Apply analytics to solve real-world problems with a data science degree

This course prepares students to be successful lifelong learners both academically and in their chosen careers. Franklin courses require a high level of self-directed learning and focus on the skills required in the workplace and the classroom that are easily transferrable between the two environments. The course includes strategies for time management, goal setting, reading comprehension, and advancing communication skills, including the use of electronic tools to participate in virtual environments.

This course prepares students to be successful lifelong learners both academically and in their chosen careers. Franklin courses require a high level of self-directed learning and focus on the skills required in the workplace and the classroom that are easily transferable between the two environments. The course includes strategies for advancing communication skills, including the use of electronic tools to participate in virtual environments. The assignments and activities in the course are created to closely simulate teamwork found in the workplace.

By using applied critical and creative thinking, students in this course will develop a set of communication skills that will enhance their personal and professional relationships and endeavors. This course will focus on skill development in key areas such as self, perception, listening, verbal messages, conversations, relationships, conflict management, persuasion, and presentation skills.

This basic public-speaking course intends to improve the student's ability to think critically and to communicate orally. Theory and practice are provided in various speaking situations. Each student is required to speak before an audience, but class work also involves reading, gathering and organizing information, writing, and listening.

This is an intermediate course focusing on the composition of research papers. Students in this course prepare to be active participants in professional discourse communities by examining and practicing the writing conventions associated with their own fields of study and work. By calling attention to the conventions of disciplinary writing, the course also prepares students for upper-division college writing and the special conventions of advanced academic discourse. Course activities include three extended research papers, semi-formal writing addressing interdisciplinary communication, and readings fostering critical engagement with disciplinary conversations.

This course focuses on using spreadsheets to solve business problems.

This course introduces you to statistics with applications to various areas. The course covers both descriptive and inferential statistics. Topics included are: sampling techniques, data types, experiments; measures of central tendency, measures of dispersion, graphical displays of data, basic probability concepts, binomial and normal probability distributions, sampling distributions and Central Limit Theorem; confidence intervals, hypothesis tests of a mean, or a proportion for one or two populations, and linear regression.

This introductory course focuses on applying information technology to business strategies using databases. The student will gain a working knowledge of current database technology, including relational database concepts, database design, data extraction, and data warehousing while working with database applications.

This course introduces data analytics using Structured Query Language (SQL). Students will learn how to apply SQL in data exploration analysis and business problem-solving.

Many organizations today utilize computers and information systems to store, organize, analyze, and summarize data to solve problems. As a result, computing is a tool that can benefit students in many different fields. At the heart of solving problems with computers is the study of structured thinking using algorithms. This course is designed for students with no prior programming experience and teaches the building blocks of algorithms, including variables, expressions, selection and repetition structures, functions and parameters, and array processing.

This course introduces the fundamentals of Business and Data Analytics. Students will learn business problem framing, data wrangling, descriptive and inferential statistics, data visualization, and data storytelling in analytics.

This course introduces data visualization fundamentals using the leading visualization tools in the industry and focuses on project-based learning. Students will learn how to develop dashboards and discover insight effectively based on data.

This course introduces the principles of analytics modeling. Students will learn exploratory data analytics, regression, classification, clustering, model interpretation, and model evaluation.

Students will learn the basic concepts behind major machine learning algorithms, the essential steps for creating a typical machine learning model, the strengths and weaknesses of different algorithms, and the model evaluation using different performance metrics. Eventually, students will be able to build a prediction model by machine learning algorithm using Python language. The common problems in practical machine learning exercises and their solutions also will be discussed.

This course covers advanced analytics topics, including big-data analytics using popular platforms, model interpretation strategies, simulations, optimizations, and analytics reporting and presentation methods. A discussion of ethical considerations for model evaluation is also included.

The purpose of this capstone course is to assess students' ability to synthesize and integrate the knowledge and skills they have developed throughout their coursework. The course provides students with the opportunity to demonstrate competency in the key domains of analytics through a comprehensive project that includes problem framing, data preparation, data visualization, data analysis, model development, model interpretation, and report presentation

This course introduces fundamental concepts from calculus and linear algebra providing foundations for mathematical modeling. It also covers some statistics topics beyond an introductory level including several discrete probability distributions, and continuous probability distributions with a calculus lens. The focus is not on proof nor on excessive hand computations; instead, it is on employing and relating mathematics to real-world situations. Concepts are made concrete through visual and numerical computation with the help of programming tools.

This course is a breadth-based cybersecurity course for non-technical majors. It aims to equip a bachelor?s degree seeker with no prior cybersecurity knowledge, other than what the newspaper reports say, with essential cybersecurity knowledge. The course introduces organizational, people, and technological aspects of cybersecurity. More specifically, it covers (1) governance, standards, and risk management topics in the organizational domain, (2) security awareness, privacy, ethics and cyber threats in the people domain, and (3) cyberspace, critical sectors, and emerging topics in the technological domain.

This course serves as an introduction to the function, design, administration, and implementation of computer networks. Topics include network infrastructure, architecture, protocols, applications, and the OSI networking model. Note, this course has proctored exam(s).

This course introduces the essential general programming concepts and?techniques to analytics students. The goal is to equip the students with the?necessary programming skill in analytics problem-solving. Topics include?boolean, numbers, loops, function, debugging,?Python's specifics?(such as NumPy,?Pandas,?Jupyter?notebook), R's specifics?(such as list,?data frame, factor, apply,?RMarkdown),?the process of?data retrieving, cleaning,?integrating, transforming, and enriching to support analytics.

This?course covers fundamental methods and?widely-used technologies?in?data engineering. Topics include application programming interface (API),?web scraping, Extract Transform Load (ETL), and analytics at-scale using?PySpark.?

This course explores the concepts of cloud computing, including financial impacts and business value, financial requirements, deployment, risks, and security. Hands-on exercises help students to gain experience with cloud computing environments, identifying technical and security requirements for given deployment scenarios, implementing the proposed cloud deployment scenario, and troubleshooting technical issues of existing cloud computing scenarios.

This course provides a conceptual survey of general systems theory followed by a conceptual and technological survey of the structure of distributed information systems architectures, operating systems, network operating systems, peripheral technology and user interfaces. Interoperability between these architectural components will be explored and current technology and trends in each architectural element will be reviewed. This course will de-emphasize, although not ignore, mainframe architectures in favor of information architectures more applicable to client/server computing. The various interacting categories of client/server computing as well as the benefits and implications of such a system will be fully explored.

This course provides an introduction to the concepts of information technology project management and techniques for initiating, planning, executing, monitoring, and controlling of resources to accomplish specific project goals. Both technical and behavioral aspects of project management are discussed. While the focus is on information technology projects, the principles follow the nine project management knowledge areas obtained in the Project Management Institute's?PMBOK?Guide, Third Edition?and, thus, are applicable to the management of any project. Topics will include integration, scope, time, cost, quality, human resource, communications, risk, and procurement management. Project management software utilization is emphasized.

Upon successful completion of this course, students will be able to design and implement data gathering processes and data warehouse architectures appropriate for supporting data mining and business analytics modeling applicable to the solving of typical operational, supply and demand problems encountered by organizations. Learning will be supported by relevant texts, lectures, research papers, collaboration sessions and projects, both individual and team-based.

This course is an introduction to financial and managerial accounting. It is designed for non-accounting majors. Financial accounting emphasizes how general purpose financial statements communicate information about the business's performance and position for users external to management. It emphasizes how the accountant processes and presents the information. The course also examines the major elements of the financial statements. The managerial accounting portion of the course studies internal reporting and decision-making. The course assists those who wish to learn "what the numbers mean" in a clear, concise and conceptual manner without focusing on the mechanical aspects of the accounting process.

A study of the everyday legal problems encountered in business with emphasis on the areas of legal procedure, contracts, agency, employment law, business organizations and torts, with cases relating to these and other areas.

An introduction to economic theory involving the examination of how decision making by firms and individuals is shaped by economic forces. Emphasis is placed on demand, supply, market equilibrium analysis, and basic market structure models. The invisible hand as the driving force for economic decisions as well as market externalities are discussed. The class concentrates on providing a balanced approach to studying economic agents' behavior and the global implications and outcomes.

This course is designed to survey the field of finance and provide the foundation for more advanced finance coursework. Topics include sources of business and financial information, financial statement analysis, the time value of money, the nature and measurement of risk, financial institutions, investments and corporate finance.

This course explores the basic concepts and processes of management. Students will explore the functional roles and processes of planning, leading, organizing, and controlling comprising the manager role. Students develop skills related to the manager function that are required in today's competitive environment.

Theory, strategies and methods are foundational to the informed practice of marketing. Students investigate the importance of marketing to an organization or cause, the interrelationship of the difference phases of marketing, the marketing of goods versus services, analysis and identification of markets, pricing strategies and digital marketing tactics.

This course will provide fundamental information regarding health, healthcare, and the healthcare delivery system. Students will become familiar with the various types of healthcare organizations, stakeholders, and healthcare issues in order to shape their understanding of the different components of the healthcare delivery system. Through the exploration of health information, students will discuss and analyze the role healthcare professions play within healthcare.

This course will introduce the foundations of medical terminology nomenclature and use. Emphasis will be on the fundamentals of prefix, word root, and suffix linkages to build a broad medical vocabulary.

Students are introduced to the roles of the health information management (HIM) professional in a variety of healthcare settings. The educational and credentialing requirements for the HIM professional will be discussed along with an overview of the U.S. healthcare delivery system, and the various reporting and accrediting requirements.

This course introduces students to various types, definitions, relationships, uses, and interpretations of data derived from healthcare functions and processes. Students will explore information standards and representations of health data that are commonly used for patient care, reporting, reimbursement, and quality improvement programs.

This course will cover the history of health informatics, design and challenges of informatics infrastructure, and current issues. Topics will include HIPAA and other legislation, application of electronic health records, and other clinical and administrative applications of health information systems.

This course examines healthcare organizations from the perspective of managing the information systems that exist within the enterprise. Identifying the clinical and healthcare delivery processes and how they relate to information systems is a main focus. The intent of the course is to identify the key issues confronting the management of healthcare information systems today, examine their causes, and develop reasonable solutions to these issues. Specific federal regulations, vendor solutions, and financial implications as they relate to healthcare information systems are also examined.

This course will require the student to apply Health Information Management software, tools, and techniques to authentic healthcare situations and problems. Emphasis will be on the applications of electronic health records, common data tools and reports, and the appropriate analysis for decision-making.

Understanding cultural competency, ethics, policy, and law is necessary for healthcare professionals in a continuously evolving healthcare system. This course will provide students with practical knowledge and methods for applying ethical, legal, and cultural decision-making frameworks to mitigate risks. Topics will include regulatory compliance, patient consent, privacy and confidentiality, and cultural competence.