Page 433 - Undergraduate Catalog 2024-25

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PHY 201L - Physics and various types of analytics starting and governance. The course covers
Engineering Application II Lab with basic univariate descriptive basic Artificial Intelligence concepts
analytics and moving through and terminologies, applications,
Credit Hour: 1 multivariate until we reach predictive tools, and performance evaluation in
Prerequisite: PHY 102 analytics. The course is designed an accessible way to a wide range of
Co-requisite: PHY 201 in a way that balances between audiences. Students are introduced
This course is designed to help theory and practice. Throughout to supervised learning including
students develop the ability to the course the students will follow classification and regression, deep
perform scientific experiments and the data-driven approach to solve learning, unsupervised learning,
to enhance their understanding of real-life problems through a series and reinforcement learning. They
theoretical material presented in of practical labs and class activities. are also trained on using simple
Phy201 (Electricity and Magnetism) They will learn how to design yet powerful Artificial Intelligence
by performing landmark experiments and implement introductory to tools to empower their creativity
with emphasis on the presentation intermediate data-driven decision- and innovation in problem solving,
and interpretation of experimental support systems using Microsoft Artificial Intelligence strategy
data. Excel. The course concludes by design, process automation, and
introducing the students to a variety cost reduction, and thus add value
CSC 201 - Computer of special data analytics applications to their future employers. This is
Programming I in engineering, health, business, and done through a practical course
the web emphasizing social, security, component designed to allow
Credit Hour: 3 and economic dimensions. students to build simple data-driven
Prerequisite: MTT 101 or higher Artificial Intelligence using Excel.
GEN 300 - Numerical Methods The data used in these laboratories
The main objective of this course is to
provide students with the logic and Credit Hour: 3 is collected from different domains
such as health, environmental
tools required to develop scientific Prerequisite: MTT 205 + CSC 201
software programs in MATLAB. A course that deals with the science, business, and engineering.
MATLAB is a matrix based language application of numerical methods in COE 202 - Engineering Ethics,
that is commonly used for scientific solving civil engineering problems. Economy and Law
and engineering computing. MATLAB Topics covered include: mathematical
has a rich set of toolboxes for a wide modeling and error analysis, solution Credit Hour: 3
range of applications in science of linear and nonlinear equations, Prerequisite: ENG 200 + MTT 102

and engineering. The material for numerical differentiation and
this course includes: Introduction integration, optimization, curve- This course integrates two
to MATLAB Programming concepts, fitting, and solution of ordinary interrelated general engineering
Control Structures (loops and differential equations. The course disciplines, namely: ethics and
conditions), Functions, Arrays and also provides students with a hands- economy. In the first part of the
Object-Oriented programming. on introduction to mathematical course, the students are introduced
COE102 - Introductory Big Data programming using MATLAB. to ethical issues that practicing
engineers may face in their
Analysis COE 101 - Introductory Artificial professional practice. This includes a
Credit Hour: 3 Intelligence discussion of the code of ethics and
Prerequisite: STT 100 Credit Hour: 3 responsibility of engineers, ethical
theories, ethical problems-solving
This course provides a general Prerequisite: STT100 methods, and case studies based

introduction to Data Analytics. on real events that illustrate the
It provides an essential guide to This course introduces students to problems faced by engineers. The
understand and use data analytics broad topics in artificial intelligence case studies also show the effects of
in real-life applications without the and machine learning without engineering decisions on society.
need for any previous familiarity requiring them to have a computing
programming. The course starts or mathematical background. The second part of the course gives
by introducing the main concepts Students will have a closer look at the students a working knowledge
of Data Analytics to provide a solid booming field of Artificial Intelligence on making economic comparison
understanding of the field, its and develop insights on how it drives of investment alternatives in
subfields, and major application value for the society in virtually engineering project environment.
areas. Then, we move through the all sectors including business, This includes description of the
healthcare, education, engineering, interest and time value of money

Abu Dhabi University | Undergraduate Catalog 2024 - 2025