Information Technology – Data Analytics Specialist

In this course, students will explore the fundamental aspects of information technology. Students investigate basic hardware systems, various operating systems, important software packages, networking fundamentals, basic internet technologies, and essential problem solving techniques. Upon completion of the class, students are prepared to utilize their IT skills to work effectively in IT-related tasks.

In this course, learners are introduced to the interconnection of data, people, processes and things that forms the Internet of Things (IoT). Learners will differentiate among smart devices, connected devices, and Internet of Things (IoT) devices. Machine-to-machine (M2M), machine-to-people (M2P), and people-to-people (P2P) connections in an IoT solution will be examined. Security concerns that must be considered when implementing IoT solutions will be investigated. Upon completion of the course, learners will be able communicate with data over networks to IoT frameworks.

Students will learn how to maintain security in the workplace. Security plans will be created based on, but not limited to, ten key security technologies: access control, network security, management security procedures, systems development security, cryptography, security models, operations security, disaster recovery, laws and ethics, and physical security.

In this course, students investigate the fundamentals of computer programming using the Python programming language. Students examine data types, variables, conditional statements, looping, array structures, and structured programming techniques. Upon completion of the course, students will be able to use Python to apply problem solving skills to create applications for delivery to various platforms.

This course is intended to develop analytic reasoning and the ability to solve quantitative problems. Topics to be covered may include: construction & interpretation of graphs; descriptive statistics; geometry & spatial visualizations; math of finance; functions and modeling; probability; and logic. Appropriate use of units and dimensions, estimates, mathematical notation, and available technology will be emphasized throughout the course.

In this course, students will learn the basic concepts of data analysis and how they are used to drive business processes. Students will learn to identify and retrieve relevant data sources, and to prepare data for analysis with pre-configured and custom tools. Upon completion of this course, students will be able to prepare data for further analysis to drive decision making for business.

In this course, students explore concepts, design, documentation, and implementation of various database systems, including proprietary and open source technologies. Students implement Structured Query Language (SQL) to store, retrieve, and manipulate data. Students create queries, normalize database structures, and create stored procedures. Upon completion of this course, students will be prepared to develop and maintain databases used in application development.

This course is designed for learners to develop knowledge and skills in all aspects of the writing process. Planning, organizing, writing, editing and revising are applied through a variety of activities. Students will analyze audience and purpose, use elements of research, and format documents using standard guidelines. Individuals will develop critical reading skills through analysis of various written documents.

In this course, students explore information systems and their role in organizations. They examine management decision support systems, system analysis and design methodologies, information processing technologies, and their role in decision making. Students will explore tools and techniques for supporting and executing organizational processes. Upon completion of the course, students will work as a team to design an information systems solution to meet a specific business need.

Students taking Introductory Statistics display data with graphs, describe distributions with numbers perform correlation and regression analyses, and design experiments. They use probability and distributions to make predictions, estimate parameters, and test hypotheses. They draw inferences about relationships including ANOVA.

In this course, students will build upon the skills learned in Data Analytics 1. Students will learn to work with large data sets and organize that information for effective data analysis. Students utilize commercial data analysis software packages, and create custom computer programs to analyze data. Upon completion of the course, students will be able to perform analysis of relevant data with various software tools, and use the generated information to help make informed business decisions.

Please complete 809-143 Microeconomics or 809-195 Economics. This is for informational purposes only. Once you register for your course, you can delete this block from your timeline.

In this course, students continue working with IoT devices. Students connect devices and analyze firmware and software for weaknesses. Students research and perform upgrades to IoT devices. After upgrading the IoT devices, the students secure these devices by applying industry best practices. This may include changing firewall settings or remote access settings. Upon completion of this course, students can recognize, update and secure IoT devices.

In this course, students will learn to use the R programming language to analyze data. Students will learn the syntax and data structures of the R language, and how to apply the language to perform traditional statistical analysis, such as means testing, variable correlations, and linear regressions. Upon completion, students will be able to create R programs to process data and create meaningful output rooted in sound statistical techniques.

The student will prepare and present oral and written technical reports. Types of reports may include lab and field reports, proposals, technical letters and memos, technical research reports, and case studies. This course is designed as an advanced communication course for students who have completed at least the prerequisite introductory writing course.

In this course, students will learn to organize, manage and analyze very large data sets from various sources. Students will use software tools to present complex data in visually meaningful representations that can be communicated to business stakeholders. Upon completion, students will learn how to transform raw data into meaningful information that will be utilized for data-driven decision making.

In this course, students apply data analysis techniques to a real world project. Students will interface with a client data source and prepare the data for analysis to help determine the outcome a industry problem that needs to be solved. Upon completion of this course, students will work in teams to create visualizations, gather business intelligence information, and provide structured data to assist in making a business decision.

This course focuses upon developing speaking, verbal and nonverbal communication, and listening skills through individual presentations, group activities, and other projects.

This course introduces students to some of the major theories and topics of psychology, including the physiological basis of behavior, personality and learning theories, memory, states of consciousness, stress, research methods, intelligence, human development, psychopathology, and social behavior.