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(RCNNs) for Stop Sign Detection. include Deep learning, Computer MTT 200 - Calculus II eigenvalues, eigenvectors, and in Physics I course (PHY 102) by
The course has a project. In this Vision, Behavior Cloning, Lane Assist, Bachelor of diagonalizing matrices. performing landmark experiments
project, students work teams using PID Control, and Internet of Things Science in Credit Hours: 3 with emphasis on the presentation
PyCharm, Scikit Libraries, Keras, and (IoT). Students connect theoretical Prerequisite: MTT 102 MTT 205 - Differential Equations and interpretation of experimental
Tensorflow to design a YOLO and concepts learned in the course to Electrical The Calculus II course extends the Credit Hours: 3 data.
RCNN Object Detection Networks practice using hands-on laboratory principles introduced in Calculus I, Prerequisite: MTT 200
and communicate their experience experiences covering Lane Finding, Engineering aiming to deepen understanding and Co-requisite: MTT 204 PHY 201 - Physics and
using presentations and reports. Behavior Cloning on data collected expand applications. Beginning with Engineering Applications II
using Unity Simulator, Autonomous a review of foundational functions This course is designed to equip Credit Hours: 3
AIRE430 - Generative AI indoor flight mission programming. from Calculus I, students will engineering students with essential Prerequisite: PHY 102
Credit Hours: 3 The course has a project. In this Degree Requirements progress to explore Transcendental techniques for solving various types
Prerequisite: AIRE 310 project, students work teams Functions, Integration Techniques, of first-order differential equations The course is intended to provide
using PyCharm, MATLAB, Arduino, Infinite Series, and Power Series. including Separable, Exact, Linear, computer science students with
This course builds on the Raspberry Pi, Actuators, and Sensors ECS100 - Introduction to Through practical problem-solving and Bernoulli equations. Additionally, sufficient understanding and
concepts and skills acquired in to design a Self-driving Robot with exercises, students will refine students will learn to formulate knowledge of physics concepts in
AIRE310 Machine Learning. It Lane Assist and PID Control System Engineering and Computing their skills in translating real- mathematical models for basic Electricity and Magnetism that can
provides students with an in- and communicate their experience Credit Hours: 3 world scenarios into mathematical physical systems. Moreover, they will be relevant to their field of study.
depth understanding of concepts, using presentations and reports. Prerequisite: No Prerequisite equations, enhancing their ability solve higher-order linear ordinary The course is divided into two parts;
techniques, and applications of to interpret and solve complex differential equations using different Electricity and Magnetism.
generative modeling and deep AIRE 325 - Ultra-low Power AI This course provides an introductory application problems. methods such as the auxiliary
learning. Topics covered include on Microcontrollers general overview of electrical equation, infinite series, and Laplace The topics covered are; electric
field, Gauss’s law, electric potential,
Generative Modeling, Variational engineering, biomedical engineering, MTT 201 - Calculus III transforms. Furthermore, students
Autoencoders, Generative Adversarial Credit Hours: 3 computer engineering, and AI will explore the solution of systems of capacitance and dielectrics, current
Networks, Text-to-Image Generation, Prerequisite: CEN325 + AIRE310 and robotics engineering fields, Credit Hours: 3 differential equations. and resistance, direct current circuits,
Prerequisite: MTT 200
magnetic fields, sources of magnetic
and Autoregressive Models. Students This course builds on the concepts introducing students to concepts,
connect theoretical concepts learned and skills acquired in CEN325, techniques, and applications This course is a continuation of the PHY 102 - Physics & Engineering field, Faraday’s law, inductance, and
Applications I
alternating current circuits. Taken
in the course to practice using hands- Internet of Things: Foundations of Electrical, Computer, and study of Calculus II. The purpose is
on laboratory experiences covering and Design, and AIRE310, Machine Biomedical Engineering. Topics to establish a firm understanding Credit Hours: 3 Simultaneously with PHY 201L
Generative Modeling Fundamentals, Learning. It introduces students covered include an Introduction to of multi-dimensional aspects of Prerequisite: MTT 102 (1credit hour) prerequisite PHY 102 +
PHY 201 Co-requisite.
Image Generation with GANs, and to concepts, techniques, and Engineering, Roles, and Workplace calculus and its applications. The
Text Generation with Autoregressive applications of Machine Learning of Engineers, Ethical Practices in topics covered are as follows: An The course aim is to provide PHY 201L - Physics and
Models. The course has a project. (ML), Deep Learning, and Internet of Engineering, Design Process, Basic introduction to vectors and geometry computer science students with clear Engineering Application II
In this project, students work teams Things (IoT). Topics covered include Circuit Concepts, Numeric Systems, of space, partial derivatives, and understanding of the basic concepts Laboratory
using MATLAB and PyCharm to Machine Learning, Deep Neural and Teamwork. Students connect multiple integrals. of physics. The course is divided into
design a Synthetic Data Generator Networks, IoT, Microcontrollers, theoretical concepts learned in the two parts: Mechanics, and Waves. Credit Hour: 1
and communicate their experience Embedded Systems, TinyML. course to practice using hands-on Working through application The topics covered are; Units, Vectors Prerequisite: PHY 102
using presentations and reports. Students connect theoretical laboratory experiences covering problems, the students will develop and Scalars, Kinematics, Newton’s Co-requisite: PHY 201
concepts learned in the course to Ohm’s law, electronic simulations, the ability to interpret and evaluate laws of Motion, Work and Energy, This course is designed to help
Oscillatory Motion, Wave Motion,
real world application problems
programming, and debugging. The
AI Concentration practice using hands-on laboratory course has a project where students from text form into a mathematical Sound Waves, and Superposition of students develop the ability to
experiences covering TinyML Models
perform scientific experiments and
Elective Courses Training and Testing, Deployment of work in teams using Tinkercad, equation. Waves. Taken simultaneously with to enhance their understanding of
PHY 102L (1 credit hour) prerequisite
TinyML Models to Microcontrollers, EasyEDA, ICs, PCBs, and testing and MTT 204 - Introduction to Linear MTT 102 + PHY 102 Co-requisite. theoretical material presented in
measuring equipment to design
and Wake-Word Detection Algebra Phy201 (Electricity and Magnetism)
AIRE 475 - Self-Driving Cars Application. The course has a project. an electrocution protection system PHY 102L - Physics and by performing landmark experiments
and communicate their experience
In this project, students work teams Credit Hours: 3 Engineering Applications I with emphasis on the presentation
Credit Hours: 3 using Arduino IDE , TensorFlow Lite, using presentations and reports. Prerequisite: MTT 200 Laboratory and interpretation of experimental
Prerequisite: CEN325 + AIRE310 PyCharm, Arduino Nano 33 BLE Students will also analyze the This course introduces Linear data.The student will be required to
impact of Electrical, Computer, and
Sense, Sensors, and Actuators to Credit Hours: 1 make extensive use of computer-
This course builds on the concepts Biomedical Engineering on society, Algebra and its practical applications, Prerequisite: MTT 102
and skills acquired in CEN325, design a TinyML-based Model and the environment, and the economy. particularly in Engineering. It aims Co-requisite: PHY102 generated graphs and tables
Deployment and communicate their
Internet of Things: Foundations experience using presentations and to impart fundamental concepts of for displaying and analyzing
and Design, and AIRE310, Machine reports. linear algebra while demonstrating This course is designed to help experimental data. This will be
Learning. It provides students with an their applicability in engineering students develop the ability to accomplished using Excel or other
in-depth understanding of concepts, contexts. Topics covered include perform scientific experiments and spreadsheet programs of comparable
techniques, and applications of matrices, systems of linear equations, to enhance their understanding capability. To accomplish this, each
Self-Driving Vehicles. Topics covered determinants, linear transformations, of theoretical concepts presented laboratory station is equipped with a
Abu Dhabi University | Undergraduate Catalog 2026 - 2027 Abu Dhabi University | Undergraduate Catalog 2026 - 2027