homepage | Dr. Alex Francisco Leads Introduction to Data Analytics
February 2, 2022
February 2, 2022
Introduction to Data Analytics unites real-world experience with practical knowledge. Dr. Alex Francisco (PhD, University of Missouri Kansas City), senior population health scientist and statistician at the Kansas City Health Department, leads the non-degree course.
The workshop will be held online in two parts on March 23 and March 26.
Dr. Francisco is the director of the Office of Population Health Science and Statistics. Data plays a central and critical role in assessing public health matters and decision-making. He uses data analytics to research, understand, and improve the health of populations within Kansas City. His current efforts utilize computational modeling to best aid the City of Kansas City’s COVID-19 response.
For example, Dr. Francisco was featured in a December news report on KSHB. He discussed how data is used in the Health Department’s mapping tool. The data-driven tool helps to visualize how the virus has moved through different age groups in Kansas City since the pandemic started.
That level of expertise and real-world experience bolsters the data analytics knowledge presented to students in Introduction to Data Analytics. Extending beyond theory, the course is a non-technical introduction to data analytics. Students learn how data science is a process that can be leveraged for strategic decision making in daily operations.
Companies such as Spotify, Netflix, and Starbucks rely on data analytics for a range of reasons. Insights gleaned from data analysis supports making better decisions faster. Data analysis can also help to reduce costs, gauge customer needs and satisfaction, and lead to development of new and improved products and services. From health care to banking to retail giants like Amazon, data analysts are needed to improve processes and performance.
The introductory course is a smart way to begin learning about the high-demand field of data analysis. In Dr. Francisco’s course, participants learn the terminology of data science. More importantly, students consider big questions that they should be asking in an organization.
Other course topics include an introduction to the data analytics industry, comprehensive overview of the data analysis process, common analytics strategies, and basic manipulation and analysis of data in Excel.
Introduction to Data Analytics is one of seven courses in the UMKC Data Analytics Workshop Series. The Series consists of seven instructor-led interactive courses. Begin with one course or attend a series of three workshops to earn a non-degree certificate from UMKC TalentLink.
Learn more about Introduction to Data Analytics.
March 29 and April 2 – Python Boot Camp
Understanding Python is a highly sought-after data science job skill. The course is a non-technical introduction to Python applications for data cleaning, merging, visualizing, and analyzing data.
April 5 and 9 – Introduction to SQL
SQL is a bedrock database management tool for modern data science. Students are introduced to the SQL environment, principles of database management, and basic tools for working with databases.
April 12 and 14 – R for Data Analytics
R is an open-source programming language for data analytics. This workshop introduces students to R through a process of guided examples, ensuring a broad understanding of how it can easily address your analytical needs.
April 19 and 23 – Data Dashboards with Tableau
This course leverages Tableau to help attendees create functional, attractive, and relevant dashboards as tools to communicate important data to internal and external stakeholders.
April 26 and 28 – Spatial Data Analysis with ArcGIS
Where we are matters. Learn basic techniques for understanding the impact of geography in relation to an organization. Participants will use both ArcGIS Online and ESRI Business Analysts to address real world problems.
May 3 and 7 – Data Visualization with R
This workshop leverages R as a tool for creating visually appealing and persuasive data stories.
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