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Course Planning by Program

2024-25

Essential Objectives

Course Syllabus


Revision Date: 20-May-24
 

Fall 2024 | CIS-1280-VO01 - Introduction to Data Analytics


Online Class

Online courses take place 100% online via Canvas, without required in-person or Zoom meetings.

Location: Online
Credits: 3 (45 hours)
Day/Times: Meets online
Semester Dates: 09-03-2024 to 12-16-2024
Last day to drop without a grade: 09-16-2024 - Refund Policy
Last day to withdraw (W grade): 11-04-2024 - Refund Policy
This section is waitlisted (0). Please contact your nearest center for availability.

Faculty

Hilary Ivy
View Faculty Credentials

Hiring Coordinator for this course: Deb Grant

General Education Requirements


This section meets the following CCV General Education Requirement(s) for the current catalog year:
VSCS Digital and Technical Literacy
    Note
  1. Many degree programs have specific general education recommendations. In order to avoid taking unnecessary classes, please consult with additional resources like your program evaluation, your academic program catalog year page, and your academic advisor.
  2. Courses may only be used to meet one General Education Requirement.

Course Description

This course introduces foundational skills, concepts, applications, and techniques used in the field of data analytics. Students explore a variety of applied business scenarios and examine how analysts structure, present, communicate and make data-driven decisions. Topics include data types and formats, structured thinking, bias and the ethical use of data, the role of databases and spreadsheets, and best practices for organizing and securing data.


Essential Objectives

1. Define and explain key concepts, practices, analytical skills, tools, and processes used in data analytics.
2. Demonstrate effective questioning techniques and strategies that help guide data analysis.
3. Discuss the role of spreadsheets, query languages, and data visualization tools in data analytics.
4. Explain how each step of the problem-solving process contributes to common data analysis scenarios.
5. Examine how analysts decide which data to collect for analysis.
6. Discuss the use of data in the decision-making process including how data analysts present and communicate findings with teams and stakeholders.
7. Demonstrate the use of spreadsheets in the data life cycle including organization, formulas, functions, and custom data tables.
8. Describe how analysts use spreadsheets and SQL with databases and data sets.
9. Examine how assumptions, decisions, and data sources can lead to biased data sets, skewed outcomes, inaccuracy, lack of credibility, and/or systemic prejudice.
10. Explore open data and the relationship between and importance of data ethics and data privacy.
11. Identify best practices for organizing and securing data.
12. Explore the scope and diversity of career opportunities in the field of data analytics through assignments such as informational interviews, job shadows, or other career-exploration activities.


Required Technology

More information on general computer and internet recommendations is available on the CCV IT Support page. https://support.ccv.edu/general/computer-recommendations/

Please see CCV's Digital Equity Statement (pg. 45) to learn more about CCV's commitment to supporting all students access the technology they need to successfully finish their courses.


Required Textbooks and Resources


*** This is a no cost textbook or resource class. ***

This course uses one or more textbooks/books/simulations, along with free Open Educational Resources (OER) and/or library materials.

Fall 2024 textbook/book details will be available on 2024-05-20. On that date a link will be available below that will take you to eCampus, CCV's bookstore. The information provided there will be specific to this class. Please see this page for more information regarding the purchase of textbooks/books.

CIS-1280-VO01 Link to Textbooks for this course in eCampus.

For Open Educational Resources (OER) and/or library materials details, see the Canvas Site for this class.

The last day to use a Financial Aid Advance to purchase textbooks/books is the 3rd Tuesday of the semester. See your financial aid counselor at your academic center if you have any questions.


Artificial Intelligence(AI) Policy Statement

CCV recognizes that artificial intelligence (AI) and generative AI tools are widely available and becoming embedded in many online writing and creative applications.

Integrated: This course's generative AI policy acknowledges the use of AI is an essential skill in today's world. By using genAI for specific purposes, students become equipped with relevant skills and tools necessary to thrive in a technology-driven society. Emphasizing the mastery of generative AI should empower you to harness its potential, enhancing your problem-solving abilities and preparing you for future challenges and opportunities. Be aware, however, that any time generative AI is used at any point in the assignment without attribution it may be considered a violation of CCV's Academic Integrity Policy.


Methods

  • Hands-on Practice: Provide students with sample data sets and guide them through creating spreadsheets, formatting cells, entering formulas, and using various functions. Encourage them to follow along and practice as you demonstrate.
  • Real-world Examples: Use practical examples from different industries or scenarios to illustrate how spreadsheets are used in the real world. This helps students understand the relevance and applicability of the skills they are learning.
  • Step-by-Step Tutorials: Break down complex tasks into smaller, manageable steps and provide detailed tutorials or worksheets for students to follow. This approach ensures that no one gets left behind and everyone can work at their own pace.
  • Collaborative Learning: Encourage students to work in pairs or small groups on spreadsheet projects or assignments. This fosters peer learning, teamwork, and the ability to troubleshoot problems together.
  • Visual Aids: Use screencasts, video tutorials, or live demonstrations to visually explain concepts and techniques. Visual aids can help reinforce understanding and provide a reference for students to review later.
  • Quizzes and Lab Assessments: Incorporate quizzes, practice exercises, or mini-projects to assess students' understanding and provide feedback on their progress.

Grading Criteria

CCV Letter Grades as outlined in the Evaluation System Policy are assigned according to the following chart:

 HighLow
A+10098
A Less than 9893
A-Less than 9390
B+Less than 9088
B Less than 8883
B-Less than 8380
C+Less than 8078
C Less than 7873
C-Less than 7370
D+Less than 7068
D Less than 6863
D-Less than 6360
FLess than 60 
P10060
NPLess than 600


Attendance Policy

Regular attendance and participation in classes are essential for success in and are completion requirements for courses at CCV. A student's failure to meet attendance requirements as specified in course descriptions will normally result in a non-satisfactory grade.

  • In general, missing more than 20% of a course due to absences, lateness or early departures may jeopardize a student's ability to earn a satisfactory final grade.
  • Attending an on-ground or synchronous course means a student appeared in the live classroom for at least a meaningful portion of a given class meeting. Attending an online course means a student posted a discussion forum response, completed a quiz or attempted some other academically required activity. Simply viewing a course item or module does not count as attendance.
  • Meeting the minimum attendance requirement for a course does not mean a student has satisfied the academic requirements for participation, which require students to go above and beyond simply attending a portion of the class. Faculty members will individually determine what constitutes participation in each course they teach and explain in their course descriptions how participation factors into a student's final grade.


Participation Expectations

Participation in discussion forums is an integral part of building a community for this remote class. There are multiple discussion post assignments throughout the semester. For all discussion post assignments student's initial submission must be received at least THREE days BEFORE the assignment due date. Response post to your classmates must be received by the due date to recieve full credit.

Zero tolerance policy for bigoted, racist, msogynist or xneophobic statements in this class. Failure to engage respectfully with your peers will affect your final grade.



Missing & Late Work Policy

Late work will recieve an automatic deduction of 5 points for each day late. Missing work will receive a zero. If you are having trouble keeping up with your work please reach out early.


Accessibility Services for Students with Disabilities:


CCV strives to mitigate barriers to course access for students with documented disabilities. To request accommodations, please
  1. Provide disability documentation to the Accessibility Coordinator at your academic center. https://ccv.edu/discover-resources/students-with-disabilities/
  2. Request an appointment to meet with accessibility coordinator to discuss your request and create an accommodation plan.
  3. Once created, students will share the accommodation plan with faculty. Please note, faculty cannot make disability accommodations outside of this process.


Academic Integrity


CCV has a commitment to honesty and excellence in academic work and expects the same from all students. Academic dishonesty, or cheating, can occur whenever you present -as your own work- something that you did not do. You can also be guilty of cheating if you help someone else cheat. Being unaware of what constitutes academic dishonesty (such as knowing what plagiarism is) does not absolve a student of the responsibility to be honest in his/her academic work. Academic dishonesty is taken very seriously and may lead to dismissal from the College.