This course provides Airmen with an introduction to data analytic terms and concepts. Students are shown how to acquire data, conduct basic analysis, and leverage data to better inform data-driven decision making. Although this course is designed as a stand- alone course, it will also serve as a springboard to more advanced courses on data management and data analysis.

The two-day instructor-led course, or the 4 days VIRR option, is designed for Air Force personnel as a foundational hands-on course. Students will apply Data Analytics techniques to solve case-based problems in a laboratory environment. Students will gain a basic understanding of conducting statistical analysis using Microsoft Excel® and several representative case studies/exercises on using data analytics to describe, diagnose, and predict various operations management challenges. Students will learn how to manipulate a large data set, including descriptive statistics, pivot tables, charting and visualization techniques, formulas, text manipulation, data tables, concatenation, and parsing. Graduates will obtain immediate tools they can use to increase their job performance and Data Analytics acumen.

This course provides Airmen an opportunity to explore fundamental data analysis to manipulate data using Microsoft® Excel as a foundational analysis tool. An Airman’s data analytics journey ultimately arrives at this crucial stage where the data in use will need proper formatting and reorganizing through a process known as data manipulation. Following this short course, students will be able to navigate through data contained in spreadsheets more efficiently and apply time-saving techniques to data sets through the use of several special built-in functions, user- created formulas and logical functions. Students will be able to immediately apply what they have learned within their organizations and be confident in taking the next steps in their data journey.

This course provides Airmen a deeper understanding of the importance and techniques of cleaning and validating raw datasets in preparation of extrapolating information from them. Airmen will follow a single data source through the cleansing process, with each module providing a specific error and solution, to gain understanding of the tools and techniques to clean data prior to analysis. The course culminates in a direct contrast of the analysis of a raw and cleaned dataset. Following this short course, students will be able to readily recognize errors and weak points in data entry and apply cleansing techniques to ensure accurate and precise analytical outcomes from more advanced data manipulation efforts.

Manipulating data for analysis can be extremely time consuming and rigorous. This course provides Airmen an opportunity to quickly and easily manipulate data using Microsoft Excel as a foundational analysis tool. An Airmens data analytics journey ultimately arrives at this crucial stage where the data in use will need proper formatting and reorganizing through a process known as data manipulation. Following this short course, students will be able to quickly summarize data sets through the use of pivot tables modified by slicers, filters, and dynamic formatting. Students will be able to immediately apply what they have learned within their organizations and be confident in taking the next steps in their data journey.

One of the most challenging aspects of data analytics is communicating the results from hours of work to decision makers, shareholders or colleagues. This course provides Airmen an opportunity to effectively and efficiently communicate analysis results through charts using Microsoft Excel. Students will be introduced to basic human visual processing methodologies. By utilizing these visual processing methods, students are aided in the selection of chart type, use of color and formatting options to minimize audience effort in understanding data visualizations. Students will be able to immediately apply these visualization concepts in using data to tell a story to their intended audience. Students visual communication repertoire will be enhance, not only for data analysis.

This course builds on foundational Power BI knowledge, focusing on advanced data transformation, modeling, and visualization techniques within the Department of the Air Force environment. Participants will develop proficiency in Data Analysis Expressions (DAX), M Query, and Power BI’s data modeling tools to create more efficient, interactive, and insightful reports. Emphasizing hands-on application, this course teaches Airmen how to structure and refine datasets, optimize dashboards for mission-driven reporting, and streamline workflows for better data management.

Take the next step in your Data Analytics journey, applying the tools you mastered in Data Analytics Tools and Techniques. This workshop will build on what you have already learned to solve a real world problem you may be facing in your organization today. In an immersive five day workshop, or during 10 half-days (VIRR), you will work in dynamic teams using industry tools and statistical methods to uncover keen insights about an assigned case while further adding to your Data Analytics toolkit. You will learn how to diagnose a problem using data analytics while producing a solution, predicting the outcome and finally visually communicating your solution with confidence. Tools used in this workshop are: Microsoft Excel, Access, Structured Query Language SQL, Tableau, R and R-Studio. Graduates of this workshop will be prepared to lead data analytics projects within their organizations, helping foster a more data-driven culture.

This course is data literacy and artificial intelligence (AI) for senior leaders training (O-6, GS-15 and above). Focused within the DoD/DAF, and tailored to the senior leader perspective, expert coverage of fields and subfields of AI, ML, neural networks, and data literacy topics are presented, and backed by recent research. Leadership, legal/policy, ethics, safety, and other timely real- world and combat related topics are integrated with leadership lessons and how- to's for implementation of AI technology. Senior leaders will walk away from the course with a solid baseline of the emerging requirements and considerations of AI modernization for their own organization within the context of the larger US Presidential, DoD, USAF, and USSF strategic plans.

This course provides Airmen an opportunity to explore fundamental data analysis using R in the popular RStudio environment. Basic R language syntax and concepts are introduced and used to import data and compute descriptive statistics. Visualizing this data via common plot types will also be explored. Following this short course, students will be able to use R in RStudio to produce and replicate simple data analysis and plotting.

This course provides Airmen an opportunity to explore data analysis and visualization using the powerful R language in RStudio. The concept of packages is introduced, a feature that extends and compliments R's capabilities, and is used for advanced data manipulation and analysis. Additional new capabilities for creating complex visual charts and graphs are also explored. Following this course, students will be able to manipulate large datasets and utilize strong data visualization tools.

This course provides Airmen a look into the multi-disciplinary aspect of data research. Students will discuss how to apply various analytical tools and techniques to be more informed decision makes and to solve complex problems found in the exponentially expanding data collected by organizations today. Students will also go more in-depth in data exploration, data management, linear programming and optimization to build models within Excel to find or define the solution space. They will gain a basic understanding of the theoretical assumptions of these models and the abilities and limitations such models inherently provide. At the end of the course students will get an introduction to R-studio and programming in R. This is an intermediate course on data analysis tools and techniques for students familiar with Excel and limited understanding of object oriented programming.

This course provides Airmen an opportunity to explore foundational Python programming skills in Jupyter notebook. An Airmen’s data analytics journey ultimately arrives at this crucial stage where the data in use will need proper formatting and reorganizing through a process known as data manipulation. Following this short course, students will be able to import and export data in Jupyter notebook and access a variety of package tools to begin working with data. Additionally, students will be able to conduct basic calculations and manage data within arrays using the NumPy package tool.

This course provides Airmen an opportunity to explore Python data frame manipulation and visualization within Jupyter notebook. As feature exploration becomes important in analyzing data, a data frame helps in maintaining the structure of the data within a multidimensional setting. Following this short course, students will be able to create and manipulate data frames using the Pandas tool package. Additionally, students will be able to create basic visualizations to depict relationships and key features of datasets.

This course provides Airmen an opportunity to explore technical skills beyond basic analytic tools and gain a solid foundation in Python Programming. Python is a programming language used for automation, data analysis, and problem-solving. Through hands-on exercises, students will learn core programming concepts, data manipulation techniques, and visualization capabilities to automate tasks and solve real-world problems. Additionally, this course also introduces Generative AI as a tool to streamline code generation and increase productivity. By the end of this course, students will be ready to apply Python to operational challenges and experiment with AI-driven tools in their workflow.

Introduce students to the methods and techniques of data science using the Python programming language. This workshop will train students to interact with stakeholders and domain experts, formulate a data science task, organize and clean data, choose the appropriate data science tool based on the required task, and present findings to aid in decision-making.

Introduce students to various intermediate level concepts of data science with a focus on machine learning methods. This workshop will train students on a range of topics including dimensionality reduction and expansion, unsupervised learning, plotting decision spaces, and Neural Networks with Keras, including Convolutional Neural Networks and Recurrent Neural Networks.

Introduce students to various advanced level concepts of data science, especially in regard to application. This workshop will train students on a range of topics including Recommender Systems, Reinforcement Learning, Natural Language Processing, Transformers, Generative AI, and AI Bias and Ethics.