Page 472 - Undergraduate Catalog 2024-25

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CSC 201 - Structured students to build simple data-driven COE 102 - Introductory Big Data
Programming I AI using Excel. The data used in Analytics
these laboratories is collected from
Credit Hours: 3 different domains such as health, Credit Hour: 3
Prerequisite: MTT 102 or MTT 102 environmental science, business, and Prerequisite: STT 100
The main objective of this course is to engineering.
provide students with the logic and COE 202 - Engineering Ethics, This course provides a general
tools required to develop structured Economy and Law introduction to Data Analytics.
software programs in C++. C++ is a It provides an essential guide to
challenging programming language Credit Hour: 3 understanding and using data
that is based on both structured Prerequisite: ENG 200 + MTT 102 analytics in real-life applications
programming and object-oriented without the need for any previous
programming methodologies. This course integrates two familiarity with programming. The
However, this course focuses on interrelated general engineering course starts by introducing the main
structured programming as the main disciplines, namely: ethics and concepts of Data Analytics to provide
learning objective. It also serves as a economy. In the first part of the a solid understanding of the field,
preliminary foundation for learning course, the students are introduced its subfields, and major application
the object-oriented programming to ethical issues that practicing areas. Students will learn the
methodology. engineers may face in their different types of data, data sources
and data uses, and technologies for
professional practice. This includes a Big Data. Then, we move through
COE 101 - Introductory Artificial discussion of the code of ethics and the various types of analytics starting
responsibility of engineers, ethical
Intelligence theories, ethical problems-solving with basic univariate descriptive
analytics and moving through
Credit Hours: 3 methods, and case studies based multivariate until we reach predictive,
Prerequisite: STT 100 on real events that illustrate the model-based analytics. The course
problems faced by engineers. The is designed in a way that balances
This course introduces students to case studies also show the effects of
broad topics in artificial intelligence engineering decisions on society. between theory and practice.
(AI) and machine learning without Throughout the course, the students
requiring them to have a computing The second part of the course gives will follow the data-driven approach
or mathematical background. students a working knowledge to solving real-life problems through
Students will have a closer look on making economic comparison a series of practical labs and class
at the booming field of AI and of investment alternatives in activities. They will learn how to
develop insights on how it drives engineering project environment. explain and identify the elements
value for the society in virtually This includes description of the of introductory to intermediate
all sectors including business, interest and time value of money data-driven systems using Microsoft
healthcare, education, engineering, relationships, methods of comparing Power BI. The course concludes by
and governance. The course covers alternatives using economic concepts introducing the students to a variety
basic AI concepts and terminologies, such as: the rate-of return (ROR), the of special data analytics applications
applications, tools, and performance present worth (PW), the future worth in engineering, health, business, and
evaluation in an accessible way to a (FW), the annual equivalent (AE), the web emphasizing social, security,
wide range of audiences. cost-benefit analysis and breakeven and economic dimensions.
and payback analysis. Other topics
Students are introduced to include replacement analysis,
supervised learning including inflation and depreciation. The course
classification and regression, deep enables students to make suitable
learning, unsupervised learning, and decisions in their professional life
reinforcement learning. They are also when they have to make a decision
trained on using simple yet powerful on ethical and economical basis.
AI tools to empower their creativity
and innovation in problem solving, AI
strategy design, process automation,
and cost reduction, and thus add
value to their future employers. This
is done through a practical course
component designed to allow

Abu Dhabi University | Undergraduate Catalog 2024 - 2025