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MAT 195 Calculus I for Business, Business Information Systems, and Economics
Prerequisite: Placement at this level, MAT 099, or SAT 510+
4 credits
LAC T1M-Mathematics
This course blends topics form Precalculus and Calculus, focusing specifically on the skills and applications necessary to support students' majoring in Business or Economics. This course offers just-in-time algebra support. Precalculus topics include the study of functions, domain and range, polynomial, rational, radical, exponential, and logarithmic functions. Calculus topics include an introduction to limits and continuity, rates of change, the definition of the derivative, and techniques of differentiation of linear, polynomial, exponential, logarithmic, and rational functions. The course will include applications of the derivative to solve applied problems in the fields of business and economics. Characteristics of functions such as intervals of increase or decrease, concavity, extrema, and end behavior will be studied as a means to describe, reason, interpret and analyze relationships. The course concludes with an introduction to integration. Use of an approved graphing calculator is required thoughout the course. This course is intended for students majoring in Business or Economics and cannot be substituted for MAT 243 Calculus I with technology.
MAT 243 Calculus I with Technology
Prerequisite: MAT 155/155P or Placement at this level
4 credits
LAC T1M-Mathematics
A first course in calculus with a focus on differential calculus. Topics include the study of limits, continuity, rates of change, the definition of the derivative, indeterminate forms, and techniques of differentiation of linear, polynomial, exponential, logarithmic, rational, and trigonometric functions. The course will include applications of the derivative to solve applied problems. Characteristics of functions such as intervals of increase or decrease, concavity, extrema, and end behavior will be studied as a means to describe, reason, interpret, and analyze relationships. The course concludes with an introduction of antiderivatives. Use of an approved graphing calculator is required throughout the course.
MAT 216 Statistical Data Analysis
Prerequisite: LAC student with T1M or GER student with IIIA or SAT 550+
3 credits
LAC T2IT-Applied Info Tech
Multidisciplinary, data-driven course in applied statistics. Topics selected from exploratory data analysis (tables, graphs, central tendency and variation), correlation and regression, probability and statistical inference (confidence intervals and hypothesis testing). Emphasis placed on interpretation and analysis of real-data sets. Use of statistical computing software is integral to the course.
*MAT 315 Applied Probability And Statistics
Prerequisite: MAT 244 or (T1M & CSC 202)
Stage 2 Writing Intensive for Mathematics majors
4 credits
This course covers applied probability and statistics (both descriptive and inferential), including random variables and their distributions, and applications of standard statistical techniques. Descriptive statistics include appropriate graphic displays, measures of center and variability, correlation and regression as well as proportions and analysis of two-way tables. Significance tests include t-tests and chi-square tests. The role of historical figures in the development of probability and statistics (e.g. Bayes, Bernoulli, Gauss, Pearson, Tukey) is discussed. Focus will be on a concept development (including simulation and derivation), and analysis and interpretation of real data. Analysis/ computation is facilitated by statistics and mathematics software. A data-based research project culminating in a technical report is an integral component to the course.
ECO 215 Statistics For Business And Economics
Prerequisite: LAC student with T1M course or GER student
Note: Not open to math majors. Not open for credit to students who have passed MAT 315.
LAC T2IT-Applied Info Tech
3 credits
A practical course in statistics with applications to economics, business and science. Emphasis placed on probability, probability distributions, statistical inference, correlation and regression.
MAT 342 Explorations in Data Science
Prerequisites: MAT 315 or MAT 216 or ECO 215 or approved statistics course
3 credits
This course provides and introduction to the interdisciplinary field of data science. The emergence of massive datasets from diverse areas such as telecommunications, large-scale retailing, astronomy, sports, medicine and social media provide the primary impetus for the field. This course will emphasize practical techniques that include cleaning and transforming data, exploring/ analyzing data, statistical inference, creation of statistical models, and communicating results. R programming language will be used for data manipulation, visualization, and analysis.
CSC 202 Introduction to Programming and Machine Intelligence
Prerequisite: T1M course
LAC T2IT-Applied Info Tech
3 credits
Machine Intelligence is the sub-discipline of computer science concerned with the automation of tasks which have, traditionally required human intelligence. The course provides an overview of the current state of the art, and provides instruction in the technologies and techniques required to utilize or develop new intelligence-based systems. Students will gain hands-on experience writing computer code using modern scripting languages (such as Python) and using cloud-based services to create sample intelligent applications that access and analyze information to solve problems. Since these technologies can greatly amplify the influence of any one person the societal impacts and ethical issues regarding the design and application of the technology will be discussed.
*CSC 203 Advanced Programming for Data Science
Prerequisite: CSC 202 or CSC 210
3 credits
This course covers the concepts of object-oriented programming, data manipulation, and data visualization that are commonly used in data science applications, using modern scripting and programming languages such as Python, R and Java. This course introduces students to fundamental object-oriented programming concepts, such as classes and inheritance; software design considerations such as exception handling; and theoretical and applied frameworks used for data storage, manipulation, and visualization.
Management Of Business Information
Prerequisite: LAC student with T1M course or GER student
LAC T2IT-Applied Info Tech
3 credits
The course introduces the use of information technology for ethical problem solving and decision-making across all major functions of organizations. Particular attention is given to the critical analysis, organization, communication and presentation of information for organizational planning and control, with critical reflection on project work.
*BUS/BIS 305 Business Analytics
Prerequisite: BUS 205 and Introductory statistics course
3 credits
Business analytics techniques are introduced in this course to assist with making business decisions for a wide variety of business functional areas and processes. This course introduces students to performing conditional analysis, how to use descriptive including basic visualization and pivot tables, predictive and prescriptive analytical tools to solve practical business problems. The course addresses hypotheses testing, forecasting, data modeling, decision analysis, simulation and risk analysis for supporting operational, tactical and strategic problem-solving in business and organizational settings.
EES 300 Basics of Geographic Information Systems
Prerequisite: LAC student with T1M or GER student
3 credits
This course takes a multidisciplinary approach to the concepts, techniques, and current applications of geographic information systems. Students will be exposed to the historical and cultural use of maps and cartography to convey or communicate a message related to geographic information. Students will apply spatial analysis skills to address issues related to environmental management, public policy, health science (public health), and business using state-of-the-art mapping software and visually convey their findings using appropriate cartographic and graphic design techniques. Throughout the semester students will work towards the completion of a project proposal that utilizes geographic information systems to address an issue within each individual's major are of study
EES 301 Introduction to Geographic Information Systems Laboratory
Pre- or Co-requisite: EES 300
1 credit
This course provides further hands-on experience to students interested in the multidisciplinary applications of geographic information systems. Students will learn how to apply the concepts and theories demonstrated in EES 300 to address issues related to environmental management, public policy, health science (public health), and business using state-of-the-art mapping software. Students are required to convey their findings visually using appropriate cartographic and graphic design techniques. A semester project demonstrates the learning objectives of the course by applying the students' knowledge to fulfill the project proposal completed in introduction to Geographic Information Systems (EES 300).
*CSC 341 Database And Information Management
Prerequisite: CSC 270 or instructor’s permission
3 credits
The task of organizing large volumes of information of potentially different kinds is a daunting one. Typically, resolution of the associated problems depends on the use of an underlying database technology, often involving networking. This course and addresses the theoretical, technical and social issues involved, as well as the use of information for intelligent decision-making.
BIS 373 Business Database Management
Prerequisites: BUS 205 or instructor’s permission
3 credits
Provide students an opportunity to acquire and integrate multiple skills sets and knowledge in 1) creating and managing effective databases for businesses and other organizations and in 2) developing and managing databases that meet the needs of modern businesses and organizations in the Internet-Information Age. This course draws upon their Liberal Arts Core courses, skills and experiences as well as their foundational systems development, management, and technical skills acquired in introductory business information systems courses and 3) their foundational business skills of understanding organizational dynamics, needs, constraints and processes. They will invoke and expand their independent inquiry and critical thinking skills in addressing the dynamic data and information needs of businesses, nonprofits and greater society.
*CSC 305 Data Mining and Applications
Prerequisite: CSC 202 or 210
3 credits
Data mining is the process of extraction of implicit, previously unknown and potentially useful information from data. This course provides fundamentals of data mining and knowledge discovery including: knowledge representation, association analysis, clustering, predictive modeling, anomaly detection, visualization and so on. The emphasis will be laid on using techniques in different settings, including business, medicine, science and engineering, rather than developing new techniques or algorithms.
*MAT 343 Explorations in Data Analytics
Prerequisite: MAT 342
3 credits
This course covers advanced analytical techniques students can use in the modeling and evaluation stages of a data science project. Such techniques may include neural networks, k-means and model-based clustering, association rules, segmentation models, and model voting techniques. This course relies on the foundational structure and methodologies established in Explorations in Data Science (MAT 342). Students will complete a group analysis of a data set and present their findings in a lightning talk. Soft skills such as communication and teamwork are built alongside analytical skills.
*BIS 447 Business Intelligence and Data Solutions
Prerequisites: BIS 377 or BIS 373 or BIS 378 or Instructor’s permission
3 credits
The course focuses on utilizing data management and analysis techniques used in organizational decision support and business intelligence systems. This is done by introducing a variety of business-data management techniques and tools including decision modeling utilizing spreadsheets, decision analysis tables, advanced Structured Query Language, online analytical processing, business objects, business data mining for business intelligence, as well as business data warehouse management. Common business decision making and support problems and tasks found in the healthcare and public services sectors such as client management, determining employee skill needs, and relevant general organizational decision support problems in accounting, finance and operations will be used as examples.
* BIS 449 Data Visualization
Prerequisite: MAT 343 or CSC 305 or BIS/BUS 305 or BIS 447
3 credits
In a world of data superabundance, raw data is difficult to understand. Data visualization can reveal or obscure the truth embedded in data. Great data visualizations provide insight into the data, which allows us to see both the expected and unexpected. This course is designed to introduce students to data visualization design principles in order to read, critique, and create effective and beautiful visualizations. This includes story-telling principles in visualization design and presentation.
BIS 377 Organizational Website & Data Management
Pre or Co-requisite: BUS 370
Prerequisite: LAC student with at least two Tier II courses or GER student
4 credits
Provide students an opportunity to acquire and integrate multiple skill sets and knowledge in 1) creating and managing effective databases for business and other organizations; and in 2) developing and managing database driven websites that meet the needs of modern business and community organizations in the Internet Age.
CSC 450 Senior Research
Prerequisite: Senior Standing; and LAC student with at least two Tier II courses or GER student
3 credits
This is the writing course for the major.
It includes project proposals, software proposals, technical writing, semester projects, high-level and new issues in computer science.
LAP 430 Liberal Arts Capstone Colloquium
Prerequisites: LAC student with at least 2 Tier 2 courses or GER student. Senior status required.
3 credits
In this course you will reflect through short essays and a larger summary on your liberal arts coursework and Eastern experiences, develop a five-year professional development plan, discuss in writing and in class a relevant text and create a scholarly, independent inquiry study that may serve as the foundation for your future academic and professional development. You will also be developing an electronic portfolio. This course is also designed as a capstone (Tier III) course for your liberal arts studies and experiences at Eastern and is a writing intensive course.
MAT 244 Calculus II with Technology
Prerequisite: MAT 243
4 Credits
This is the second course in a three semester calculus sequence. MAT 244 focuses on two related topics: methods and applications of integration, and infinite series and representation of functions by power series. Topics in integration include Riemann sums, definite and indefinite integrals, the Fundamental Theorem of Calculus, applications to geometry (area, volume, arc length) and to real-life problems, and techniques or integration. The course concludes with the study of sequences and series, convergence tests, and power series representation of functions (Taylor series). Use of an approved graphing calculator is required throughout the course.
MAT 230 Discrete Structures
Prerequisite: MAT 130 or Placement at this level
3 Credits
A study of discrete structures including sets, relations, functions, graphs, trees, and networks, with some applications (such as modeling or designing data structures). Other topics include propositional and predicate logic, methods of proof (for example direct, indirect, induction), an introduction to permutations and combinations, iteration, recursion, and finite differences. Students will be introduced to writing formal proofs.
MAT 310 Applied Linear Algebra
Prerequisites: MAT 230, MAT 243, MAT 244
3 Credits
This course covers systems of linear equations and matrix algebra with emphasis on applications. Topics include systems of linear equations and their solutions, matrices and matrix algebra, determinants and inverse matrices, vector spaces and subspaces, linear independence, bases for vector spaces, dimension, linear transformations, inner products, orthogonal bases and projections, eigenvalues and eigenvectors. Possible areas of applications include graph theory, coding and curve fitting. Use of technology is integral to the course.
MAT 355 Probability
Prerequisite: MAT 315
3 Credits
This course is a comprehensive introduction to the major ideas of probability, such as independence, conditional probability, mean and variance, and counting techniques. We will consider a range of probability distributions and their properties, including both discrete and continuous univariate probability distributions such as the uniform, binomial, geometric, Poisson, normal, and exponential distributions. We will also consider multivariate probability distributions. Applications to the insurance industry are emphasized throughout the course.
MAT 356 Financial Mathematics
Prerequisite: MAT 244
3 Credits
This course is a comprehensive introduction to the major ideas of financial mathematics, such as the time value of money, annuities and cash flows, loans, bonds, cash flows, portfolios, immunization, interest rate swaps, and determination of interest rates. Applications of the insurance industry are emphasized throughout the course.
MAT 374 Explorations in Topic
Prerequisites: MAT 230 and MAT 244
3 Credits
Each exploration course will focus on an advanced topic in mathematics. The course will provide students with experiences and background that will be helpful if they choose to pursue undergraduate research projects. Possible activities will include but are not limited to group work, projects, portfolios, research, or other activities in line with undergraduate research. Note: Can be taken with different topics up to 5 times for credit.
MAT 480 Independent Studies
Prerequisite: Approval of Department Chairperson and Dean
1 TO 6 Credits
CSC 210 Computer Science And Programming I
Prerequisite: CSC 180 or Tier 1 Math
3 Credits
An introduction to the fundamental concepts of computer science and programming. Topics include data types, control structures, arrays, files, and an introduction to objects as well as debugging techniques and the social implications of computing. The course also offers an introduction to the historical and social context of computing and an overview of computer science as a discipline.
CSC 212 Computer Game Design And Visualization
Prerequisite: LAC Student w/T1M Course or GER student
3 Credits
This course presents the introductory principles of design, application, and implication of computer game design and Visualization systems. The course uses an integrated approach to two-dimensional and three-dimensional graphics. The course gives some introductory principles in the design, use, and understanding of computer game and Visualization systems. The course uses contemporary Computer Game Design and Visualization APIs with high level programming languages to illustrate examples in simple 2D game design.
CSC 230 Discrete Mathematics for Computer Science
Prerequisite: MAT 130
3 Credits
This course covers the mathematical topics most directly related to computer science. Topics include logic, sets, functions and relations, permutations and combinations, counting, proof techniques, mathematical induction, recursive definition, graphs and trees, boolean algebra, logic gates and circuits, and languages and state machines.
CSC 231 Computer Science And Programming II
Prerequisite: CSC 210
This course focuses on the concepts and fundamentals of the object-oriented programming methodology. It provides an introduction to the fundamentals of object-oriented design and the definition and use of classes. Other topics include an overview of programming language principles, human-computer interfaces, basic searching and sorting techniques, and an introduction to software engineering issues.
CSC 270 Data Structures
Prerequisite: CSC 231 and (CSC 230 or MAT 230)
3 Credits
This course is an introduction to the fundamental concepts of data structures and algorithms. Topics include the underlying philosophy of object-oriented programming, recursion, fundamental data structures (including stacks, queues, linked lists, hash tables, trees, searching and sorting algorithms), and the basics of algorithmic analysis.
CSC 335 Algorithm Design And Analysis
Prerequisite: CSC 270 or CSC 330
3 Credits
This course is an introduction to the design and analysis of computer algorithms. The emphasis is on general algorithm design techniques such as divide-and conquer, dynamic programming, the greedy method, and heuristic search. Also emphasized are the applications of these techniques in solving real problems that arise frequently in computer applications. The course will include the analysis of algorithms in terms of time and space complexities. Satisfies the stage 2 writing enhanced requirements.
CSC 301 Advanced Web Development and Web Scraping
Prerequisites: CSC 231, permission of the department chair. Web pages are functional products that provide a service, but also contain rich sources of data that can be collected and analyzed. This course covers the design, development, analysis, and automated browsing of web pages. Specifically, this course teaches students how to build dynamic web pages using HTML, CSS, and JavaScript, and how to use selected web development frameworks. Writing web browser extensions is also discussed. Students will gain experience scraping and parsing web pages in order to answer data-driven questions and to present information in meaningful ways. Finally, students will gain experience with web browser automation for web page testing and for automating web- based tasks.
3 Credits
CSC 315 Genomic Data Analysis
Pre- or Co-requisites: CSC 210
3 Credits
Bioinformatics is an interdisciplinary science that involves the development and use of computational and statistical tools to store and analyze large biological datasets such as genomic sequences and gene expression profiles. This course will cover core concepts in biology, statistics, and programming as related to the analysis of genomic data, with a focus on gene expression data. Students will gain proficiency in (1) programming in R, a statistical computing language, (2) statistical analyses using R and related theory, and (3) the analysis of gene expression data including data processing, identification of differentially expressed genes, clustering, and predictive modeling. The analysis of sequencing data will also be discussed.
CSC 342 Advanced Database Systems
Prerequisite: CSC 341
3 Credits
This class builds on the earlier prerequisite class, CSC 341 Database and Information Management. The intention is to provide a solid foundation in use and management of data in a real world setting. Topics covered included advanced database design, physical database implementation, SQL API Usage, performance monitoring and tuning, advanced SQL, and database data movement and utilities.
CSC 343 Big Data Programming and Management
Prerequisite: CSC 341 and permission of the department chair
3 Credits
The analysis of Big Data - datasets that are too large or complex to be handled using traditional data storage and processing tools - drives discovery and innovation in science and industry. This course introduces students to the challenges posed by Big Data, along with the theory, systems, and algorithms used to manage and process large data sets in a parallel and distributed fashion. Students are exposed to theoretical and applied topics in parallel and distributed processing, data models, scalable computing and programming models, and levels of abstraction for Big Data processing. The course discussed specific platforms and teaches students how to effectively design and develop Big Data applications.
CSC 375 Artificial Intelligence
Prerequisites: CSC 330
3 Credits
A study of goals and methods of artificial intelligence, the area of computer science concerned with designing "apparently" intelligent computer systems. Covers basic problem-solving techniques, knowledge representation, and a brief overview of expert systems. Includes writing of programs in LISP.
CSC 480 Independent Study
Prerequisite: Approval of Department Chairperson and Dean
1 TO 6 Credits
EES 342 Advanced Geographic Information Systems With Laboratory
Prerequisite: EES 130; 224; 340; or EES 300 and EES 301
0 TO 4 Credit hours
This course expands upon students' knowledge and capabilities in the rapidly developing field of Geographic Information Systems (GIS). GIS allows integration of information in ways that promote understanding and assists in addressing evolving global and environmental strains, such as deforestation, urbanization sprawl, disease outbreak, and the effects of climate change. Essential principles and concepts of GIS are expanded beyond those introduced in EES 340 or EES 300/301 with hands-on experience in the industry-standard software, ArcGIS®. The skills training previously attained in the use of ArcGIS software is further developed as emphasis is placed upon concepts and spatial reasoning of the analysis techniques and methods. Completion of this course and mastery of its content will provide students with a thorough understanding of GIS functionality, methodology for implementing the technology, and working knowledge of its applications in environmental earth science and other geographic disciplines.
EES 444 Geospatial Applications Using Remote Sensing
Prerequisite: EES 340 or Instructor consent
3 Credits
This course will be a capstone experience in integrating environmental science courses and applying that knowledge to an environmental problem. Each student will develop a GIS application project and present it in a written, poster, or oral format.
EES 480 Independent Study In Earth Science
Prerequisite: Consent of Instructor and Dept. Chairperson
1 To 6 Credits
Student conducts independent research under the guidance of a faculty supervisor.
EES 491 Internship In Environmental Earth Science
Prerequisite: Consent of Instructor and Dept. Chairperson
Practical experience in earth science working with a government agency or private company under the supervision of an EES faculty member and an agency representative.
1 TO 15 Credits
ACC 310 Cost Accounting Systems
Pre or Co-requisite: ACC 302
3 Credits
Covers fundamental principles and procedures needed for planning, evaluating and controlling the organization's internal activities. Students are exposed to accounting systems that are designed to provide information for managers in a wide variety of organizations as they strive to make decisions regarding budgeting, product pricing, production levels and inventory evaluations. Students learn how to work effectively with accounting information that involves job-order costing, process costing and standard costing.
BUS 346 Investment Analysis
Prerequisite: BUS/FIN 245 or Equivalent
3 Credits
Principles and techniques of investment in securities with a continuous appraisal of the economic setting. The mathematics of investment, the role of investment banking houses, stock exchanges and over-the-counter market, federal and state regulations of trading in bonds and equities.
BUS 360 Supply Chain Management
Prerequisite: BUS 260
3 Credits
Supply Chain Management is a systems approach to managing the entire flow of information, materials, and cash from raw materials, and cash from raw materials suppliers through factories and warehouses to the end-customer. Supply Chain Management represents a philosophy of doing business that stresses processes and integration. This course examines the strategic importance of good supply chain design, planning and operation for every firm. The course covers topics that have become critical to organizations competitiveness such as supplier selection, information technology for supply chain management, development of logistics networks, and coordinated product design.
BUS 363 Introduction To Six Sigma Continuous Improvement
Prerequisite: MAT 216, ECO 215, HSC/HPE 430 or an approved statistics class.
3 Credits
This course is an introduction to the data driven Six Sigma problem solving methodology. The Six Sigma tools and techniques for product and process improvement are covered. The course is structured around the five phases of the DMAIC model for improving quality and performance: Define, Measure, Analyze, Improve and Control. Topics include six sigma goals, lean principles, theory of constraints, design for six sigma, quality function deployment, failure mode and effects analysis, project management basics, data and process analysis, probability and statistics, measurement systems and process capability.
BUS 380 Quality Improvement in Healthcare
Prerequisites: BUS 350
3 Credits
The course includes an overview and basic elements of quality improvement practices in healthcare organizations. The important topics of quality improvements such as PDCA cycle and data analysis for quality improvement in healthcare organizations are analyzed in this course. At the end of the course, the students will be familiarized with methods and techniques used to measure, evaluate and improve the quality of healthcare delivery services.
BUS 428 Marketing Research
Prerequisite: BUS 225
3 Credits
An introduction to the quantitative and qualitative techniques used in marketing research. Emphasis on marketing planning and decision-making. (Required for marketing concentration)
Bus 433 Strategic Talent Management
Prerequisite: BUS 333
3 Credits
Measurement and assessment skills for gathering and analyzing data and information relevant for human resource management, including absence rates, costs per hire, human capital ROI, training investment, human capital value added, turnover rates and costs, etc. with an emphasis on strategic talent management. The focus of talent management will be on selection and training, performance management, and employee development and succession planning.
ECO 305 Introduction To Econometrics
Prerequisite: ECO 200, ECO 201, ECO 215 & ECO 300
3 Credits
An introduction to the statistical methods used to test and measure relationships specified in economic models. Applications in business included.