Bachelor of Software Engineering – AI & Big Data Track

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.

Track Course Requirements (15 CRHs):

The following are the core courses required in the AI and Big Data track:

• 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 447 – Introduction to Machine Learning (Prerequisite(s): SE 312, SE 314)

One additional course may be taken from the following list of track electives:

• 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)

Bachelor of Software Engineering – Cybersecurity Track

Security is a forefront concern for software vendors and customers and an indispensable quality attribute of software given the high level of interconnectivity of systems running critical software functions and storing confidential data. There is a multitude of attacks that attempt to exploit software systems to gain illegitimate access to functionalities and data. Despite the continuous exposure to threat, software systems cannot simply seize operations as a countermeasure and they are expected to be available and deliver business value to its stakeholders reliably. The Software Engineering Department, part of the College of Engineering at Alfaisal University has approved a cybersecurity track. This track will equip students with the necessary skills and respond to challenges in cybersecurity, data privacy, network security, socio-technical issues in addition to learning how to develop secure systems by practicing proper secure software engineering principles. Students in the Bachelor of Software Engineering program at Alfaisal University are eligible to opt for this track

Track Course Requirements (15 CRHs):

The following are the core courses required in the Cybersecurity track:

• 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)

One additional course may be taken from the following list of track electives:

• 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 447 – Introduction to Machine Learning (Prerequisite(s): SE 312, SE 314)
• 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)