability confidential. 

Please notify me of your eligibility for accommodations as soon as possible. Additionally, if there are aspects of the course that present as barriers, such as inaccessible course content (e.g., learning assessments, PowerPoints, non-captioned videos, images, tables, PDFs) or if you need an immediate accommodation due to an injury, please contact me or the Disability Center as soon as possible.


Academic integrity is fundamental to the activities and principles of a university. All members of the academic community must be confident that each person’s work has been responsibly and honorably acquired, developed, and presented. Any effort to gain an advantage not given to all students is dishonest whether or not the effort is successful. The academic community regards breaches of the academic integrity rules as extremely serious matters. Sanctions for such a breach may include academic sanctions from the instructor, including failing the course for any violation, to disciplinary sanctions ranging from probation to expulsion. When in doubt about plagiarism, paraphrasing, quoting, collaboration, or any other form of cheating, consult the course instructor or the Office of Academic Integrity.

Students are expected to adhere to this honor pledge on all graded work whether or not they are explicitly asked in advance to do so: “I strive to uphold the University values of respect, responsibility, discovery, and excellence. On my honor, I pledge that I have neither given nor received unauthorized assistance on this work.”

NETIQUETTE: We all want to foster a safe online learning environment. All opinions and experiences, no matter how different or controversial they may be perceived, must be respected in the tolerant spirit of academic discourse. You are encouraged to comment, question, or critique an idea but you are not to attack an individual. Our differences, some of which are outlined in the University’s nondiscrimination statement, will add richness to this learning experience. Please consider that sarcasm and humor can be misconstrued in online interactions and generate unintended disruptions. Working as a community of learners, we can build a polite and respectful course ambiance.

NON-DISCRIMINATION POLICY: The University of Missouri does not discriminate based on race, color, national origin, ancestry, religion, sex* (including gender), pregnancy, sexual orientation, gender identity, gender expression, age, disability, protected veteran status, and any other status protected by applicable state or federal law. Discrimination includes any form of unequal treatment such as denial of opportunities, harassment, and violence. *Sex discrimination includes rape, sexual assault, sexual harassment, unwanted touching, stalking, dating/domestic violence, stalking, and sexual exploitation. Retaliation for making or supporting a report of discrimination or harassment is also prohibited.

If you experience discrimination or sexual violence, you are encouraged (but not required) to report the incident to the MU Office for Civil Rights & Title IX. Learn more about your rights and options at or call 573-882-3880.  You also may make an anonymous report online. 

If you are a survivor, or someone concerned about a survivor, and need immediate information on what to do, see Both the Office for Civil Rights & Title IX and the RSVP Center can assist students who need help with academics, housing, or other issues.

If you choose to write or speak about having experienced any of these forms of prohibited discrimination or harassment, Mizzou policies require that, as your instructor, I share this information with the MU Office for Civil Rights & Title IX. They will contact you to offer information about resources, as well as your rights and options as a member of our campus community.

INTELLECTUAL PLURALISM: The university community welcomes intellectual diversity and respects student rights. Students who have questions or concerns regarding the atmosphere in this class (including respect for diverse opinions) may contact the departmental chair or divisional director, the Office of Academic Integrity, or the MU Equity Office.

ACADEMIC INQUIRY, COURSE DISCUSSION, & PRIVACY: When students record something that happens in a course (a lecture, class discussions, meetings, etc.) it has an impact on the rights of the people captured in that recording. For example, the instructor and the University may have rights to the intellectual property contained in that recording. At the same time, another student who may have been recorded has the right to privacy. To protect these rights, MU employs a policy (called “Executive Order No. 38”) to govern both situations you may encounter while taking a course – when an instructor allows recordings and when they do not.

In this class, students may not make audio or video recordings of course activity, except students permitted to record as an accommodation under section 240.040 of the Collected Rules. Students who violate this policy are subject to discipline per provisions of section 200.020 of the Collected Rules and Regulations of the University of Missouri about student conduct matters.



*Disclaimer: The instructor reserves the right to make changes to this syllabus, and course schedule during the semester.