Technology and Science Division - Available Courses

Computer Science

Computer Science 101: Digital Literacy

This course serves as an introductory course to digital literacy, both on a theoretical and an experiential level, focusing on general purpose computing, networks and the internet, information and data management and social media. Under the umbrella of Computer Science, students are exposed to the fundamental principles of operating systems, human computer interaction, networking and communication, architecture and organization, computational science, information management, social issues and professional practice and learn to identify and exploit them for everyday organizational tasks. On a practical level, students learn how to use Operating Systems (proprietary and FOSS) and collaborative cloud based office productivity software; how to publish and present their work using computing and mobile / smart devices and the internet; how to use web 2.0 tools for content creation and delivery (collaborative wikis, blogs, newsgroups, social media platforms); how to create and manage their personal digital identity; how to organize and process data; how to search for and critically evaluate information which is available on the world wide web and scientific literature databases; how to plan projects using modern web-based tools. They are also exposed to technical writing, collaborative informatics projects, public speaking and presenting their work within pre-determined time limits. May be taken as Computer Science GER.

Computer Science 105: Introduction to Programming I – Structured Programming

This is an introduction to computing and computer programming using the Java or C language. Students are introduced to the basic elements of computing hardware, information technology and computer programming. Programming is explained, demonstrated and practiced using the Java or C programing language. Ultimately the course aims to advance beyond basic computing skills towards software engineering, instructing students to develop autonomy as sophisticated computer users and programmers. May be taken as Computer Science GER.

Computer Science 106: Introduction to Programming II – Object oriented programming

The course provides a systematic coverage of Object Oriented Modelling and Applications. Topics include Object Models, Object Class Design, Inheritance and Polymorphism, Software Reuse with Classes, Application Modelling, Simulation with Object Classes, and Business Process Modelling with Objects. Object-oriented programming (OOP) is a revolutionary concept that changed the rules in computer program development. OOP is organized around “objects” rather than “actions”, data rather than logic. Historically, a program has been viewed as a logical procedure that takes input data, processes it, and produces output data. The programming challenge was seen as how to write the logic, not how to define the data. Object-oriented programming takes the view that, “what we really care about:”, are the objects we want to manipulate rather than the logic required to manipulate them.

The course expands on the material covered in CS105 with the following aims:
• Further cultivation of algorithmic thinking and refinement of existing procedural programming skills
• Familiarization with the Object Oriented programming methodology
• Exposure to Java classes for building graphical interfaces and other extensions
May be taken as Computer Science GER. Prereq: Computer Science 105

Computer Science 107: Multimedia I - Digital Media Toolkit

This course is an introduction to digital multimedia. All media components (digital images/graphics, text, animation, sound and digital video) are introduced and their parameters defined and studied. Software multimedia development tools necessary for the creation or capture of digital media are presented and students acquire hands-on experience with a package for each media category. Hardware essential for the capture/creation of the media is also presented. Multimedia project design parameters are examined and applied to a student capstone project. 
The main software used in this course will be Adobe Bridge, Adobe Photoshop, Adobe Premier Pro, Adobe Camera Raw and/or Lightroom. Other software may be used, which will be announced at the beginning of the course. May be taken as Computer Science GER.

Computer Science 115 - Introduction to Structured Programming with the C++ programming language

An introduction to computing and computer programming course using the C++ language. The course is designed for students who have no prior experience in programming, just some basic exposure to computing fundamentals as users. It is a fast-paced, intensive structured programming course, which can also accommodate students who already know how to program in another language and wish to learn how to code in C++. Students initially go through a swift introduction to the basic elements of computing hardware, information technology and computer programming. Problem analysis and algorithmic planning are explained, demonstrated and practiced using the C++ programming language. Ultimately the course advances beyond basic computing skills, guiding students to develop autonomy as sophisticated computer users and reach an intermediate level of algorithmic thinking and coding skills. Prerequisite: Basic computing, numerical and analytical skills.

Computer Science 130: Introduction to electronics and robotics programming

The primary difference between robots and other types of computing devices is their ability to have a physical effect on their environment, rather than to simply gather, process and communicate data. This is particularly apparent in the case of autonomous mobile robots: they face the challenge of acquiring data from their surroundings using sensors, selecting their own navigation waypoints and dynamically altering their course of action to account for obstacles, power supply restrictions and unexpected events. In this introductory experiential learning course, students will be introduced to the Python programming language, assigned work as part of a team and be challenged to build both the hardware chassis and software algorithms for such autonomous mobile robots. Course participants will be instructed on using the Mindstorms EV3 robotics kit, an Arduino microcontroller board and additional electromechanical resources to solve a series of increasingly challenging problems. The course starts with programming basics and sensor data acquisition, moving through to actuators, robotic navigation, obstacle avoidance, sensor data fusion and culminates in robotic team design challenges. Prerequisite: Basic computing, numerical and analytical skills. Previous exposure to programming code is considered an advantage but not necessary.

Computer Science 151: Quantitative Computing

The course aims at deepening student quantitative skills by interrelating mathematical modeling and spreadsheet implementation. Students are presented real-world problems encountered in the modern enterprise, with emphasis on spreadsheet computing and are taught both the mathematical background and the necessary structures for tackling the problem with spreadsheets. Emphasis is placed on mutual translation of mathematical model and spreadsheet implementation. Focus is on Business Planning and topics are drawn from Microeconomics, Finance, Marketing, Managerial and Financial Accounting. Mathematical topics covered include: Real numbers and their computer implementation, polynomial, exponential and logarithmic functions, matrices, linear programming and optimization, recursive models, discrete approximation of the derivative and integral. May be taken as Computer Science GER. Prereq: Computer Science 101 or 105, Math 101

Computer Science 180: Discrete Structures

This course introduces the mathematical structures and methods that form the foundation of computer science. The material will be motivated by applications from computer science and emphasize:

• Techniques: binary and modular arithmetic, set notation, methods of counting, evaluating sums, solving recurrences
• Supporting Theory: basics of probability, proof by induction, growth of functions, and analysis techniques and
• General problem solving techniques with many applications to real problems.

The course material is divided into five modules. Each module starts with a motivating application then goes into techniques related to that application and the theory behind those techniques. Each module ends with one or more fairly deep applications based on the material.
These modules are: Computers and Computing: Numbers, Circuits, and Logic; Cryptography: Integers and Modular Arithmetic; Combinatorics: Sets, Counting, and Probability; Algorithmic Analysis: Searching and Sorting; Networks: Graphs and Trees.

Computer Science 190: Programming with Python

This course introduces students to programming for data and information science. Key concepts in programming, data structures, and data analysis are presented through Python. The various programming stages of a data analytics pipeline are explained and students are introduced to data analytics and visualization tools. Topics addressed include: Variables and mathematical operators, Files and Data visualization, Conditionals, Iteration (loops) and lists, Functions, 2D lists, Dictionaries, Classes & Objects, and Pandas.

Computer Science 201: Business Computing

The course aims at presenting Business majors with the basic computing structures needed to support a company’s management. Students will be exposed to data tables from a variety of business activities as well as the database techniques necessary to model and effectively process these data for the purposes of company assessment and planning. Examples of applications residing in the WWW will be presented, analyzed and subsequently implemented by students with the database medium used in the course. Prereq: Computer Science 151

Computer Science 205: Business Data Management

The purpose of COMP SCI 205 is to introduce the idea of business data management, data modeling, and processing methodologies with the use of standalone design tools and personal databases. It aims at fostering proper data design through the relational methodology and developing all necessary data processing and presentation skills. The aims of this course are to:
• Define the role of Systems Analyst and Database designer.
• Explain System Analysis and interpersonal communication skills that the System Analyst must have
• Explain Project Management and discuss tools that the system analyst must have
• Explain the Methodologies that are used for Systems Analysis and Database Design
• Explain the various tools that certain methodologies use
Provide students the opportunity to work on the most popular database (Oracle), in a project in order to implement the taught methodologies. Prereq: Computer Science 105

Computer Science 206: Web Development

COMP SCI 206 is an introductory course for beginning web designers. We will explore some essential concepts related to the creation of effective web sites. In the last portion of the course we will concentrate on client-side scripting using the programming language JavaScript. This course aims at introducing students the basic web design guidelines, Fundamentals of Hyper Text Markup Language (HTML), and how to use a Simple HTML Editor as well as Web Authoring Tools. Also, one of the main goals of the course will be to understand what scripting languages are and to be able to develop scripts. Prereq. Computer Science 101 or 105

Computer Science 207: Multimedia II

This course is the continuation of CS107. Advanced editing techniques of digital images and digital video will be presented, studied and practiced. Basic animation techniques (using Macromedia Flash) will be presented, studied and practiced. Students will acquire further skills on capture hardware (Photo, Video, Audio). Individual student capstone projects on Video and animation will be assigned at the end of the course. Prereq: Computer Science 107 or permission of instructor

Computer Science 209: 3-D Digital Design I

The focus of this course is the introduction to the 3D workspace, creation tools, and the basics of 3D design. Including modeling 3D geometry, creating material textures and lighting, and rendering output to animation and still image formats. 3D animation techniques will also be presented, studied and practiced. The concepts and interrelationships of developing a story and character from premise to production will be presented, studied and implemented by students on a final capstone project. Students will acquire hands-on experience using 3ds max and will build on their 2D skills with the use of Photoshop as an aid in the creation of texture maps. Prereq: Computer Science 107

Computer Science 215: Data Structures

The purpose of CS215 is to introduce students to the main concepts and implementation principles of object-oriented programming and data structures, using Java as the programming language. This course builds on the knowledge and skills acquired in CS105 – Introduction to Programming I. The course is split in two parts; the first part deals with object-oriented programming using Java, re-enforcing the fundamental concepts learned in CS105. The second part of the course introduces data structures. The data structures examined include arrays, lists, queues, stacks, trees, heaps, hash tables and graphs. Searching, sorting, inserting, deleting and other simple operations on these structures will also be discussed. Prereq: Computer Science 106 or permission by instructor

Computer Science 219: Video Game Design

This course introduces the critical study of computer video games and the professional practice of game design. Through readings, discussions, research, and practical “hands-on” projects, students will better understand the current market for games and simulations and develop the fundamental skills necessary to enter the international computer games industry. Although the commercial video game pipeline will be discussed, the actual production framework for the class will mirror a ‘Indie” game team “prototype game level” development. Students will be expected to fill multiple roles in the production process, and gain hands-on experience in the collaborative processes of game design, project management, scripting, content creation pipeline, in game animation, and play-testing. Prereq: Computer Science 107; CS105 recommended or permission by instructor

Computer Science 230: Introductory Systems Programming

The course continues from CS105, Structured Programming, aiming to making students familiar with a variety of fundamental software engineering challenges which can be solved by developing the appropriate software algorithms. The course furthers algorithmic skills with increased emphasis on systems programming. More elaborate data structures are manipulated and the role of libraries accessing Operating System resources (Disk, I/O) is examined. In this manner the course serves as a bridge between the Programming Fundamentals and the Computing Systems programme threads. The course employs a high-level language (C++) and investigates structured programming as follow-up to the introductory course in programming. More elaborate structures are learned and employed, in order to solve a wide range of tasks. Intricacies of the C/C++ languages are investigated and related to computer architecture (pointers, variable addresses, memory allocation). The course, in addition to furthering algorithmic thinking skills, also serves as the introductory course for the Computing Systems programme thread, as the relationship of the high level language with the underlying computer system is investigated and applied to system programming tasks involving I/O with a variety of external devices (user interaction, storage, microcontrollers). Prereq. Computer Science 101 or 105 or permission by instructor

Computer Science 300: Mobile Application Programming

This course focuses on the fundamentals of mobile strategy and development, application architecture and design. Students will have the opportunity to learn the benefits and challenges of mobile application planning, design, development and strategy through real world examples and actual project work. Through readings, discussions, research, and practical “hands-on” projects, students will better understand the current market for mobile applications and develop the fundamental skills necessary to enter the mobile application industry. This course aims to teach how to build cross-platform mobile solutions to solve complex problems using iOS and Android phones and tablets. The course will teach students how to develop software for iOS and Android mobile devices through real world examples and strategies. Students will be guided through a complete mobile development lifecycle during the semester, and be given the opportunity to develop a series of applications. Prereq: Computer Science 106 or permission by instructor

Computer Science 306: Advanced Web Development

This course builds upon the skills and knowledge about creating and publishing Web pages and sites taught in CS 206. It also introduces students to advanced web development areas, required for students interested in pursuing a career in web site design. This course aims mainly on client-side scripting using the programming language JavaScript. The objective will be to understand what scripting languages are and to be able to develop scripts. The course will also offer an introduction to jQuery library, Asynchronous JavaScript and XML (AJAX), basically showing the benefits of their use and applying it to certain programming tasks. In the last portion of the course, students will gain a practical knowledge about the currently most used web content management environments. By combining lectures with seminar discussions and extensive hands-on experiences the course will introduce the students both to the applied aspects of content management technologies but also to the theoretical issues involved. Prereq: Computer Science 105 & 206

Computer Science 309: 3-D Digital Design II

This Course will build on the existing cs209 course and serve as a more in-depth study of 3d digital design in practice and theory. This course will continue development from cs209 topics, and the following intermediate to advanced topics which are beyond the scope of CS209, will be presented, studied and practiced. This includes, Nurbs and Patch surface modeling, advanced Material, Mapping and Lighting techniques and more advanced Rendering methods. Advanced character animation tools will also be covered including Character studio and Max’s character animation tools. It will also cover Dynamic simulations using Reactor and introduces max scripting. Prereq: Computer Science 209

Computer Science 310: Hardware & Computer Architecture

This course addresses the structure and function of modern digital computing devices, ranging from the compilation process down to the hardware level. Despite the pace of change and variability in the fields of informatics, electronics and computer engineering, certain fundamental digital design concepts apply consistently throughout. CS310 students will both gain the relevant theoretical understanding and have a chance to apply it in practice designing, simulating, troubleshooting and optimizing their own combinational and sequential logic circuits. The course concludes with a discussion on system level organization and architecture of modern computing devices. This course builds on knowledge and skills acquired in CS105 – Introduction to Programming I. Upon successful completion of the course students be able to:
• Understand and be able to explain the significance and function of fundamental components within a typical modern
computing device (processor, memory, I/O, operating system), their interconnections with each other and the outside world.
• Comprehend and follow the data flow through the internal structure of a digital microprocessor.
• Understand the importance and function of logic gates as primary building components in digital design.
• Analyse combinational digital circuits and optimize them using Karnaugh maps.
• Be able to design, simulate, troubleshoot and optimize their combinational and sequential digital logic circuits.
• Recognize and understand basic Assembly language and Machine Code.
Prereq: Computer Science 105

Computer Science 312: Database Management Systems

The purpose of the course is to offer a systematic coverage of modern Database Computing theory and technology. Topics include: Relational Algebra, Data Modelling, Database Design, Client-Server Database Management Systems, Interface Design, trends in Database Systems, combination of Object Oriented Modelling and Relational Databases. Prereq: Computer Science 205

Computer Science 321: Operating Systems

This course deepens understanding of how contemporary computing systems are structured and, in particular, supported by an Operating System. It is a culmination course within the Computing Systems programme thread. Operating Systems are the brain of any computing system. They handle the body/DNA (hardware) as well as behaviour (usage of system by user). Following rapid to revolutionary technological developments the field of Operating Systems also undergoes tremendous changes, which constantly evolve the conception of an OS and of course the technological challenges involved in its implementation. The course aims at outlining the role of an OS in a diachronic way while comparing and contrasting design choices spanning the evolution of the field. It aims at defining fundamental needs that a von Neumann machine has from the Operating System in order to be functional, optimal and attractive to the user. The course explains Operating Systems architecture and examines trade-offs involved in different, evolving systems. It further examines diachronic as well as contemporary issues involved in Operating System design by comparing and contrasting relevant design and algorithmic choices. The course involves lab work: Communication with the OS at a low level via a Linux shell and programming tasks addressing aspects of Operating System design and implementation. Prereq: Computer Science 215, Computer Science 310, or permission by the Department

Computer Science 322: Network Operating Systems and Administration

This course aims to provide the student with the knowledge of how computer networks are designed, engineered and operated. This includes knowledge of the fundamental algorithms used in the management of both resources and traffic and how these algorithms may interact with application programs. Instruction includes, but is not limited to network terminology and protocols, network standards, LANs, WANs, OSI models, cabling, cabling tools, routers, router programming, star topology, and IP addressing. The student will study and design networks, using Ethernet, TCP/IP Addressing Protocol, and dynamic routing. Particular emphasis is given to the use of decision-making and problem-solving techniques in applying science, mathematics, communication, and social studies concepts to solve networking problems. Prereq: Computer Science 215

Computer Science 325: Distributed Applications

The purpose of the course is to examine in detail the software and hardware technologies prevalent in the Internet and provide an introduction to the principles and methods for creating distributed on-line client/server applications that are the basis for electronic commerce as it is conducted over the Internet. Methods and tools such as HTML, the Common Gateway Interface, PHP, database connectivity tools and MySQL are presented. Coverage is also given to emerging standards for information exchange, encryption and validation. Prereq: Computer Science 312

Computer Science 330: Introduction to Mobile Robotics

The primary difference between robots and other types of computing devices is their ability to physically interact with their environment, rather than to simply gather, process, store and communicate data. This is particularly apparent in the case of autonomous and semi autonomous mobile robots: they face the challenge of acquiring data from their surroundings, selecting their own navigation waypoints and dynamically altering their course of action to account for obstacles, power supply restrictions and unexpected events. In this course theoretical instruction is combined with experiential learning and challenge driven software development. 
Students participating in this course are challenged individually and in teams to build the hardware chassis and software control algorithms for mobile robots. The course assumes a basic background in structured programming and proceeds with an introduction to both visual and text source code robotic programming (C, RobotC); basic electronics circuit design and troubleshooting; microcontroller programming; sensor data acquisition algorithms; actuator control; robotic navigation and obstacle avoidance; basic sensor data fusion; and concludes with a final robotic design challenge which integrates all aforementioned knowledge and skills. This course builds on structured programming skills developed in CS105: Introduction to Programming. Prereq: CS 105: Introduction to Programming or equivalent

Computer Science 333: Cisco Advanced LAN and WAN Design

In the first part of this course, students learn to configure routers and switches and use network management techniques to find and fix network problems. Topics covered include advanced router configuration, LAN switching theory, and VLANs. There is significant emphasis on project-based learning. In the second part of the course, concepts and methods involved in wide area networking (WAN) design and implementation are introduced. Topics include WAN theory and design, WAN technology, PPP, Frame Relay, and ISDN. Numerous topics and issues are covered through the use of threaded case studies. By the end of this course, students complete advanced projects in network design and management. Successful completion of this course prepares students for the Cisco Certified Networking Associate test (CCNA). Prereq: Computer Science 222

Computer Science 340: Artificial Intelligence

This course is an introduction to the field of AI, including an intensive initial introduction to the Python programming language. Indicative AI topics include knowledge representation, problem solving via search, logical and probabilistic reasoning and machine learning algorithms such as decision trees, neural networks, reinforcement learning and genetic algorithms. Prereq: CSC 215

Computer Science 345: Applied Machine Learning and Deep Neural Networks

The course explores the vast field of Machine Learning (ML) at the senior level, focusing on its applications and related software implementations. Covers a variety of related ML models but specializes in the subfield of Deep Learning that encompasses the most successful algorithms that are used to train Deep Neural Networks (DNN). The course mostly emphasizes on the practical application of Machine Learning on data that are available for the needs of a specific intelligent task. These tasks belong to diverse domains like Image Recognition, Natural Language Understanding, and Recommender Systems, and during the course students will be handed the appropriate source code examples which implement ML models for the tasks. Understanding the basic theory through examples, allows the formulation of a solution for the given task and consequently the selection of an ML model, which can be a DNN, that will become a software implementation using popular libraries. The correct selection and usage of the related data samples are part of this research and development process. The experimental setup includes a quantitative evaluation of the solution performance using the proper metrics. The research methodology concludes by identifying problems of ML through evaluation, designing improvements for the next set of experiments, or stating open questions for future work. Prereq: CSC 190 and MATH 220

Computer Science 350: Software Engineering

After successfully finishing this course students are expected to have in-depth knowledge of all phases of the software engineering lifecycle, i.e. requirements engineering and software design, software design, implementation, verification and validation, quality assessment, software re-engineering, and software reverse engineering methods. In addition to that, students are expected to acquire skills related to communication with the customer, teamwork, time management and global software development. Prereq: CSC 450 or permission by instructor.

Computer Science 360: Introductory Data Science/MSDS 650: Data Analytics

This course is an introduction to data science using Python. Students learn how to process, clean and manipulate data in a variety of formats; visualize multidimensional data; communicate the findings of a data analytics project; apply machine learning algorithms to a variety of datasets; design pipelines for the evaluation of models performance. This course provides the student with the data-science skills and the analytical mindset necessary to meet the needs of business and the real-world decision-making problems. Prereq: CSC 340, MATH 220 or permission by instructor.

Computer Science 412: Object Oriented Programming

The course revisits Object Oriented application development methodology at the Senior level, examining its effectiveness in the life cycle of professional applications and software reuse through the adoption of Object Oriented Design Patterns. It presupposes the knowledge earned through the introductory line of the Programming Fundamentals programme thread and follows level 5 modules relating to Data Modelling (CS 312) and Systems Design (CS450) while specialising them within the context of Web Development. Currently CSC 325 (Distributed Systems) is a necessary prerequisite concerning web deployment technologies. 
The module mostly emphasizes the employment of OO concepts to Web Development yet it is of general enough nature for a level 6 module as the design patterns examined are applicable to a wide range of technologies and application domains. Prereq: Computer Science C215, CS312, CS325 or permission by the instructor.

Computer Science 421: Computer Systems Security

This course aims at providing both a theoretical and practical background concerning issues of security in modern, networked systems. Cryptography is covered first (essentially discussions of standard algorithms). The remainder of the module focuses on techniques that can be used to safeguard real systems. Topics that are covered include Key management and credentials, Steganography and watermarking, Network security (VPNs, Firewalls, Intrusion Detection) and System Security Policies. Risk assessment and threat models as well as social engineering will be covered. Prereq: Computer Science 321, CS322 or permission by the Instructor.

Computer Science 422: Advanced DBMS

This course focuses on creating and manipulating databases using SQL and PL/SQL programming languages for Oracle databases. Advanced query capabilities and procedural constructs are described using SQL and PL/SQL. The theoretical foundation for using these capabilities is presented. Performance issues are discussed including indexing, key definitions, and data constraints. The role of application development in ease of use, query optimization, and system performance is discussed. The module aims to teach students to use advanced SQL statements and PL/SQL programming features such as IF statements, Loops, Stored Functions/Procedures, Tables, Cursors, Stored Packages, Stored Triggers and creating and maintaining various databases. SmartDraw and Designer of Oracle is used for ERD’s. APEX, SQL Plus and SQL Navigator, SQL Server Management Studio are used as user interface of the databases. Prereq: Computer Science 312

CS 443 – CS 444: Capstone Project

This is a set of linked courses to be taken in sequence over the course of the senior year. The course aims to give students the opportunity to work in a guided but independent fashion to explore a substantial problem in depth, making practical use of principles, techniques and methodologies acquired elsewhere in the program of studies. It also aims to give experience of carrying out a large piece of individual work and in producing a final project report. It has two distinct phases: the preparatory phase focusing on literature review, assessment of Technologies and Project Specification and the implementation phase focusing on project design, development, documentation and presentation.

Computer Science 450: System Analysis and Design

The module introduces the waterfall model for system/application development and the formal tools employed in its various stages. The objectives of the module are to:
• Provide formal tools for functional and non-functional requirements collection and documentation (ERD, UML, DFD,
STD’s)
• Define the role of the systems analyst and designer.
• Build project management and interpersonal communication skills that the system analyst must have.
• Explain the methodologies that are used for systems analysis and design.
• Follow through the waterfall model (and discuss deviations therefrom), presenting the relevant tools at each stage.
• Provide the problem solving background for resolving trade-offs inherent in design.
• Present principles of quality and correctness testing.
• Provide students the opportunity to work as a team of analysts and designers in a project to implement the taught methodologies.
Students develop technical, analytical and business skills that support the pursuit of professional careers and advanced computer science studies. Prereq: Computer Science 201 or 205

Computer Science 499: Advanced Programming Tools

This course is a complete introduction to .NET and object-oriented programming. This course will help students build a solid foundation in .NET, and show how to apply these skills by using numerous examples. Learning .NET introduces fundamentals like Visual Studio .NET, a tool set for building Windows and Web applications. Students learn about the syntax and structure of the Visual Basic .NET language, including operators, classes and interfaces, structures, arrays, threads, console, passing parameters, sessions, cookies and manipulating all type of strings. Students will also be asked to develop various kinds of applications--including those that work with databases (ADO)--and web services (ASPX) and making use of XML. Finally the course focuses on how to build installable applications using the Setup platform of .NET to create .MSI self installed applications. Prereq: Computer Science 412 or Permission of instructor

Mathematics

Mathematics 100: Mathematics for Decision-Making

An introduction to selected areas of mathematics in familiar settings with the objective of developing students’ conceptual and problem solving skills. The course includes a study of mathematical concepts selected from graph theory, planning and scheduling techniques, statistics, probability, game theory, growth patterns, coding information, voting systems and apportionment. May be taken as a Math and Statistics GER.

Mathematics 101: Elements of Finite Mathematics

This course places an emphasis on the role of functions (coordinate systems, properties, graphs and applications of polynomial, rational, logarithmic and exponential functions), solving systems of linear equations, matrix operations, mathematics of finance, and introductory counting techniques. May be taken as a Math and Statistics GER.

Mathematics 115: Business Calculus

This course covers: rate of change and introduction of the derivative for functions of one variable; applications of the derivative to graphing one-variable functions and to optimization problems; introduction of functions of several variables and partial derivatives; problems of unconstrained and constrained multivariable optimization; applications of differential equations; integration of functions of one variable and applications, and advanced methods of optimization. Emphasis is placed on applications and problem solving through conventional and computer methods. May be taken as a Math and Statistics GER. Prereq: Math 101

Mathematics 120: Calculus I for Science and Engineering

This course provides a solid foundation in Calculus concepts, tools and techniques for the student entering Science and Engineering fields. The course covers definition, calculation, and major uses of the derivative, as well as an introduction to integration. Topics include limits; the derivative as a limit; rules for differentiation; and formulas for the derivatives of algebraic, trigonometric, and exponential/logarithmic functions. Also discusses applications of derivatives to motion, density, optimization, linear approximations, and related rates. Topics on integration include the definition of the integral as a limit of sums, anti-differentiation, the fundamental theorem of calculus, and integration by the U-substitution and Integration by parts technique. The course emphasizes conceptualization, modeling, and skills. There is a concentration on multiple ways of viewing functions, on a variety of problems where more than one approach is possible, and on student activity and discussion. May be taken as a Math and Statistics GER. Prereq: Math 101 or CSC 180. No Prereq. for Biological Sciences Majors

Mathematics 121: Calculus II for Science and Engineering

The purpose of this course is to give a solid foundation in Calculus concepts, tools and techniques for the student entering Science and Engineering fields.This course is a continuation to Calculus I for Science and Engineering where the student mastered: Limits, Differentiation, Anti-Differentiation and Basic Integration skills of 2D functions as well as basic introduction to parameterized curves and motion. This course will cover: Techniques and Applications of Integration. Topics will include: Integration by Parts; Integration by Partial Fractions; Trigonometric Integration; Numerical Integration; Improper Integrals; and Areas, Volumes, Mass/Moments and Work as Integrals; Infinite Series and Introduction to Vectors. Other topics addressed are: Convergence of Sequences and Series of numbers, Power Series representations and Approximations of Functions, 3D Coordinates, Parameterizations, Vectors, Dot and Cross Products, Equations of Lines and Planes. Prereq: MATH 120

Mathematics 130: Introduction to Mathematical Reasoning

The course aims to cover the basics of mathematical reasoning and problem solving to prepare incoming math majors for future courses which require proofs and rigor. Among other topics, the course will focus on: Fundamentals of mathematical arguments (definitions, elements of logic, quantifiers, theorems, proofs, counterexamples, proof by contrapositive and proof by contradiction); Sets and set-theoretic proofs; Counting and Combinatorial proofs; Mathematical Induction, smallest counter-examples; Relations and equivalence relations; Functions and Inverse Functions; Pigeonhole Principle and Inclusion- Exclusion; Cardinality of Sets.

Mathematics 201: Calculus III for Science and Engineering

The purpose of this course is to give a solid foundation in Calculus concepts, tools and techniques for the student entering Science and Engineering fields. This course is a continuation to Calculus II for Science and Engineering. This course will address: Vectors, the dot and cross products, lines, planes, and surfaces. Vector-valued functions, their derivatives and integrals, the length and curvature of space curves, and velocity and acceleration along space curves, culminating in Kepler’s laws. Functions of two or more variables are studied from verbal, numerical, visual, and algebraic points of view. Contour maps and the Midpoint Rule are used to estimate the average snowfall and average temperature in given regions. Double and triple integrals are used to compute probabilities, surface areas, and (in projects) volumes of hyperspheres and volumes of intersections of three cylinders. Cylindrical and spherical coordinates are introduced in the context of evaluating triple integrals. Vector fields. The similarities among the Fundamental Theorem for line integrals, Green’s Theorem, Stokes’ Theorem, and the Divergence Theorem are emphasized. The course emphasizes on skill, conceptualization and some modeling. All three are of great importance. Visualization and analysis via the use of technology is used in lecture and could be addressed in Take-Home Assignments. Prereq: MATH 121

Mathematics 210: Differential Equations

The purpose of this course is to give a solid introduction to Ordinary Differential Equations, for students entering Science and Engineering fields. This course is a continuation to Calculus II for Science and Engineering where the student has mastered: integration skills of 2D functions, and some applications in physics. This course will cover: First-order differential equations (Linear, separable, and exact .Method of integrating factor), Secondorder linear equations (Homogeneous, non-homogeneous, the Wronskian, method of variation of parameters). The Laplace transformation (Series solutions. Systems of first-order linear equations). Other topics addressed are: Integral curves of solutions, via software (MATLAB, Mathematica, or other), Numerical approximations: Euler’s method, The Existence and Uniqueness Theorem, Matrix Algebra. The course emphasizes on skill, conceptualization and some modeling. All three are of great importance. Visualization and analysis via the use of technology is used in lecture and could be addressed in Take-Home Assignments. Prereq: MATH 121

Mathematics 215: Differential Equations and Linear Algebra

The idea of constructing mathematical models to address real-life applications is at the core of the interplay between mathemat- ics and the sciences. In the context of natural sciences, it is often the case that these models involve univariate functions and their derivatives. The course will present an overview of the methods to set- up and solve such equations, called ordinary differential equations (ODE). In parallel, and motivated by systems of linear differential equations, the course will cover the core concepts of Linear Algebra. Following the completion of the course students are expected to have mastered the following topics: First Order Differential Equations; Higher Order Linear Differential Equations; Laplace Transforms; Numerical Methods; Boundary Value and Initial Value Problems; Applications to the Sciences; Systems of Equations and Matrices; Linear Transformations and Eigenvalues. Prereq: MATH 121

Mathematics 220: Discrete Mathematics

Discrete mathematics can be defined as the study of structures consisting of a sequence of individual, separated steps. As such, they contrast with calculus, the latter describing processes which vary continuously or smoothly. If one can claim that the ideas of calculus were fundamental to the industrial revolution, then one can safely assume that the backbone of the science and technology of the computer age is discrete mathematics. The purpose of this course is for the students to understand and use the aforementioned discrete backbones of computer science. In particular, this class is meant to introduce logic, proofs, sets, relations, functions, counting, and probability, with an emphasis on applications in computer science. Further, this course will cover fundamental mathematical foundations required for conceiving, proving, and analyzing algorithms. Prereq: MATH 101, Computer Science 105 or permission by instructor.

Mathematics 230 – Linear Algebra for Computer Science

This course is an introduction to the field of Linear Algebra, and focuses on the interplay between geometry, abstract algebra and hands-on programming. The main learning objectives are grouped in the four categories mentioned in the brief description above: students are expected to sharpen their geometric and visualization skills, develop and enhance abstract thinking via theoretical results and proofs, perform explicit computations cultivating and nourishing previously acquired programming skills, and apply the course’s core concepts on a wide variety of modern disciplines related to Computer Science. The course material and topics covered fall under four general categories. Visualization: focuses on the geometric aspects of linear algebra, including, but not restricted to, vectors, spaces of vectors, projections and rigid motions. Abstraction: makes use of the theoretical structures developed over the years, such as vector spaces, matrices, linear transformations, eigenvalues and eigenvectors. Computation: relates the geometry and abstract algebra of the previous two categories to programming via concrete algorithms: Gaussian elimination, determinants, Cramer’s method, Gram-Schmidt and matrix multiplication. Applications: refers to connecting Computer Science oriented problems to the tools developed. The course aims to demonstrate applications of Linear Algebra to Optimization, Linear Programming, Graphic Design, Artificial Intelligence and Machine Learning.
Prereq: MATH 101 or Computer Science 180 or permission by instructor.

Statistics

Statistics 201: Statistics with Software

This module is an introduction to descriptive and inferential statistical methods. This introductory module covers the concepts and techniques concerning exploratory data collection and analysis, basic frequency distributions, correlation, central tendency and variation, basic probability principles, sampling distribution and statistical inference. Students will be exposed to these topics and will examine how each applies to and can be used in real life applications. Students will master problem solving using both manual computations and statistical software.
The course will be balanced between classic text-oriented resources and relevant computer software. It intends to help students develop their critical thinking and problem solving ability. Students are expected to have read attendance. Upon completion of this course, it is the aim and hope of the mathematics faculty that students who work hard and apply themselves will be able to:
1. Acquire solid statistical skills necessary to meet the needs of the real-world decision-making problems.
2. Effectively communicate the results of a statistical analysis both orally and in writing.
3. Gain fundamental statistical knowledge and skills required for a higher-level module in related fields.
4. Encourage modeling and connecting Mathematics to various disciplines.

Statistics 205: Statistics I

This course introduces students to basic statistical concepts and techniques. Each technique is illustrated by examples, which help students to understand not only how the statistical techniques are used, but also why decision-makers need to use them. Topics covered include Frequency Distributions, Statistical Descriptions, Introduction to Probability Theory, Discrete Probability Distributions, Continuous Probability Distributions, Sampling and Sampling Distributions. Emphasis is given to problem solving with the use of statistical software. May be taken as a Math and Statistics GER. Prereq: Computer Science 101, Math 101

Statistics 206: Biostatistics

This course is an introduction to descriptive and inferential statistical methods with a focus on biological applications. It covers concepts and techniques concerning exploratory data analysis, frequency distributions, confidence intervals and hypothesis testing, correlation and regression, central tendency and variation, probability principles, sampling distribution and statistical inference. Students will be exposed to these topics and will examine how each applies to and can be used in biological applications. Students will master problem solving using both manual computations and the open-source R-programming environment. The course will be balanced between classic text-oriented resources and relevant computer software. It intends to help students develop their critical thinking and problem solving ability.

Statistics 210/211: Introductory Statistics with R

This module is an application-oriented introduction to modern descriptive and inferential statistics using R statistical software. Students are first exposed to the basics of the R software including writing scripts and data manipulation. Then, a variety of statistical topics are discussed: study design, descriptive statistics, data visualization, random variables, probability and sampling distributions, point and interval estimates, hypothesis tests, and linear regression. Various real-world datasets are used for the application of the techniques learnt. Prereq.: CSC 180 or MATH 120 and CSC 101 or CSC 105.
Note: Statistics 211 is offered for the Biological Sciences program with relevant application.

Statistics 305: Statistics II

Continuing from Statistics 205, this course focuses on Interval Estimation, Hypothesis Testing, Statistical Inference about Means and Proportions with Two Populations, Inferences about Population Variances, Analysis of Variance and Experimental Design, Simple Linear Regression and Correlation, Index Numbers, and Non-parametric Methods. Emphasis is given to problem solving with the use of statistical software. Prereq: Stat 205

Anatomy and Physiology

Anatomy and Physiology 115: Integrated Human Anatomy and Physiology I

This course is the first part of a two-part Anatomy & Physiology Course. It is designed to provide an understanding of the anatomical structures, function and regulation of integumentary, muscular, skeletal, nervous and endocrine systems. This course aims to provide students with knowledge of normal function of the organ systems and thereby provide the information base for interpreting data relating to health and disease. For those in health fields, this information will serve as the foundation for most of your courses. Co-requisite: Human Anatomy & Physiology 115 Lab

Anatomy and Physiology 116: Integrated Human Anatomy and Physiology II

This course is the second part of a two-part Anatomy & Physiology Course. It is designed to provide an understanding of the anatomical structures, function and regulation of cardiovascular, respiratory, digestive, urinary, and immune systems. This course aims to provide students with knowledge of normal function of the organ systems and thereby provide the information base for interpreting data relating to health and disease. For those in health fields, this information will serve as the foundation for most of your courses. Prereq: Anatomy and Physiology 115. Co-requisite: Human Anatomy & Physiology 116 Lab.

Biology

Biology 112: Principles of Biology

This course is designed to introduce the basic principles of modern biology, the framework within which new discoveries are interpreted, and the relations among various branches of biological research. The goal of this course is to provide firstyear college students with a firm grasp of the major concepts underlying biological processes. Students who are interested in careers in biological sciences, biomedical sciences, and biotechnology should find that the course provides a firm grasp on an understanding of the concepts that will serve them well in their academic track that lies ahead. The materials covered include the structural and functional aspects at the molecular and cellular level of the following: cell structure and function, cell organelles, cellular reproduction, cellular respiration, photosynthetic pathways, Mendelian inheritance, DNA structure, replication, gene structure, and gene function and expression/control.

Biology 113: General Biology 2

Upon Completion of this course students should be able to: Describe the theory of evolution, the mechanisms of evolution especially by means of natural selection, the evolution of populations and species, and the evidence in support of evolution; Describe the history of life on Earth and research into the origin of life as well as the major periods of geologic time, the fossil record and the role of changing environmental conditions and mass extinctions in the evolution of life; Recognize a phylogenetic tree and the principles involved in grouping organisms on an evolutionary tree; Distinguish between organisms in the 3 domains of life and provide identifying characteristics of each; Identify groups of protists, the main clades of fungi, major groups and evolution of land plants and key characteristics and evolution of both invertebrate and vertebrate animals; Describe the societal implications of biopharmaceuticals, ocean acidification, climate change, habitat destruction and loss of biodiversity on human health. Prereq: Biology 112.

Biology 201: Foundations of Microbiology

The goal of this course is to introduce foundational concepts in microbiology and their connection with all the health care fields. The course subjects include the identification of microbes, mechanisms of pathogenicity and microbial disease, structure and response of the host immune system, and prevention against the spread of infectious disease.

Biology 230: Genetics and Molecular Biology

This course aims in developing an understanding of fundamental concepts in genetics and molecular biology. We will examine the central dogma in molecular biology, cell division, regulation of gene expression, Mendelian, non-Mendelian and molecular genetics, genes linkage and mapping, mutations, biotechnology, developmental, evolutionary and population genetics.

Biology 299: Inquiries in Biological Sciences

This course is structured in order encourage students thinking about concepts in biology from a different perspective compared to what they were taught in their first semester of college. During the course, we will investigate the biology of stress responses to environmental factors, like extreme temperature, pollutants, and pathogens, examine the involved mechanisms at different levels of biological organization and discuss the effects of these exposures for an organism and a population. Many different areas related to the topic will be surveyed, including biochemistry, regulation of gene expression, metabolism, cell signaling, physiology, and population dynamics. These topics will be discussed based on the following core concepts of biology: 1.Evolution, 2. Structure and Function, 3. Information flow, 4. Pathways and transformation of energy, 5. Systems Biology.

Biology/Philosophy 310: Bioethics

This is a required course for all Biological Sciences majors. It is structured to encourage students to consider the values and ethical principles relevant to life and to the application of biomedical technology for the maintenance, extension, and even production of life. The module will provide students with an understanding of core terms, concepts, and decision-making procedures used to discern and defend moral issues mainly related to life’s beginning and life’s end. The module has two principal aims. First, it considers some of the mainstream Western approaches to moral philosophy, including the ones of Aristotle, Rousseau, and Kant. Second and mainly, it seeks to apply these theories and others to contemporary biomedical sciences. The students will be exposed to some of the most challenging topics in the field, which include: personal autonomy, privacy, confidentiality & medical records, the right to refuse treatment, ethics of research on animals and humans, and philosophical and religious dimensions of life (abortion, assisted reproduction, disability, transplantation, euthanasia, etc.) Finally, the students will develop the ability to identify world views that give rise to moral norms and values.

Biology 320: Biochemistry

This course will provide an introduction to biomolecules in living matter. The simplicity of the building blocks of macromolecules (amino acids, monosaccharides, fatty acids and purine and pyrimidine bases) will be contrasted with the enormous variety and adaptability that is obtained with the different macromolecules (proteins, carbohydrates, lipids and nucleic acids). The nature of the electronic and molecular structure of macromolecules and the role of non-covalent interactions in an aqueous environment will be highlighted.

Biology 330: Cell Biology and Histology

This is a required module for all Biological Sciences majors. This module is designed to provide an understanding of the fundamental aspects of cell biology and tissue organization. The central object of study is the eukaryotic cell, its intracellular molecules, and the interactions between cells that result in the construction of multicellular organisms. This is a combined lecture and lab module that explores the relationship between structure and function at the cellular and tissue levels. The module will give the students an introduction to the structure and function of cells and cellular structures including the plasma membrane, cytoplasm, intracellular organelles, extracellular matrix, epithelia, and glands. Its overarching aim is to provide students with knowledge of the general organization and functions of the different cellular organelles, the diversity of animal and plant cells, and the cytophysiological characteristics that define the different tissues.

Biology 350: Microbiology and Infectious Diseases

This course emphasizes on the microbiology of infectious diseases through analysis of case studies and specific outbreak examples. Upon completion of this courses, student will be able to critically discuss the virulence and pathogenicity of infectious agents (bacteria, viruses, fungi and other parasites); centered on the interplay of the host – microbe balance; using indicative case studies. Apply theoretical knowl- edge of identification & classification, epidemiology, pathogenicity & virulence, of infectious agents on the treatment & control of patho- gens using selected examples of infectious diseases. Critically discuss the strategies available to control and treat microbial & viral diseases.

Biology 400: Senior Seminar

This is a seminar course that will be addressing one or more topics including: Social Medicine, Development and Differentiation, Community Health, Neuropathological Mechanisms, Immunology, Pharmaceutical Chemistry, Human Genetics, Evolutionary Medicine.

Biology 410: Principles of Epidemiology and Public Health

This is a required course for all Biological Sciences majors. It is designed to cover basic epidemiology principles, concepts, and procedures useful in the surveillance and investigation of health-related states or events. The course will provide students with a basic understanding of the practices of public health and medical statistics required for preventing and addressing population-based health outcomes. The c ourse explores the basic principles and methods of public health epidemiology. The biological, environmental, sociocultural, and behavioral factors associated with the etiology and distribution of health and disease are also investigated. In this context, topics covered in this course include: basic principles of epidemiology; measures of disease frequency; epidemiologic study designs: experimental and observational; bias; confounding; outbreak investigations. Moreover, the course focuses on providing an understanding of the evolution of public health, so that the students realize the global nature of the discipline, the way historical events and threats have shaped it, and its significance for identifying solutions for public health issues.

Biology 420: Environmental Health and Toxicology

This is a required course for all Biological Sciences majors. This course explores the structure and function of ecosystems, the relationship people have with their environment, the risk management choices made, and the resulting associations that affect health and physical well-being for the individual, communities, and susceptible populations. Additionally, it focuses on describing the body’s response to drugs, foods, and toxic substances and it examines the biological responses to acute and chronic exposure to environmental, dietary, occupational, and pharmaceutical stress factors. The goal of this course is to provide students with information about the fundamental principles of organization and function of earth’s terrestrial and aquatic ecosystems, the effects of human activities on ecosystems functions, and the ways environmental factors impact health outcomes, and the control measures currently used to prevent or minimize the health effects from these negative impacts. Additionally, the course focuses on developing an understanding of how the body’s biochemical and physiological mechanisms operate to manage exposure to toxins, poisons, and drugs.

Biology 430: Biotechnology Principles and Applications

This course introduces the technology currently used in the analysis and engineering of genes. It also introduces the principles of allied technologies (proteomics, transcriptomics, and cell culture) and exposes students to industry through a site visit to a biotech company and provides an introduction to the use of a model-guided design for experimentation in biotechnology. Upon completion of this courses students will be able to understand modern biotechnology methods used to introduce genes in bacteria, plants and animals. Integrate principles of proteomics, transcriptomics and cell culture and understand their utility and applications in industrial biotechnology. Appreciate the reasons for experimental repetitions and replicates and the importance of appropriate statistical analysis for interpretation of experimental data. Gain practical knowledge of recombinant DNA techniques and basic protein isolation and characterization techniques. Gain an appreciation of the interdisciplinary nature of modern laboratory-based biological tools and techniques.

Biology 450: Immunology

This is a required course for all Biological Sciences majors. The course is designed to introduce students to the study of the molecular and cellular interactions and principles of the immune system. Topics such as immune system organization and development, humoral & cell-mediated immunity, immunodeficiency, and autoimmunity will provide the students with a broad body of interdisciplinary concepts related to homeostasis at the systemic level. Upon completion of this course the student will have a thourough understanding of immuno- logical responses to disease factors. Students will learn about the organization, structure, and function of the immune system, how it can fight infection and why in some cases an immune response can fail. In addition, the course focuses on describing the type of immune responses activated by different kinds of factors, and how infectious agents can overcome the natural immune response and cause disease.

Biology 493: Thesis I

This course is the first half of a year-long capstone project, concluding the students’ four-year learning experience in the Biological Sciences program. It is designed to foster research, autonomy and synthesis of concepts and skills acquired in all other courses. The first half of the capstone project (SNCB 493) is devoted to research/analysis and design, while the second semester counterpart (SNCB 494) places emphasis on implementation, experimental validation, thesis writing and final project presentation. This course will provide students with an opportunity to work in a guided but increasingly independent fashion, to explore a particular problem in depth, to make practical use of principles, techniques and methodologies acquired elsewhere in the course. To challenge students to form a scientific thesis, carry out a sustained piece of individual work to prove or disprove it, and to present their project work in a dissertation. To enhance communication skills, both oral and written.

Biology 494: Thesis II

The module is the second half of a year-long capstone project, concluding the students’ four-year learning experience in the Biological Sciences program. It is designed to foster research, autonomy, and synthesis of concepts and skills acquired in all other modules. The first half of the capstone project (SNCB 493) is devoted to research/analysis and design, while the second semester counterpart (SNCB 494) places emphasis on implementation, experimental validation, thesis writing, and final project presentation.

Chemistry

Chemistry 117: General Chemistry for the Biological Sciences

This course is designed to introduce biology students to the fundamental principles of chemistry. Topics to be covered include atomic structure, chemical equations, the periodic table, chemical bonding and intermolecular interactions, thermochemistry, reaction spontaneity, reaction rates, chemical equilibria, acid base chemistry and reactions in aqueous systems. Emphasis will be given to applications of chemical principles in biological systems. Students will develop an understanding of: Atomic structure and chemical properties of elements; Chemical reactions and reaction stoichiometry; Nature of chemical bonding and molecular shape; Significance of intermolecular forces; Thermodynamics of chemical reactions; Chemical kinetics, chemical equilibria, reaction rates, Acid base chemistry, and Buffers, acid base equilibria.

Chemistry 215: Organic Chemistry I

This course is designed to introduce students to the fundamental principles of chemistry of carbon-containing compounds, including three-dimensional structures, chemical properties and methods of structural dentification, reactions, and syntheses. Topics to be covered include, stereochemistry, and functional group characteristics of alkanes, alkenes, alkynes, alkyl halides, alcohols, and ethers, with an emphasis on reaction mechanisms and multi-step syntheses. Co-requisite: Chemistry 215L

Chemistry 216: Organic Chemistry II

This is a required course for all Biology majors. It continues Organic Chemistry I. It is designed to introduce biology students to the basic concepts in organic chemistry in order to better comprehend related subjects such as Biochemistry, Biotechnology and Environmental Health and Toxicology. Elucidate reaction mechanisms using curved arrows for reactions of ethers, conjugated systems, and aromatic compounds. Assign the stereochemistry of more elaborate organic compounds. Explain the mechanisms of reactions of condensations and alpha substitutions of carbonyl compounds. Describe and explain the reactivity of amines and carboxylic acid derivatives toward a selection of reagents. Discuss the use of NMR, IR, and MS in the elucidation of organic structure. Emphasize on applications of chemical principles in biological systems. Co-requisite: Chemistry 216L

Ecology

Ecology 110: Ecological Principles

The goal of the course is to introduce students to general ecology. It focuses on major ecological concepts in order to provide students with a robust framework of the discipline upon which they can build. Each discussion is organized around two or four major concepts to present the student with a manageable and memorable synthesis of the lecture and it is supported by case histories that provide evidence for the concept and introduce students to the research approaches used in the various areas of ecology. Special emphasis to local environmental problems countries face and the approaches they use in solving these problems. Laboratory included. May be taken as a Natural and Physical Science GER.

Nutrition

Nutrition 130: Fundamentals of Human Nutrition

The course explores basic concepts of the science of nutrition. Topics include description and role of nutrients, their dietary sources and their fate into the human body (digestion, absorption etc.); energy balance and weight control; eating disorders; nutrition at different developmental stages (childhood, pregnancy, lactation, old age); nutrition in the development/ prevention of human diseases. Emphasis will be given in the use of scientific methodology to explain how nutrients and other food constituents contribute to proper growth, development and health. (4 credits)

Physics

Physics 120: University Physics I, for Science & Engineering

This course is designed to introduce students to the fundamental principles of Mechanics. Topics to be covered include Dynamics, Work, Kinetic and Potential Energy, Systems of Particles, Momentum, Collisions, Rotation, Torque and Angular Momentum, Statics. As far as specific Systems and Force Laws we will look at Fluids, Oscillations, and Gravity. May be taken as a Natural and Physical Science GER.

Physics 121: University Physics II, for Science & Engineering

This course is the second of a two-semester sequence of college Physics courses for students in the sciences and engineering.
Topics to be covered include electric fields and Coulomb’s Law, Gauss’ law, capacitors, resistors and DC electric circuits, magnetic fields, induction and the basic properties of electromagnetic waves. In this course, we want you to learn how to analyze mechanical systems using Newton’s laws. In particular, you should learn to: Describe wave motion graphically and algebraically, apply calculus to the study of waves, identify the electric forces acting on a charge, and work with systems of charges, learn and work with the concept of the electric field for point charges and extended bodies, understand the principles Gauss’ law and the work with calculus to do this, work with electric potential for systems of charges and extended bodies of charge, understand capacitance and how charge and energy are stored in such devices, understand resistance and know how to work with simple DC networks of resistors, be able to work with small combinations of resistors and capacitors (RC circuits), work with the forces on charges and current elements in magnetic fields, know how moving charges and current elements produce magnetic fields, be able to work with changing magnetic field fluxes which induce EMF’s (Faraday’s law), work with the inductance of a coil.