Course Catalog Description
This course covers database design and applications of database management systems in software development.
It includes relational database management systems (RDBMS) and SQL, and how databases are accessed in computer programs.
It also covers different data formats, i.e. XML, JSON, etc. This course will also introduce to students the application
of NoSQL systems. It will explore topics related to data analysis.
Prerequisites
COP 3530 for level Undergraduate with minimum grade of C
Required Material
Textbook:
Database System Concepts 7th Edition by Abraham Silberschatz, ISBN: 9780078022159
Learning Outcomes
Upon successful completion of this course, the student will be able to:
- Understand the principles behind the relational data model and basic information storage & retrieval (IS&R) concepts.
- Understand the principles of RDBMS including normalization, relational data models, and ACID.
- Create data flows to extract and load information from text data sources onto a database.
- Be able to write and perform DDL & DML SQL Queries using both programing interfaces & database interfaces directly to support searching & retrieving information needs.
- Build backend systems which support the building of software and information applications.
- Understand the basic principles of Big Data and other data systems (data frames, SaaS, Warehouses) and the differences between them and relational databases.
Instructional Methods
This is a face-to-face course with lectures, instructor led programming examples, and in-class labs.
Attendance
Attendance is mandatory for all classes. Attendance will be taken and will count towards participation credit.
Students should notify me at least 48 hours in advance of intent to miss a class to arrange alternate schedules
for in-class assignments.
Communication:
All course related communication should be via Canvas message. Each student is responsible for checking his/her
FGCU email at least once a day. The instructor will respond to your emails within 24 hours except
weekends and holidays.
Topics / Tentative Schedule
- Intro to Relational Model
- Intro to SQL
- Intermediate SQL
- Exam 1
- Database Design Using the E-R Model
- Relational Database Design
- Advanced SQL
- Intro to Python w/SQL
- Python UI Programming
- Database Application Development
- Exam 2
- Group Project Demonstrations
Assessment
There is no grace period for late submission of assignments. All assignments with due dates and times will be posted on Canvas. Alternate schedules can be arranged ahead of time with instructor approval.
Working Independently:
Students are to work independently on all non-group assignments. It is cheating to see other
classmate's work or let other classmates see yours. This does not mean you cannot assist or discuss assignments with your classmates.
*** IMPORTANT ***
Student submissions that contain work from another student or source will receive
a zero for that assignment. A second occurrence will result in failing the class, and the academic
sanction will be reported to the Dean of Students.
Generative AI Use Policy:
Use of Generative AI tools (such as ChatGPT, Copilot, Gemini, etc.) is permitted in this course,
but only within strict boundaries that support learning without compromising academic integrity
or the intent of the assignments.
Permitted Use:
-
Generative AI may be used to assist with understanding a specific concept,
algorithm, or section of provided code.
-
Prompts must be narrowly focused (for example, explaining how an algorithm works or
clarifying what a provided code segment does).
-
You may include code from the textbook, lecture materials, or other sources in a prompt
only for the purpose of understanding it.
-
AI may be used to clarify or reinforce understanding, but not to generate code or
complete any portion of an assignment.
Prohibited Use:
-
Do not prompt with entire assignments, assignment questions, or large portions of an assignment.
-
Do not use AI to generate code that is submitted as part of your work.
-
Do not use AI to debug, improve, or modify code that you are submitting.
Disclosure Requirement:
-
You must submit a copy of all AI prompts and corresponding responses
along with your assignment, including coding assignments.
-
Submissions without accompanying AI usage documentation will be treated as
not using AI.
Violations:
-
First violation: zero on the assignment.
-
Second violation or use of AI beyond what was disclosed may result in a
formal academic integrity referral.
This policy is intended to support learning while ensuring that submitted work reflects your
own understanding and effort.
Assignments (45%):
Individual problems and small programs worked outside of class.
Exams (30%):
Written exams taken in class.
Group Project (15%):
Group project is a small database application with backend database and frontend user interface.
Participation (10%):
In class quizzes and labs, attendance, and overall participation.
University Resources and Syllabus Policies