Online data science degree

This course introduces practices in data analytics foundational to the industry and the field of data analytics. Covered are theories of analytics, the phases of the analytics lifecycle, analysis and exploration of data, relevant statistics for data modeling, data visualization, and the tools used for data analytics.

This course provides students with a basic understanding of programming development practices. Concepts covered include the application of algorithms and logic to the design and development of procedural and object oriented computer programs to address the problem solving requirements associated with business information systems. This course will cover procedural programming concepts, including data types, controls structures, functional decomposition, arrays, files, classes, and objects.

This course covers the three most popular data programming languages: Python, Java®, and Ruby. Students will be introduced at a high level to the programming languages as they relate to database design, development, and management.

This course provides an overview of advanced spreadsheet functions used in data analysis. Topics include filters, sorts, lookups, formulas, functions, macros, pivot tables, graphs and charts, dashboards, forms, reports, queries, statistical analyses, and data validation.

This course provides a foundational workshop on data structures, which is a functional component of business intelligence (BI) within an organization. Building upon basic programming and database structure, this course builds competencies for the student to recognize the structure of data contained in deployed enterprise information systems.

This course provides an introduction to the Python programming language. Students will review the function and use of variables, data types, lists, tuples, functions, classes, files, exceptions, search/sort algorithms, memory management, and code testing. Additional topics may include Integrated Development Environments (IDEs), data visualization, global data sets, and Web Application Programming Interfaces (APIs).

This course covers fundamental database concepts including SQL, non-relational databases, distributed databases and database architectures. Students are provided an overview for how to manage, display, sort, group, retrieve, and organize data for the application or tool associated with the software development taking place within an organization

This course provides an overview of R, which is a programming language commonly used for data science, statistical analysis, and data visualization. Topics include syntax, variables, operators, functions, data structures, statistical data sets, and graphical presentation.

This course provides an overview of applied business research, statistical tools, and data analytics used to support strategic decision making. Students will examine methods used to frame business problems, conduct research, collect and evaluate data for validity and reliability, determine patterns and trends in performance, and effectively present conclusions.

Structured Query Language (SQL) is a domain-specific language used to store, query, and manipulate data within databases. This course provides an overview of SQL and relational database applications with a focus on SQL syntax, data types, keywords, functions, structured and unstructured data, and data modeling.

This course provides an overview of database administration, including database implementation, configuration, authentication, monitoring, backup, and security. Students will examine database architecture with a focus on business requirements, data integrity, and the ethical handling of private data.

This course provides an overview of Exploratory Data Analysis (EDA), including the cleaning, preparation, exploration, and visualization of data. Students will review machine learning algorithms, neural networks, and Artificial Intelligence (AI) concepts used to analyze data sets and build intelligent applications.

This course will introduce students to data analytics and modeling through contemporary business tools. Students will examine how data is architected and organized. After completion of this course, students will be able to understand the different data models used to store data, several schemas that drive how data is structured, and provide other database concepts relating to the design and architecture of data.

This course covers data mining techniques for structured and unstructured data. Learn programming techniques and algorithms to transform large quantities of data into usable Business Intelligence (BI).

This course introduces students to tools and techniques needed to present data, both simple and complex, to gain support and recommend business decisions. Student will use graphical tools such as graphs, animation, and presentation techniques to communicate the message behind the data and improve decision making. Topics include requirement gathering, graphical representation of data sets, visualization techniques and tools, and data validation.

This course reviews the origin and applications of big data within the framework of current businesses. Topics include data validation, processing, and predictive analytics used in a timely manner to make informed decisions.

This course provides an overview of machine learning, including the use of algorithms, neural networks, and supervised, unsupervised, and reinforcement learning to automate advanced computer tasks.

This course provides an overview of predictive modeling techniques, with a focus on statistical analyses, data mining, and machine learning tools used to find patterns and trends, identify potential risks, and forecast probable outcomes within various data sets.

This capstone course combines the skills and applies the knowledge from various courses in the Bachelors of Science in Data Science program. Student teams working with large data sets combine the concepts of statistics, programming, data mining, data analysis, and data visualization to design, implement, and present a data science project representing a real-world application to decision-making executives.

This course transitions students through the foundations of study at University of Phoenix. Students develop personal strategies for achieving educational goals and develop skills in critical thinking, collaboration, and communication.

The course introduces theories and concepts in psychology that will foster academic success and provide students with opportunities to synthesize and apply that knowledge.

This course develops the reading, writing, and critical thinking skills that are essential for academic and life success.

Students learn how to think critically, focusing on developing the necessary tools and skills to analyze problems, make decisions, and formulate well-supported points of view on key academic, social, and professional issues.

This course introduces students to thinking about and working with numbers by examining the day-to-day and societal importance of money.

This course extends practice in critical reading, writing, and thinking. Emphasis is given to developing an effective writing process that takes into account audience and rhetorical purpose.

This course provides an applied approach to team building, collaboration, and conflict resolution. Students must understand and apply these concepts within academic and professional settings. Students develop structures, processes, and strategies to create and maintain effective teams. Gender, cultural, and individual considerations in team dynamics are also explored.

This course provides an overview of the key components of comprehensive wellness. Based on a preventive model, the course will allow learners to explore choices that promote wellness with goals of living longer and better.

The course provides an introduction to the most prominent forms of media that influence and impact social, business, political, and popular culture in contemporary America. It explores the unique aspects of each medium as well as interactions across various media that combine to create rich environments for information sharing, entertainment, business, and social interaction in the United States and around the world.

This in-depth environmental science course examines how people use science to understand how they relate to the environment. The course explores relationships between people and ecosystems, and the science behind how ecosystems work. It reviews the historical development of the environmental movement, interactions between humans and natural ecosystems, and more specifically, the role of a growing population and associated pressures on natural resources. This course further examines how economics, natural systems, and conservation are interrelated. The many forms of pollution as well as types of energy resources are addressed. This course challenges students to consider the impact of lifestyle choices on environmental sustainability.

Students apply advanced quantitative reasoning skills to solve real-world problems. This course emphasizes modeling skills, statistical methods, and probability to create, analyze, and communicate solutions.

This applications-driven course prepares students to critically analyze and solve problems using quantitative reasoning. Students approach real-world scenarios using numerous reasoning skills and mathematical literacy to draw conclusions.

This course covers Distributed Database Management System (DDBMS) architectures, data structures, schemas and standards, in addition to centralized and client server systems, server system architectures, parallel systems, and distributed systems.

This course addresses the main standards for data integration, movement or replication and federation. Students will investigate transparency and emulation, cleaning, archiving, and information preservation across systems.

This course is a study in Java programming. It covers topics around Java programming, variables, expressions, using branches and loops, storing data in arrays and using methods.

This course covers prepping, cleaning, organizing, and augmenting data for analysis. Students learn how to prepare data by cleaning it, creating the necessary variables, formatting all variables, transcribing data, adjusting data that requires weighting, scale transformations, and selecting the data analysis strategy.

This course explores the recent technological advances associated with digitized data flows, which have recently opened up new horizons for AI. Students will gain insight into some of the areas of application of Big Data in AI, including robotics, home automation, health, security, image recognition and natural language processing.

This course is an advanced study in Java™ programming. It covers topics around advanced Java™ class design, object-oriented design principles, threads, concurrency, localization, and accessing database applications. These topics are closely aligned with the Oracle® Certified Professional Java™ SE examination.

This course examines traditions and developments in the visual and performing arts including music, dance, theater, cinema, visual arts, and architecture. Students will be introduced to the elements of each genre, along with an overview of its historical development in Western European tradition.

This course covers the skills necessary for effective written and oral communication in the work environment and in modern society. The course reviews basic communication theories and discusses the fundamentals of interpersonal, written, and oral communication skills. This course emphasizes applying these theories and skills to group processes and professional situations.

This course introduces the basic concepts of human nutrition to highlight ways that students can integrate healthy nutrition into their lifestyles. Principles of digestion and absorption, the function of nutrients, lifecycle nutrition practices, disease prevention, diet modifications, and weight management are covered. Practical application of these principles to the students' lives is emphasized.