Data Analytics is used to analyze vast databases that must be examined using complex algorithms and artificial intelligence to identify previously unidentified useful sets of relationships and trends. All aspects of the business and medical communities, as well as government agencies and non-profit organizations rely on data analytics, yet are hampered by a growing shortage of data analysts. Davenport’s 12 credit Graduate Certificate in Data Analytics responds to this need by preparing individuals to conduct data mining projects, generate data visualization products, and build data dashboards and automated reports. Using industry standard software, graduates get hands-on experience in practical applications directly related to current trends and issues that impact organizations across a broad spectrum. Credit from the certificate program can be transferred to the Master of Science in Data Analytics Degree program. Courses for are offered online in 15 week format with two courses completed per semester.
PROGRAM PREREQUISITES: • Completion of a bachelor’s degree from a regionally accredited university • Student must have earned a minimum undergraduate GPA of 2.75 or a graduate GPA of 3.0. • Strong analytical skills with interest in applying sophisticated analytical methods using cutting edge software.
DATA courses are only offered in a 15-week online format.
Essentials of big data and data analytics are introduced and include descriptive, predictive and prescriptive statistics, regression analysis, optimization techniques and data visualization. The instructional approach in this course focuses on application-based reinforcement of concepts to include the use of simulations. A key component of instruction is an emphasis on analytical report writing and other ways to effectively present data analytic results. Techniques examined emphasize applicability in multiple organizational sectors to include business, finance, human resources, healthcare, manufacturing, sport management, social services, education, non-profit, and government entities. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees.
The benefits of using data to optimize the decision-making process, including understanding the differences between various types of data, data formats, data warehouses and data marts. Students will develop usable extraction, transformation and loading (ETL) techniques associated with data analysis and be introduced to data modeling and data mash-up techniques. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees.
Data visualization and communication skills are taught using industry standard software. The instructional approach in this course focuses on application using hands-on projects to create reports and dashboards with high-impact visualizations of common data analyses to help in decision making. A key element of instruction is an emphasis on communicating the practical implications of data analytics results to a non-technical audience in a timely manner. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees.
The basics of R programming are introduced including software installation and configuration necessary for effective data analysis. Generic programming language concepts are introduced and covered within the context of how they are implemented in practice when conducting high-level statistical analysis. The instructional approach in this course focuses on application-based introduction of programming concepts such as reading data into R, accessing analysis tool boxes in R, writing R functions, debugging, and organizing and commenting in R code. Data mining and analysis projects will be used to provide working examples. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees.