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Bachelor of Computer Science (Artificial Intelligence and Big Data)

Degree Summary

Program Outcomes

Program Structure

Faculty

Accreditation

Admission Requirements

Duration

3 Years Bachelor Degree
(24 subjects)

4 Years Bachelor Degree
with Integrated Freshman Year (32 subjects)

Classes commence

September (Autumn)

January (Winter)

April (Spring)

Yearly Fees*

AED 60,429 / USD 16,466
*VAT 5% inclusive
Note: Yearly fees will vary depending
on number of subjects enrolled in

In an era defined by digital transformation, Artificial Intelligence (AI) and Big Data stand as the twin pillars driving the fourth industrial revolution. These technologies are reshaping industries, revolutionizing businesses, and solving some of the world's most pressing challenges. From enhancing productivity and efficiency to unlocking groundbreaking innovations, AI and Big Data are transforming how we work, live, and connect.

The AI and Big Data major at the University of Wollongong in Dubai (UOWD) is designed to meet the surging demand for professionals with advanced AI and data analytics skills. This program bridges the gap between technology and application, equipping students with the expertise needed to thrive in a digitally transformed world. By synthesizing cutting-edge concepts from AI and Big Data, students will learn to harness the power of these complementary disciplines to develop innovative solutions for global challenges across industries such as healthcare, transportation, security, and commerce.

AI empowers machines to learn from past experiences, enabling business automation, reducing costs, improving operational efficiency, and enhancing customer experiences. Simultaneously, Big Data addresses the challenge of managing vast and complex datasets, providing actionable insights for strategic decision-making. Together, these fields form a powerful synergy, enabling students to tackle complex problems through data-driven and AI-enabled solutions.

This program offers a future-focused curriculum designed to develop creative, analytical minds capable of unlocking the full potential of AI and Big Data. Whether it's designing predictive models, implementing intelligent algorithms, or visualizing massive datasets, students will gain hands-on experience with the tools and techniques shaping tomorrow's innovations.

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Program Selection Guide

UOWD's Bachelor of Computer Science (Big Data)

Entry Requirements

Students who have excelled academically at school and meet our advance entry requirements can finish their bachelor's degree in three years, instead of the existing four-year programs. Any prospective student that does not directly qualify for an advance entry three-year program, is still able to enrol in any of our bachelor’s degree, through a one-year Freshman Year.

Admission requirements for UOWD depends on the type of high school curriculum you have followed. The requirements based on the most common high school curricula are listed below:

School System	Bachelor Degree Advanced Entry (3 Years)	Bachelor Degree Direct Entry (4 Years)
UAE Al-Thanawiyya Al-Aama	N/A	Elite or Advanced Track 70%, General Track 75%
Arab Countries Al-Thanawiyyah Al-Aama	N/A	70%
American High School Diploma	Overall average grade of C (70% or 2.5/4.0) + SAT 1100	Overall average grade of C (70% or 2.5/4.0)
Bangladesh HSC	GPA of 4.0 / 5.0	GPA of 3.0 / 5.0
Brazil Brazil Higher Secondary Certificate	N/A	60%
British GCE Curriculum	Minimum 5 IGCSE/GCSE subjects – Grade D and Minimum of 3 A level subjects – Grade CCD Completion of Year 13	Minimum 5 IGCSE/GCSE subjects – Grade D and 2 AS or 1 A level subject (s) – Grade D Completion of Year 13
Chinese Senior High School	80%	60%
Colombia Título de Bachiller Académico	N/A	3 out of 5 or 6 out of 10
International Baccalaureate Diploma	25 Points	21 Points
India CBSE & ICSE, Grade 12	65%	50%
Iran Pre-University Certificate	14	11
Japan Upper Secondary School Diploma	3.8 out of 5	2.5 out of 5
Kenya	60	31
Mexico	N/A	6 out of 10
Nepal School Leaving Certificate Examination	3 out of 4	2.3 out of 4
Nigeria WAEC & NECO	N/A	Minimum of 7 subjects with no more than 1 “Pass”
CIS Countries Attestat	N/A	Average 3/5
South Korea CSAT	77.5%	70%

Notes:

All students applying for these programs are required to have an EmSAT in Mathematics with a score of 700 or equivalent.
Students with qualifications from other curriculum should contact the Student Recruitment and Admissions department at UOWD to determine their eligibility.
All students applying from non UAE MoE curriculum must provide an equivalency of their Secondary School Certificate from the Ministry of Education, UAE; stating the completion of Grade 12.
A student who does not satisfy the criteria for Equivalency of Secondary School Certificate, may be subject to conditional admission, based on receiving a Letter of No Objection to Conditional Admission issued by the Ministry.

English Language Requirements

At UOWD, all classes are taught in English and in order to enrol in a bachelor’s degree you will need to submit one of the following certificate of English language proficiency:

English Language Testing	Bachelor Degree Advance Entry (3 Years)*	Bachelor Degree Direct Entry (4 Years)**
IELTS Academic	Overall IELTS (Academic) score of 6.0 & Minimum score of 6.0 in Reading & Writing Minimum score of 5.0 inListening & Speaking	Overall IELTS (Academic) score of 5.0 & Minimum score of 5.0 in Reading & Writing
TOEFL Internet-based	79 with not less than 20 in Writing, 18 in Reading, 17 in Listening, 16 in Speaking	61
TOEFL Computer based	213 with a 4.0 TWE/Essay Writing	173
TOEFL*** International paper based	550 with a 4.0 TWE/Essay Writing	500
EmSAT Achieve – English	1400	1100

Notes:

* Students with a minimum overall score of 6.0 in academic IELTS and no more than one score (either in reading or writing) between 5.0 and 6.0 will be given the opportunity to complete a remedial subject in the first semester as a condition for progression.

** Students with a minimum overall score of 6.0 in academic IELTS (or equivalent) and a minimum score of 6.0 in reading and writing(or equivalent) are eligible for advanced standing for English Language subjects.

*** Students admitted under this criterion must complete the test at AMIDEAST.

Credit for Prior Learning

If you are seeking advanced standing status, please submit an official academic transcript showing all courses studied and the grades achieved, syllabus details (including information on course content) for the courses you have completed and an explanation of the grading system.

To make an application for your chosen program, complete the online application form and submit it along with all your supporting documentation (see below) prior to the application deadline.

Late applications may be accepted subject to the availability of places but applicants are encouraged to apply as early as possible.

Supporting Documentation

Please ensure that all these documents accompany your application for admission form submittal:

An original or certified copy of your secondary school records
A Statement or Certificate of Completion of secondary school
Proof of your English language proficiency

(Note: Results from IELTS & TOEFL tests may be sent to the University directly from the IELTS or TOEFL testing centres quoting the UOWD institution code IELTS: AE109 / TOEFL: 7907)

UAE ID (if applying from within the UAE)
A copy of your passport (and Residence Visa, if resident in the UAE).

Additionally, if you are seeking advance standing in your chosen program:

Certified copies of official academic transcripts showing all courses studied and grades obtained, syllabus details (including information on course content) of the courses you successfully completed and an explanation of the grading system.

Applicants who completed secondary schooling within the UAE

All applicants for admission who have completed the Thanaweya Al-Amma must get their certificates attested by the UAE Ministry of Education.

Applicants from all other curriculum, who have completed their high school from UAE, are required to obtain equivalency of their high school qualifications from the UAE Ministry of Education.

In these circumstances, you will be provisionally admitted to the University and permitted to commence the first semester of study, subject to you obtaining the required attestation/equivalency.

Applicants who completed secondary schooling outside the UAE

You must have your secondary school records and Certificates of Completion certified by:

The issuing Board of Secondary Education OR a recognised authority for secondary education
The Ministry of Foreign Affairs in the host country
The UAE Embassy in that host country OR the Embassy of the host country in UAE must attest the authenticity of the documents and attestations and the UAE ministry of Foreign Affairs

In special cases where complying with conditions (2) and (3) are not feasible, the certificates may be verified against originals by Embassies in the UAE and the UAE Ministry of Foreign Affairs.

In these circumstances, you will be provisionally admitted to the University and permitted to commence the first semester of study.

If you are unable to secure the attestations as outlined above you will be asked to sign a “Consent to Provide Documents” form agreeing to secure the equivalency. You will be permitted to commence your studies at UOWD, but will be given a maximum of one semester to obtain the attested certificate(s). UOWD reserves the right to take appropriate action against any applicant who cannot secure the appropriate documentation in this time, which may result in the termination of the student’s enrolment at UOWD.

For more information or assistance on attesting documents from outside UAE, click here.

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Program Structure

To earn the Bachelor of Computer Science (AI and Big Data) degree at UOWD, a student must successfully complete a total of 144 credit points (CP). This includes 14 core subjects (84 CP), 5 specialized subjects in Data Science (30 CP), 2 elective subjects (12 CP) chosen from the approved list, 1 general education subject from the Emirati Studies category (6 CP), and a capstone project in AI & Big Data (12 CP).

Core Subjects

The broad aim of this subject is to develop in students an understanding of the fundamental principles of programming. The subject focuses on the object-oriented view of problem analysis and solving. It enables students to develop skills in the design and implementation of well-structured programs in a range of domains.

This subject provides an introduction to different techniques and technologies for understanding and specifying what a computer based information system should accomplish. It examines the complementary roles of systems analysts, clients and users in a system development life cycle. Students will learn different fact-finding techniques to elicit system requirements and how to develop business models, data and process models, and object models representing a system. Students will also make use of a Computer Aided Software Engineering (CASE) tool to build those models that capture the specifications of a system.

This subject introduces the analysis of problems and the strategies used to manage them, primarily in the context of computing. Problem classification is introduced, as are formal and informal approaches to problem solving. The importance of method and method classification for problem solving strategies is motivated, and the need to compare and analyse strategies is justified. Introductory tools for the analysis of strategies are covered. Appropriate representations for problem solving are explored.

The aims of this subject are to consolidate and extend student's knowledge and skills in structured programming and to develop their understanding and practice of object oriented programming. To achieve this aim the subject will provide students with an opportunity to develop further programming skills and good coding style; develop skills in using the object oriented concepts of encapsulation, inheritance, polymorphism, access control, overloading and messaging; develop and display competency in the design and implementation of object oriented programs to solve business problems.

The subject investigates three major areas of modern data management systems: data modelling, data processing, and data security. The goal of the subject is to learn the fundamental concepts in data management including conceptual modelling, the relational data model, processing of relational data with Structured Query Language (SQL), enforcing the concepts of data confidentiality, integrity, and availability data management systems. The subject develops the skills in the design, implementation, processing, and security of data management systems. The subject covers the following topics in data security: discretionary access control, user management, enforcing data security and integrity. The subject also explains the important ethical issues associated with responsible disclosure, responsibility, liability, security weaknesses, and privacy in data management systems.

This subject introduces students to the fundamentals of data communications and computer networks. Topics covered include: different types of data and the history of data communications; signals; modulation and multiplexing, switching and routing, network architectures: LANs, WANs and the Internet; Internet services and protocols; and emerging topics. The subject explains computer networking models that interconnect diverse communication systems, including the OSI reference model and the TCP/IP protocol Suite.

This subject introduces students to fundamental web technologies that underlie the World Wide Web and its commercial applications. Topics include an overview of internet communications, an introduction to the web-browser/web-server client-server systems, HTML5/CSS/XHTML/XML markup languages, web forms and client side scripting. Students will build working web-sites with dynamic content. The subject explains the differences between client-side and server-side Web development, and demonstrates how to build simple applications using scripting and other tools. The subject also covers current Web standards and future W3C recommendations.

General Elective Subject

Students are required to choose an additional ONE elective subject, each worth 6 credit points, from the school's approved list.

Core Subjects

Approaches to analysing algorithm complexity and implementation efficiency will be introduced; and used to motivate the development of appropriate abstract data types. Students will be taught to recognise the role of abstract data types and algorithms in solving real-world problems; and given the opportunity to implement solutions to such problems.

The primary aim of this subject is to acquaint students with the methodologies and processes associated with the task of managing information technology and software development projects. Topics may include: stakeholder and impact analysis, setting project objectives and conflict resolution, project planning and the selection of appropriate project approaches, software project effort estimation, cost-benefit analysis, activity planning and scheduling, risk management, contract management, quality assurance, professional and ethical responsibilities, and case studies.

The subject provides students with an understanding of Human Computer Interaction (HCI) principles and practices, and how to apply them in the context of developing usable interactive computer applications and systems. The subject also emphasises the importance of taking into account contextual, organisational, and social factors in the design of computer systems. Students will be taken through the analysis, design, development, and evaluation of user interfaces. They will acquire hands-on design skills through an interaction design project. The subject will cover topics including user-centred design, the development process, prototyping, usability testing, measuring and evaluating the user experience and accessibility.

The subject presents advanced topics in the modern relational database technology and it introduces the new non-relational (NoSQL) database technologies. The relational database technology component of the subject includes database normalization, introduction to indexing in relational database systems, programming of relational database server with stored PL/SQL procedures, functions, and triggers, concurrency control and database recovery techniques, design and programming of distributed database systems. The non-relational (NoSQL) database technology component of the subject includes a review of non-relational data models such as the key-value data model, document-oriented model, column-family stores, and graph data model. The non-relational component of the subject presents the new approaches to database design, data distribution, consistency preserving, and transaction processing in distributed and clustered database systems. Programming of NoSQL database server includes the new data definition and data manipulation languages, a new query language, indexing, design and implementation of replication and sharing.

Advanced Programming
This subject develops a thorough understanding of advanced programming features, and how to implement them in modern C++. It consists of three primary components, namely procedural programming, object-based/object-oriented programming, and generic programming. In addition to the core of each of those components, this subject addresses topics including resource management tied to RAII, in particular the management of dynamic memory; the use of the standard template library; profiling and debugging; programming for efficiency including concepts such as moving; exception handling; C++ RTTI; and recent additions to C++.

Java Programming
This subject develops a thorough understanding of advanced programming features, and how to implement them in modern C++. It consists of three primary components, namely procedural programming, object-based/object-oriented programming, and generic programming. In addition to the core of each of those components, this subject addresses topics including resource management tied to RAII, in particular the management of dynamic memory; the use of the standard template library; profiling and debugging; programming for efficiency including concepts such as moving; exception handling; C++ RTTI; and recent additions to C++.

Major Subjects

The subject considers the problems related to data mining techniques and implementation in Big Data environment. The topics include data pre-processing techniques, pattern, association and correlation discovery, classification and clustering, stream and real-time processing techniques and post-processing techniques like outlier detection, statistical and, proximity, and clustering base approaches. Laboratory classes and hands-on programming exercises related to these topics will provide the students with the abilities to design and implement Big Data algorithms and to use already existing software libraries. The subject also addresses the problems of scalability, selection of appropriate implementation techniques, and performance aspects when mining Big Data.

The subject addresses the problems of managing and processing of extremely large data sets in a single-server centralized computing systems and in multi-server clustered and distributed computing systems. The topics related to processing of large data sets in centralized environments include the techniques based on the classical data warehouse technologies such multidimensional data model, data warehouse architecture, data warehouse design both at conceptual and logical levels, and data warehouse processing with appropriate specialised query operations. The topics related to processing of large data sets in distributed environments include the techniques that can be implemented on the clusters of inexpensive computing nodes using MapReduce programming model. The subject introduces the students to the real time analytical processing of large data sets with analytical cluster-based distributed data processing systems. Discussion and hands on exercises related to these topics will equip students to meet the challenges in Big Data environments and appreciate the added challenges of dealing with unstructured data. Students will be presented with opportunities to do hands-on work with appropriate commercial tools.

Core Subject

The subject introduces to students modern methodologies for software development. Topics may include software development life cycle activities, the role of software process models, different types of evolutionary models, Unified Process and UML, agile principles of software development, Dynamic Systems Development Method (DSDM), Scrum and extreme programming, test driven software development, the Capability Maturity Model Integration (CMMI), software engineering knowledge management, software architecture, and emerging trends in software development processes.

Major Subjects

This subject presents the foundations of artificial intelligence (AI). It introduces the history of AI, its evolution, and the recent development. Also, it presents the representative topics selected from the important areas in the field of AI. For each of these topics, this subject introduces the fundamental concepts, classic methods, and important applications. This subject concludes with a summary of the present of AI and its future trends. By providing the fundamental knowledge of AI, this subject helps students to gain the basic idea of this important field, paving their way to study more advanced AI techniques.

This subject introduces students to the advanced theories, algorithms and applications in the modern development of AI. For each topic covered, its important concepts and principles will be presented to help students gain an essential understanding. Advanced approaches, methods and algorithms will be introduced to show how artificial intelligence is realised. State-of-the-art applications, tools, and platforms will be demonstrated and analysed to connect theories with practices. This subject will equip students with advanced knowledge of modern AI and enhance their skills to appropriately choose and apply AI techniques to resolve practical problems.

This subject is designed to equip the student with an understanding of the fundamental tools required to analyse, design and implement computer vision systems. Topics covered include low-level, mid-level, and high-level vision; image formation; camera model and calibration, stereo vision; edge detection and segmentation; thinning and skeletonising, binary morphological operations; object recognition, image interpretation and scene understanding.

Capstone

This subject is the capstone project for undergraduate students in the School of Computing and Information Technology it aims to provide students with: practical experience in complete systems development. The projects connect groups of students with supervisors and clients that are facing an ICT-based problem for which the students are required to find innovative and creative solutions. Working in groups, students design, implement, and document a system. This involves: project planning and scheduling, seminars and individual presentations, group coordination, research of proposed application domain, use of design methodologies, design documentation, coding, module and system integration, testing, verification, and implementation. Teams will meet weekly with supervisors to discuss progress and problems.

General Elective Subjects

Students are required to choose an additional TWO elective subjects, each worth 6 credit points, from the school's approved list.

This course is focused on learning innovation and entrepreneurship that can be applied to any high-growth enterprise or other organization. The course is composed of three modules:

Module 1: Design Thinking
Module 2: Entrepreneurship
Module 3: Growth and Leadership

* Highly Recommended Elective Subject

Choose One Emarati Studies*

The societies and places in which we live are very complex, and the interactions of individuals, as well as social institutions, have a direct impact on the life path we take. This course provides an engaging and accessible introduction to urban sociology and the study of cities, with particular focus on the experience of the UAE and Dubai. We’ll examine a number of substantive urban topics, including but not limited to the growth of cities and urban spaces in the UAE, sustainable development and practices, and the ‘built’ environment.

This course will introduce Public Health as an interdisciplinary science concerned with topics central to the population of U.A.E and on a wider scale of GCC region with regard to their physical, mental, and social well- being. The course focuses on current pertinent public health problems, assessing causation and examining intervention and management strategies at personal, social, and organizational levels.

This course offers an overview of the UAE’s rapidly emerging significance and its increased roles in global networks of international relations and diplomacy. Within that overview, the course examines the internal dynamics of the UAE, in particular, the priorities that emerge from a specific workforce dependency, a construction and tourism industry that looks ‘East’ as much as it does ‘West’. Thus the new ‘Look East’ policy complements the country’s historical partnership with the Western states. With the expansion of its global ties and relations, the UAE also becomes more sensitive to transnational issues, such as immigration, fluctuations in international markets or terrorism.

This subject aims to provide an understanding of relations and interactions between society and environment, including impact of societies on the Earth and its processes. Topics covered include the agricultural, industrial and urban revolutions; governance of environments; Indigenous land management; climate change; sustainability; and environmental impacts in the context of the Anthropocene.

This course aims to provide students with critical thinking perspectives about the relationship between history, religion and culture, in this case, the formation of Islamic culture(s). A sociological introduction to the study of Islamic culture will introduce students to the emergence of Islam in its 7th century historical context, its relationship to the other monotheistic traditions of the region, its growth into the dominant cultural paradigm of the Near East by the 9th century, alongside its impact and contribution to key fields of medieval science and knowledge. A historical approach will help students acquire familiarity with key Islamic texts, institutions, concepts of authority, traditions of jurisprudence and spirituality, artistic expressions, as well as milestones in Islamic history. The course wraps up with a discussion of issues central to contemporary debates relating to Islamic culture, such as identity, gender, multiculturalism, pluralism, secularism and religiosity.

* Students must complete 6 credit points (cp) of General Education subjects in the area of Emirati Studies as part of the 144 cp.

Note: If you enrolled at the University before Autumn 2024 and have already completed some GED subjects, you may continue with your original study plan to fulfill your graduation requirements. Alternatively, you may choose to follow the new guidelines by completing one GED subject in the Emirati Studies category from the list above and transferring any completed GED subjects to Electives if permitted by your degree plan.

For support and guidance on this option, please consult an officer at the Academic Success Centre or speak with the Academic Advisor in your School.

Program Outcomes

Upon successful completion of this program, a student should be able to:

Apply theoretical basis of computer science to solve a range of practical problems
Design and develop state of the art software solutions for a variety of applications.
Design, develop, and employ effective and efficient approaches and algorithms in solving practical problems.
Manage all aspects of the project including analyses of requirements, design of solutions, selection of appropriate tools for implementation, or integration.
Demonstrate the ability to function effectively as part of a team to accomplish a set of common goals and objectives and efficiently communicate with project stakeholders.
Adopt a professional and ethical approach to decision making and related social responsibilities.
Determine appropriate artificial intelligence and big data analysis techniques for solving real world problems.
Design and implement AI-enabled and data driven solutions using big data and artificial intelligence algorithms and techniques.

These outcomes ensure that graduates are well-equipped with the knowledge, skills, and ethical grounding necessary to lead in the dynamic fields of AI and Big Data. Graduate will be able to pursue careers such as:

AI Specialist
Data Scientist
Big Data Engineer
Machine Learning Engineer
Data Analyst
AI Product Manager
Business Intelligence Analyst
Cybersecurity Analyst

Accreditation and Recognition

All degrees at the University of Wollongong in Dubai are accredited by the Commission for Academic Accreditation (CAA) of the UAE Ministry of Education and are licensed by the Knowledge and Human Development Authority (KHDA). In addition, the degree is quality assured by UOW, which is registered with the Tertiary Education Quality and Standards Agency (TEQSA), the national regulator of the higher education sector in Australia.

Students will be issued a UOW Australia degree upon graduation.

Professional Accreditation

Australian Computer Society (ACS)

ACS promotes quality in ICT-related higher education to meet future industry needs. ACS sets graduate standards, drives improvements and refinements, and gives recognition to quality programs. ACS also ensures that new specialist courses build key skills for critical emerging fields.

Prof May El Barachi

Head of School
School of Computer Science

Dr El Barachi is an Associate Professor at the Faculty of Engineering & Information Sciences and is a next generation networking expert currently teaching the subjects of Information & Communication Security, Distributed Systems & Cloud Computing, as well as Programming in the Bachelor of Computer Science and the Bachelor of Information Technology programs.

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Bachelor of Computer Science (Artificial Intelligence and Big Data)

Degree Summary

Program Outcomes

Program Structure

Faculty

Accreditation

Admission Requirements

Duration

Classes commence

Yearly Fees*

Enquire Now

Program Selection Guide

View Program Structure

Program Structure

Core Subjects

Programming Fundamentals with PythonCSIT110 | 6 cp

System AnalysisCSIT114 | 6 cp

Data Management & SecurityCSIT115 | 6 cp

Object Oriented Design and ProgrammingCSIT121 | 6 cp

Computing and Cyber Security FundamentalsCSIT123 | 6 cp

Networks and CommunicationsCSIT127 | 6 cp

Introduction to Web TechnologyCSIT128 | 6 cp

General Elective Subject

Core Subjects

Algorithms and Data StructuresCSCI203 | 6 cp

IT Project ManagementCSIT214 | 6 cp

Human Computer InteractionCSIT226 | 6 cp

Database SystemsCSIT235 | 6 cp

Advanced Programming | Java ProgrammingCSCI251 | CSCI213 | 6 cp

Mathemathics for ComputingMATH225 | 6 cp

Major Subjects

Big Data Mining Techniques and ImplementationCSCI316 | 6 cp

Big Data ManagementISIT312 | 6 cp

Core Subject

Software Development MethodologiesCSIT314 | 6 cp

Major Subjects

Foundations of Artificial IntelligenceCSCI218 | 6 cp

Modern Artificial IntelligenceCSCI323 | 6 cp

Computer Vision Algorithms and SystemsCSCI435 | 6 cp

Capstone

ProjectCSIT321 | 12 cp

General Elective Subjects

Fundamentals of Innovation and Entrepreneurship*INE 301 | 6 cp

Choose One Emarati Studies*

Urban SociologyURBS103 | 6 cp

Public HealthPUBH115 | 6 cp

UAE and International RelationsIRAE135 | 6 cp

Society and Environment – Resources, Challenges, FuturesGEOG222 | 6 cp

Muslim Societies Across the Ages: Tradition, Secularism & ModernityARTS317 | 6 cp

Program Outcomes

Accreditation and Recognition

Professional Accreditation

Australian Computer Society (ACS)

Prof May El Barachi

Faculty

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