Welcome to part four in our multi-part series of DAU LOG Blog posts highlighting a range of resources, references and related learning opportunities covering a range of critically important interdisciplinary topics of interest to the defense acquisition workforce. So far, we have examined:

• Supply Chain Resiliency & Supply Chain Risk Management (SCRM)
• Additive Manufacturing/3D Printing
• Digital Engineering, Digital Acquisition and Digital Product Support:

Today, we will be taking a looking at Data Analytics, Artificial Intelligence (AI) & Machine Learning (ML)

Definition

• Artificial Intelligence (AI) & Machine Learning (ML) - The ability of machines to perform tasks that normally require human intelligence.” (Source: JAIC)

Training

• CENG 002 - Data Analytics for DoD Acquisition Managers Credential
• CENG 003 - Artificial Intelligence Foundations in the DoD Credential (in development) leveraging combination of DAU & DAU Coursera Partnership courses
  • AI for Everyone
  • Ethics in the Age of AI - AI Algorithms and Limitations
  • Ethics in the Age of AI - AI Data Fairness and Bias
  • Ethics in the Age of AI - AI Privacy and Convenience
  • Ethics in the Age of AI - AI Ethics in Action
  • DAU SWE 1210 – Artificial Intelligence (AI) in the DoD
  • DAU SWE 1220 - Orchestrating Artificial Intelligence (AI) Acquisition
• UNI 4010V Data Science
• UNI 4030V Machine Learning & Visualization
• UNI 4040V Applied Decision Analysis
• UNI 4060V Lean Supply Chain Processes
• LOG 0600 Data Analytics Fundamentals for Product Support (in development)
• Hosted NAVWAR Data Analytics Training Videos
  • NAVWAR Foundations of Data Analytics Lesson 2.1: DoD AI Initiatives
  • NAVWAR Foundations of Data Analytics Lesson 2.2: Navy AI Initiatives
  • NAVWAR Foundations of Data Analytics Lesson 3.1: Data Science Demystified
  • NAVWAR Foundations of Data Analytics Lesson 3.2: Data Science vs. Artificial Intelligence
  • NAVWAR Foundations of Data Analytics Lesson 4.1: Limitations of Data Science
  • NAVWAR Foundations of Data Analytics Lesson 4.2: Augmented Intelligence
  • NAVWAR Foundations of Data Analytics Lesson 5.1: Data Discovery
  • NAVWAR Foundations of Data Analytics Lesson 5.2: Machine Learning Models
  • NAVWAR Foundations of Data Analytics Lesson 5.3: Natural Language Processing
  • NAVWAR Foundations of Data Analytics Lesson 6.1: F-18 Case Study
  • NAVWAR Foundations of Data Analytics Lesson 7.1: Review and Next Steps
• Hosted NAVWAR Data Visualization Training Videos
  • NAVWAR Data Visualization Course Lesson 1.1: Course Overview
  • NAVWAR Data Visualization Course Lesson 2.1: Visual Information and the Brain
  • NAVWAR Data Visualization Course Lesson 2.2: Pre-Attentive Attributes
  • NAVWAR Data Visualization Course Lesson 2.2: Pre-Attentive Attributes
  • NAVWAR Data Visualization Course Lesson 2.3: The Rules of Data Visualization
  • NAVWAR Data Visualization Course Lesson 3.1: Data Exploration and Discovery
  • NAVWAR Data Visualization Course Lesson 3.2: Data Storytelling
  • NAVWAR Data Visualization Course Lesson 3.4: Dashboard Evaluation Solution
  • NAVWAR Data Visualization Course Lesson 4.1: Review and Next Steps
• Other Training Courses through the DAU Coursera Partnership including: Data Science Methodology (IBM), Machine Learning (Stanford University), Applied Data Science with Python (University of Michigan), Executive Data Science (Johns Hopkins University), and AI for Everyone (DeepLearning.AI), among others

Additional Resources

• Joint Artificial Intelligence Center (JAIC)
• Understanding AI Technology
• “Assessing the Use of Data Analytics in Department of Defense Acquisition” RAND Report (Note: For those who may not be familiar with the issuers of this report, the RAND Corporation is a nonprofit institution that helps improve policy and decision making through research and analysis. Inclusion of a link to this report here is for defense acquisition workforce informational and professional development purposes, and does not imply DAU or DoD endorsement of any particular organization, document, findings or recommendations.)