UoPeople Online Syllabus Repository (OSR)
Here you will find the syllabi and primary textbooks for all UoPeople courses. The Disclaimer for Use of the Repository can be found here.
Computer Science
CS 3440 Big Data
CS 3440: Big Data
Prerequisite: CS 3303 Data Structures
Course Description:
This course will introduce students to the fundamental concepts of big data including the definition and taxonomy. Various topics such as big data integration, data generation, storage, management, transfer, to analytics with a focus on state-of-the-art technologies and big data stream techniques, visualizations, and applications for big data. Also covered with real-world applications regarding querying big data with SQL and HiveQL, ending with a discussion on the future of big data.
Required Textbook and Materials: UoPeople courses use open educational resources (OER) and other materials specifically donated to the University with free permissions for educational use. Therefore, students are not required to purchase any textbooks or sign up for any websites that have a cost associated with them. The main required textbooks for this course are listed below, and can be readily accessed using the provided links. There may be additional required/recommended readings, supplemental materials, or other resources and websites necessary for lessons; these will be provided for you in the course's General Information and Forums area, and throughout the term via the weekly course Unit areas and the Learning Guides.
- This course does not contain a main textbook; resources to all required reading will be provided in the course Learning Guide for each week.
Software Requirements/Installation: No special requirements.
Learning Objectives and Outcomes:
By the end of this course students will be able to:
- Explain big data and its basic characteristics
- Compare and contrast existing big data processing data platforms and tools.
- Demonstrate how to query big data repositories.
- Explain clustering and data analysis of big data
- Discuss the trends of big data and its future advancement
Course Schedule and Topics: This course will cover the following topics in eight learning sessions, with one Unit per week. The Final Exam will take place during Week/Unit 9 (UoPeople time).
Week 1: Unit 1 - Introduction to Big Data
Week 2: Unit 2 - Big Data Tools, Techniques, and Systems
Week 3: Unit 3 - Analytical Theories and Methods
Week 4: Unit 4 - Querying Big Data
Week 5: Unit 5 - Big data and privacy
Week 6: Unit 6 - Using big data in business
Week 7: Unit 7 - Trends in Big data
Week 8: Unit 8 - Future of Big Data
Week 9: Unit 9 - Course Review and Final Exam
Learning Guide: The following is an outline of how this course will be conducted, with suggested best practices for students.
Unit 1: Introduction to Big Data
- Read the Learning Guide and Reading Assignments
- Participate in the Discussion Assignment (post, comment, and rate in the Discussion Forum)
- Complete and submit the Written Assignment
- Make entries to the Learning Journal
- Take and submit the Self-Quiz
Unit 2: Big Data Tools, Techniques, and Systems
- Peer assess Unit 1 Written Assignment
- Read the Learning Guide and Reading Assignments
- Participate in the Discussion Assignment (post, comment, and rate in the Discussion Forum)
- Complete and submit the Written Assignment
- Make entries to the Learning Journal
- Take the Self-Quiz
Unit 3: Analytical Theories and Methods
- Peer assess Unit 2 Written Assignment
- Read the Learning Guide and Reading Assignments
- Participate in the Discussion Assignment (post, comment, and rate in the Discussion Forum)
- Make entries to the Learning Journal
- Take and submit the Self-Quiz
- Take and submit the Graded Quiz
Unit 4: Querying Big Data
- Read the Learning Guide and Reading Assignments
- Participate in the Discussion Assignment (post, comment, and rate in the Discussion Forum)
- Complete and submit the Written Assignment
- Make entries to the Learning Journal
- Take and submit the Self-Quiz
Unit 5: Big data and privacy
- Peer assess Unit 4 Written Assignment
- Read the Learning Guide and Reading Assignments
- Participate in the Discussion Assignment (post, comment, and rate in the Discussion Forum)
- Complete and submit the Written Assignment
- Make entries to the Learning Journal
- Take and submit the Self-Quiz
Unit 6: Using big data in business
- Peer assess Unit 5 Written Assignment
- Read the Learning Guide and Reading Assignments
- Participate in the Discussion Assignment (post, comment, and rate in the Discussion Forum)
- Make entries to the Learning Journal
- Take and submit the Self-Quiz
- Take the Graded Quiz
Unit 7: Trends in Big data
- Peer assess Unit 6 Written Assignment
- Read the Learning Guide and Reading Assignments
- Participate in the Discussion Assignment (post, comment, and rate in the Discussion Forum)
- Complete and submit the Written Assignment
- Make entries to the Learning Journal
- Take and submit the Self-Quiz
Unit 8: Future of Big Data
- Peer assess Unit 7 Written Assignment
- Read the Learning Guide and Reading Assignments
- Participate in the Discussion Assignment (post, comment, and rate in the Discussion Forum)
- Make entries to the Learning Journal
- Take and submit the Self-Quiz
- Complete and submit the anonymous Course Evaluation
- Read the Unit 9 Learning Guide carefully for instructions on the Final Exam
- Take the Review Quiz
Unit 9: Course Review and Final Exam
- Read the Learning Guide and take the Review Quiz, if you haven't already done so
- Prepare for, take, and submit the Final Exam
- The Final Exam will take place during the Thursday and Sunday of Week/Unit 9 (UoPeople time); exact dates, times, and other details will be provided accordingly by your instructor
Course Requirements:
Discussion Assignments & Response Posts/Ratings
Some units in this course require that you complete a Discussion Assignment. You are required to develop and post a substantive response to
the Discussion Assignment in the Discussion Forum. A substantive response is one that fully answers the question that has been posed by the instructor. In addition, you must extend the discussion by responding to at least three (3) of your peers’
postings in the Discussion Forum and by rating their posts. Instructions for proper posting and rating (out of a 10 point scale) are provided inside the Discussion Forum for each week. Discussion Forums are only active for each current and relevant
learning week, so it is not possible to contribute to the forum once the learning week has come to an end. Failure to participate in the Discussion Assignment by posting in the Discussion Forum and responding to peers as required may result in failure
of the course.
Written Assignments & Assessment Forms
Some units in this course require that you complete a Written Assignment. You are required to submit your assignments by the indicated deadlines and,
in addition, to peer assess three (3) of your classmates’ assignments according to the instructions found in the Assessment Form, which is provided to you during the following week. During this peer assessment period, you are expected to provide details
in the feedback section of the Assessment Form, indicating why you awarded the grade that you did to your peer. Please note that each assignment grade is comprised of a combination of your submission (90%) and your peer assessments (10%). Failure
to submit Written Assignments and/or Assessment Forms may result in failure of the course.
Learning Journals
Your instructor may choose to assign specific topics and/or relevant questions as a weekly Learning Journal entry for you to complete, but you are still encouraged to also use
it to document your activities, record questions/problems you may have encountered, reflect on the learning process, and draft answers for other course assignments. The Learning Journal must be updated on a weekly basis, because its entries will be
assessed by your instructor directly as a part of your final grade. The Learning Journal will only be seen by your instructor.
Quizzes
This course will contain three types of quizzes – the Self-Quiz, the Graded Quiz, and the Review Quiz. These quizzes may contain multiple choice, true/false, or short answer questions.
The results of the Self-Quiz will not count towards your final grade. However, it is highly recommended that you complete the Self-Quiz to ensure that you have adequately understood the course materials. Along with the Reading Assignments, the results
of the Self-Quiz should be used as part of an iterative learning process, to thoroughly cover and test your understanding of course material. You should use the results of your Self-Quiz as a guide to go back and review relevant sections of the Reading
Assignments. Likewise, the Review Quiz will not count towards your final grade, but should also be used to assist you in a comprehensive review and full understanding of all course material, in preparation for your Final Exam. Lastly, the results
of the Graded Quiz will count towards your final grade. Specific instructions on the format and content of the Graded Quiz will be provided by your instructor.
Final Exam
The Final Exam will take place during the Thursday and Sunday of Week/Unit 9, following the completion of eight units of work. The format of the
Final Exam is similar to that of the quizzes, and may contain a combination of different question types. You will have one attempt to take the exam, and it will be graded electronically. Specific instructions on how to prepare for and take the exam
will be provided during Week/Unit 8.
Course Forum
The Course Forum is the place to raise issues and questions relating to the course. It is regularly monitored by the instructors, and is a good place to meet fellow students taking the same course. While it is not required to participate in the Course
Forum, it is highly recommended.
Course Policies:
Grading Components and Weights
Each graded component of the course will contribute some percentage to the final grading scale, as indicated
here:
| Discussion Assignments | 15% |
| Written Assignments | 15% |
| Learning Journals | 20% |
| Two Graded Quizzes | 20% (10%each) |
| Final Exam | 30% |
| TOTAL | 100% |
Grading Scale
This course will follow the standard 100-point grading scale defined by the University of the People, as indicated here:
| Letter Grade |
Grade Scale | Grade Points |
| A+ | 98-100 | 4.00 |
| A | 93-97 | 4.00 |
| A- | 90-92 | 3.67 |
| B+ | 88-89 | 3.33 |
| B | 83-87 | 3.00 |
| B- | 80-82 | 2.67 |
| C+ | 78-79 | 2.33 |
| C | 73-77 | 2.00 |
| C- | 70-72 | 1.67 |
| D+ | 68-69 | 1.33 |
| D | 63-67 | 1.00 |
| D- | 60-62 | 0.67 |
| F | Under 60 | 0.00 |
Grade Appeal
If you believe that the final grade you received for a course is erroneous, unjust, or unfair, please contact your course instructor. This must be done within seven days of the
posted final grade. For more information on this topic, please review the Grade Appeal Procedure in the University Catalog.
Participation
Non-participation is characterized by lack of any assignment submissions, inadequate contributions to the Discussion Forums, and/or lack of peer feedback to Discussion/Written Assignments.
Also, please note the following important points about course participation:
- Assignments must be submitted on or before the specified deadline. A course timeline is provided in the course schedule, and the instructor will specify deadlines for each assignment.
- Any student showing non-participation for two weeks (consecutive or non-consecutive) is likely to automatically fail the course.
- Occasionally there may be a legitimate reason for submitting an assignment late. Most of the time, late assignments will not be accepted and there will be no make-up assignments.
- All students are obligated to inform their instructor in advance of any known absences which may result in their non-participation.
Academic Honesty and Integrity
When you submit any work that requires research and writing, it is essential to cite and reference all source material. Failure to properly acknowledge your sources
is known as “plagiarism” – which is effectively passing off an individual’s words or ideas as your own. University of the People adheres to a strict policy of academic honesty and integrity. Failure to comply with these guidelines may result in sanctions
by the University, including dismissal from the University or course failure. For more information on this topic, please review the Academic Integrity Policy in the University Catalog.
Any materials cited in this course should be referenced using the style guidelines established by the American Psychological Association (APA). The APA format is widely used in colleges and universities across the world and is one of several style and citation formats required for publication in professional and academic journals.
Refer to the UoPeople APA Tutorials in the LRC for help with APA citations.
Code of Conduct
University of the People expects that students conduct themselves in a respectful, collaborative, and honest manner at all times. Harassment, threatening behavior, or deliberate
embarrassment of others will not be permitted. Any conduct that interferes with the quality of the educational experience is not allowed and may result in disciplinary action, such as course failure, probation, suspension, or dismissal. For more information
on this topic, please review the Code of Conduct Policy in the University Catalog.
Submitting Assignments
Please note that accepted formats for assignments are Microsoft compatible format, PDF, or any other file format that is clearly specified in the course and activity instructions. These files should not be password-protected. Additionally, unless otherwise stated in assignment instructions, screenshots of computer coding, mathematical formulas or images with sentence structures (typed or in handwriting) are not allowed when you submit your assignments in this course.