MIT Lincoln Laboratory The course begins with a brief history of Artificial Intelligence (AI), including a survey of representative AI success stories and covers topics such as AI data requirements and conditioning, a selection of AI techniques including supervised learning, unsupervised learning and reinforcement learning, applications including computer vision and natural language processing, and computing and hardware requirements to support AI and Big Data applications.
In addition, the course covers properties and techniques that lead to robust AI solutions and review effective human-machine teaming principles and requirements. Each of the AI system components is addressed at a level deep enough to provide a working knowledge of the key technical drivers. Through it all, the course emphasizes an AI system architecture approach applied to engineering prototypes. We highlight strengths and weaknesses of AI solutions and illustrate the role AI can play in augmenting human intelligence.
Enterprise-level digital transformation awareness videos that the Digital Campaign feels would benefit the workforce to view. This page contains videos related to Digital Transformation and Digital Material Management. For those looking for a video that would explain basic digital concepts look in the folder "Digital Awareness".
Discover how to begin responsibly leveraging generative AI. Learn how generative AI models are developed and how they will impact society moving forward. (license required)
This lesson covers some concerns and ethical considerations when working with Generative AI. (license required)
Welcome to “Introduction to Engineering Concepts," a lesson that will introduce you to several STEM fields and help you build core skills that are helpful across many engineering disciplines. We also explain the engineering/research development process. This lesson assumes little to no prior engineering experience but does provide suggestions to increase the difficulty of the experiments should you desire to do so. To accomplish these goals, we invited several subject matter experts from across MIT Lincoln Laboratory (LL) to discuss their involvement in interesting, topical projects.
This series of articles explores the foundational techniques that make generative AI so powerful and current obstacles and applications related to the technology. The series includes: How Generative AI Works; Limitations of Generative AI; Types of Generative AI Applications; Milestones in Generative AI; The Future of Generative AI.
This free, online, at-your-own pace course is designed to equip you with the skills to use Generative AI in your day-to-day work as a public professional. This course provides public sector professionals with a comprehensive understanding of Generative AI (GenAI) and its potential to revolutionize work in government. Through hands-on activities and best practices, participants learn to use GenAI as a powerful companion to assist in their daily tasks while maintaining public trust and safety. The course covers the fundamentals of GenAI, its practical applications, prompt engineering techniques, risk mitigation strategies, and broader societal challenges. By the end of the course, participants will be equipped to harness the power of GenAI responsibly and effectively in their public sector roles. Learn hands-on and receive a certificate upon completion!
The education aims to produce an applied mathematician or applied statistician with the ability to develop new theoretical results and apply them as the need arises. Central to this goal is the research part of the program. Both the ability to conduct the research successfully and to report it in a coherent and fully documented dissertation is essential to the program. The program is kept sufficiently flexible, however, to permit students to develop their own specific interests.
The Cyber-Physical Sensing Certificate Program; Artificial Intelligence (AI) is designed for students with an educational background in Computer Engineering, Electrical Engineering, or Computer Science. Graduates can conduct exploratory and advanced research to develop innovative solutions that help warfighters predict mission-level effects based on sensor performance across land, air, sea, space, and cyberspace. This program is targeted for military officers, mid-grade enlisted, or DoD civilians assigned to positions at the Air Force Research Laboratories, Air Force Institute of Technology (AFIT), and DoD conducting CPS research, development, design, and analysis.
The Certificate in Data Analytics is a multi-departmental distance-learning program consisting of five courses provided one per quarter that supports the Department of the Air Force. The certificate provides Airmen and Space Professionals with the knowledge and skills to put the Department of the Air Force on the path to becoming a more data-informed organization. Courses will cover an introduction to data analytics, data and databases, introduction to machine learning, statistics, and computer programming with python. Program courses will focus on the use and understanding of applications/tools, not mathematical theory and algorithm development. Distance learning is completed from your current location through internet access. Recorded lectures must be completed in the week delivered. For more information, email AFIT.EN.DataAnalytics@us.af.mil.
Data Science is a multi-disciplinary field that focuses on the application of data-driven techniques to improve processes and/or identify patterns and recommend solutions for defense challenges. The scope of data science is holistic; it leverages the expertise developed via theoretical and practical studies in other disciplines to derive practical techniques to design, access and manage data sets (e.g., information systems and databases); the efficiently manipulate data (e.g., computer science); examine patterns and relationships among data (e.g., operations research, computer science, statistics); develop descriptive, diagnostic, predictive, and predictive analytic models (e.g., operations research); develop and field applications to automate the use of data science techniques (e.g., computer science); and manage the deployment of such applications.
The Doctor of Philosophy (Ph.D.) degree in Data Science entails completion of rigorous coursework requirements that prepare the student for advanced research and analysis in the field. The doctoral degree is characterized as a research degree with substantial emphasis placed on the completion of the dissertation research. Close interaction between the student and his/her research advisory committee plays a pivotal role in the successful completion of the Ph.D. program. Equally important is the discipline and dedication of the student, as independent study is a critical element for timely completion of the program.
The purpose of the Modeling, Simulation, and Analysis Certificate Program is to enhance the MS&A capability of selected Air Force students (e.g., within AFRL, LCMC, or AFMC), whether it be uniformed officers (e.g., 62X career field) and civilian personnel (e.g., GS 0800 series of engineers). The applicants for this program are determined in coordination with the Strategic Development Planning & Experimentation (SDPE) Office, who both sponsors and organizationally benefits from this educational program. The curriculum consists of four graduate level courses for a total of 16 graduate credits. No additional electives or research hours are required for the certificate. Typically, students will take one course per quarter depending on which quarter the classes are offered. The courses will be offered in-residence and via distance learning.
The Doctor of Philosophy (Ph.D.) degree in Operations Research entails completion of rigorous coursework requirements that prepare the student for advanced research and analysis in the field. The doctoral degree is characterized as a research degree with substantial emphasis placed on the completion of the dissertation research. Close interaction between the student and his/her research advisory committee plays a pivotal role in the successful completion of the Ph.D. program. Equally important is the discipline and dedication of the student, as independent study is a critical element for timely completion of the program.
Systems Engineering (SE) is a transdisciplinary and integrative approach to enable the realization, use and retirement of successful engineered systems. SE principles and practices are essential for the development of large, complex, high-performing, sustainable and secure systems, whether they are products, services, or enterprises. Modern approaches make use of integrated digital system models to capture requirements, structure, behavior and parametrics. Model-based systems engineering (MBSE) using System Modeling Language (SysML) is state-of-the-practice in the field, with the future toward more open, integrated and interoperable analysis tools and scripting languages.
The Test and Evaluation Certificate Program (TECP) is a graduate level education program focused on the application of operational analysis techniques and methodology as applied to the Test and Evaluation (T & E) Community. The program provides an understanding of planning and analysis tools dedicated to supporting the evaluation of test data, test design, and results from test execution. Particular emphasis is given to incorporating past, present, and future DoD T & E examples from all aspects of test (developmental, operational, etc.) into the curriculum to tailor the applications of the methodology and approaches within each course. Current T & E focus in design of experiments (DOE) and reliability, maintainability, and availability (RM&A) analysis are addressed in required courses to complete the program.
Data literacy involves reading, working with, analyzing, and arguing with data. It includes the application of data concepts, the interpretation and analysis of data, and the use of data to drive informed decision-making.
The AF Digital Campaign Conducted Getting "Digital Smart" sessions where we invited Industry partners and government organizations to share topics such as their digital transformation journey, their successes, their challenges, and in some cases, the technical details of their software products. Most of these sessions are recorded and included below "Getting Digital Smart Sessions" folder. In addition, other digital engineering and digital transformation videos are included. We have turned on the "Likes" function for each of the videos and would appreciate that if you do like a particular video that you click the heart so that we can see the types of videos visitors to this site enjoyed the most.
DoD Cyber Workforce Framework (DCWF) Orientation is an eLearning course designed to familiarize learners with the fundamental principles of the DCWF. This course an introduction to the policies and key attributes of the DCWF, and it outlines why the DCWF is critical to organizing and consolidating different positions as Work Roles across the DoD.
InnovateUS provides no-cost at-your-own pace and live learning on data, digital, innovation, and AI skills for public service professionals like you. Governed by a coalition of public sector learning and innovation leaders in California, Colorado, Maine, New Jersey, and Pennsylvania, our curriculum gives you the skills to deliver more effective, equitable and engaged policies and services. InnovateUS is brought to you by a team at the Burnes Center for Social Change at Northeastern University. We maintain full and sole control over writing, editing, and creation of InnovateUS course and workshop content, without influence from our generous funders.
Learning Maps’ feature curated lists of training resources to help jumpstart learning in digital skill areas. These maps include a description of a targeted digital skill, anticipated learning outcomes, and recommended resources including videos, workshops, and e-learning courses from sources like AFIT, DAU, and Google Cloud Skills Boost. The Learning Maps are organized according to audience skill level: Awareness, Intermediate, Advanced. Learning Maps are available to individuals across directorates and of all levels of experience. Resources listed in the Learning Maps are non-exhaustive and continually updated to meet the changing needs of AFRL’s workforce. For a full list of training opportunities across digital skill areas, please consult the Digital Skills Training Catalog.
The following catalog provides information on digital skills training opportunities relevant to AFRL needs. These trainings come from DoD-specific organizations as well as public online universities. Some training opportunities may be more relevant for AFRL employees than others.
The appearance of hyperlinks does not constitute endorsement by the Department of the Air Force of non-U.S. Government sites or the information, products, or services contained therein. Although the Department of the Air Force may or may not use these sites as additional distribution channels for Department of Defense information, it does not exercise editorial control over all of the information that you may find at these locations. Such hyperlinks are provided consistent with the stated purpose of this website.