Software Engineering Concentration Areas (tracks)
The world is growing at an exponential rate and so is the size of the data collected across the globe. Current and future sources of data are devices which utilize the Internet of Things (IoT) technology in addition to social networks and business applications. Big data infrastructure and analytics are emerging as key concepts to sorting, managing analyzing this massive amount of generated data from connected objects and applications which helps to take the initiative to improve decision making. Thus, data is becoming more meaningful and contextually relevant, breaking new grounds for new computing concepts such as Machine Learning (ML) and Artificial Intelligence (AI). These concepts will introduce a new approach to shift the traditional computing concepts related to data from just collecting structured data to understanding it, to turning this massive amount of data into knowledge, conclusions, and intelligent actions.
In this track, students will be able to study new emerging technologies in the area of Artificial Intelligence and Big Data. Students enrolled in the Software Engineering program are eligible to register in this track.
Game Development and Digital Media Track Course Requirements (12 CRHs):
Core courses
- SE 461 – Game Engine Architecture and Implementation (Prerequisites: SE328)
- SE 462 – Fundamentals of Game Design (Prerequisite: SE 310)
- SE 463 – Game Mechanics, Prototyping, and Production (Prerequisite: SE 412)
- SE 464 – Innovative Topics in Immersive Game Development (Prerequisite: SE 324)
Cybersecurity Track Course Requirements (15 CRHs):
Core courses
- SE 330 – Introduction to Cybersecurity (Prerequisite(s): EE 305)
- SE 450 – Cryptography and Data Privacy (Prerequisite(s): STA 212, SE 330)
- SE 452 – Network Security (Prerequisite(s): EE 305, SE 330)
- SE 454 – Ethical Hacking and Systems Defense (Prerequisite(s): SE 330, SE 452)
Elective courses (Select 1)
- SE 435 - Undergraduate Research (Prerequisite(s): SE 310, SE 322 or SE 330, SE 324, SE 328 - Min GPA 3.0)
- SE 440 - Special Topics in Software Engineering (Prerequisite(s): SE 324)
- SE 443 – Cloud Computing for Software Engineers (Prerequisite(s): SE 324, EE 305)
- SE 444 – Artificial Intelligence (Prerequisite(s): SE 214, SE 324)
- SE 445 – Information and Software Security (Pre-requisite: STA 212, SE 324)
- SE 446 – Introduction to Big Data (Prerequisite(s): SE 312, SE 314, SE 322)
- SE 447 – Introduction to Machine Learning (Prerequisite(s): SE 312, SE 314, SE322)
- SE 448 – Blockchain Development (Prerequisite(s): SE 324)
- SE 451 – Secure Software Engineering (Prerequisite(s): SE 310, SE 330)
- SE 453 – Security Risk Management & Control (Prerequisite(s): SE 330)
AI and Big Data Track Course Requirements (15 CRHs):
Core courses
- SE 322 – Internet of Things Application Development (Prerequisite(s): SE 100, EE 305)
- SE 444 – Artificial Intelligence (Prerequisite(s): SE 214, SE 324)
- SE 446 – Introduction to Big Data (Prerequisite(s): SE 312, SE 314, SE 322)
- SE 447 – Introduction to Machine Learning (Prerequisite(s): SE 312, SE 314, SE 322)
Elective courses (Select 1)
- SE 435 - Undergraduate Research (Prerequisite(s): SE 310, SE 322 or SE 330, SE 324, SE 328 - Min GPA 3.0)
- SE 440 - Special Topics in Software Engineering (Prerequisite(s): SE 324)
- SE 443 – Cloud Computing for Software Engineers (Prerequisite(s): SE 324, EE 305)
- SE 448 – Blockchain Development (Prerequisite(s): SE 324)
- SE 449 – Data Analytics (Pre-requisite(s): SE 312, SE 314)
- SE 450 – Cryptography and Data Privacy (Prerequisite(s): STA 212, SE 330)
- SE 451 – Secure Software Engineering (Prerequisite(s): SE 310, SE 330)
- SE 452 – Network Security (Prerequisite(s): EE 305, SE 330)
- SE 453 – Security Risk Management & Control (Prerequisite(s): SE 330)
- SE 454 – Ethical Hacking and Systems Defense (Prerequisite(s): SE 330, SE 452)
Minor in AI for NON-SE students (15 CRHs):
Pre-requisites
- SE 120 and SE 120 L - Object Oriented Programming and Lab
- SE 214 and SE 214L - Algorithms and Data Structures and Lab
- SE 312 and SE 312 L - Database Management System and Lab
Core courses (all three required)
- SE 444 – Artificial Intelligence (Prerequisite(s): SE 214, SE 324)
- SE 446 – Introduction to Big Data (Prerequisite(s): SE 312, SE 314, SE 322)
- SE 447 – Introduction to Machine Learning (Prerequisite(s): SE 312, SE 314, SE 322)
Electives (select 2)
- SE 435 - Undergraduate Research (Prerequisite(s): SE 310, SE 322 or SE 330, SE 324, SE 328 - Min GPA 3.0)
- SE 440 - Special Topics in Software Engineering (Prerequisite(s): SE 324)
- SE 443 – Cloud Computing for Software Engineers (Prerequisite(s): SE 324, EE 305)
- SE 448 – Blockchain Development (Prerequisite(s): SE 324)
- SE 449 – Data Analytics (Pre-requisite(s): SE 312, SE 314)
Minor in Cybersecurity for NON-SE students (15 CRHs):
Pre-requisites
- SE 120 and SE 120 L - Object Oriented Programming and Lab
- SE 214 and SE 214 L - Algorithms and Data Structures and Lab
- EE 305 and EE 305 L - Computer Networks and Lab
- SE 314 and SE 314 L - Operating Systems and Lab
Core courses (all four required)
- SE 330 – Introduction to Cybersecurity (Prerequisite(s): EE 305)
- SE 450 – Cryptography and Data Privacy (Prerequisite(s): STA 212, SE 330)
- SE 452 – Network Security (Prerequisite(s): EE 305, SE 330)
- SE 454 – Ethical Hacking and Systems Defense (Prerequisite(s): SE 330, SE 452)
Electives (select 1)
- SE 435 - Undergraduate Research (Prerequisite(s): SE 310, SE 322 or SE 330, SE 324, SE 328 - Min GPA 3.0)
- SE 440 - Special Topics in Software Engineering (Prerequisite(s): SE 324)
- SE 445 – Information and Software Security (Pre-requisite: STA 212, SE 324)
- SE 451 – Secure Software Engineering (Prerequisite(s): SE 310, SE 330)
- SE 453 – Security Risk Management & Control (Prerequisite(s): SE 330)
