Modular Courses: Build Targeted Skills

Learning Objectives

• Set up and navigate a coding environment
  Gain an understanding of the tools, terminals, and editors essential for working with any technical system. This allows participants to operate independently in engineering workflows.
• Master programming fundamentals
  Variables, data types, loops, functions, and control flows are the universal building blocks of all software. Those who understand them can reason about programs, debug issues, and create useful scripts.
• Process files and work with structured data
  Missions rely on logs, telemetry, reports, CSVs, and text data. The ability to read, parse, and transform files enables the automation of manual tasks and analysis at scale.

Resulting Capability

Participants complete the course with the ability to write simple, effective Python scripts to clean data, parse files, and automate repetitive tasks, skills that are immediately useful for analysts, operators, and technologists across the USSF.

Learning Objectives

• Build reliability into Python code via testing
  Testing ensures programs behave as expected, which is critical for mission environments where code accuracy cannot be left to chance.
• Write programs that connect to public APIs
  Many modern systems expose data through APIs. Learn to pull, send, and integrate live data to automate workflows and build powerful data-driven tools.
• Understand and work with larger programs using modules and packages
  Real-world software isn’t a single file. Learn to contribute to multi-file codebases, understand architecture, and collaborate with engineering teams.
  
• Model real-world problems with advanced data structures
  Learn how to map real mission scenarios to code, unlocking the ability to prototype solutions for scheduling, resource allocation, data pipeline steps, and more.
  

Resulting Capability

Participants  complete the course ready to build small applications, automate multi-step processes, integrate external data sources, and work within a larger software ecosystem. These are foundations for future work in analytics, automation, and software roles.

Learning Objectives

• Set up and understand a TypeScript development environment
  Gain fluency with the tools used by production engineering teams, including terminal commands, editors, bundlers, and TypeScript compilers.
  
• Learn core programming fundamentals
  Learn core programming fundamentals – types, functions, control flow, objects, and arrays – to reinforce correctness and build skills applicable to enterprise software workflows.
• Understand basic web concepts (HTML/CSS/DOM)
  Learn how the browser works in order to build interactive, dynamic webpages, and understand how front-end applications actually function.

Resulting Capability

Participants complete the course with the ability to build simple interactive web pages, understand strongly typed code, and reason about how modern front-end systems operate. This is ideal groundwork for future front-end or application development roles.

Learning Objectives

• Frame analytical problems and prepare reliable data
  Develop an analytics mindset by asking the right questions before using tools. Ingest, clean, and structure real-world datasets, including CSVs, APIs, and tabular data, to ensure accuracy and reliability before analysis begins.
• Analyze data using industry-standard tools
  Use Python, pandas, and NumPy to filter, group, aggregate, and explore structured data, uncovering meaningful patterns and trends.
  
• Communicate insights through visualization and narrative
  Create clear, effective visualizations via Matplotlib and Seaborn, and translate findings into concise, decision-ready narratives that support operational and strategic decisions.

Resulting Capability

Participants complete the course  with the ability to clean and structure datasets, perform exploratory analysis, create meaningful visualizations, and communicate insights that support operational decision-making across intelligence, cyber, operations, acquisition, and program management roles.

Learning Objectives

• Adopt the product manager mindset and define customer problems
  Understand the role of a product manager, collaborate across functions, and translate research into validated problem statements grounded in user and business needs.
• Build strategy and execute with structured methods
  Define product vision, success metrics, and priorities, applying Agile practices to manage backlogs, write clear requirements, and guide iterative delivery.
  
• Design, validate, and deliver solutions with business alignment
  Prototype and test ideas, collaborate with technical teams, assess risk and ROI, and develop business cases that align stakeholders around a shared roadmap.
  
• Communicate and present product recommendations effectively
  Develop executive-ready narratives, apply structured storytelling, and present data-informed proposals with clarity and confidence.

Resulting Capability

Participants complete the course with the ability to identify validated customer problems, define product strategy, prioritize effectively, collaborate with engineering teams, and communicate structured, data-informed product recommendations that support mission-aligned innovation.

Learning Objectives

• Understand AI capabilities, limitations, and risk
  Gain a practical understanding of generative AI systems, including bias, hallucinations, privacy, and governance. Learn how to use AI safely and responsibly in enterprise environments.
  
• Prepare data and knowledge systems for AI use
  Recognize how structured information, documentation quality, and data hygiene impact AI performance and reliability.
  
• Design repeatable AI workflows for knowledge work
  Move beyond one-off prompting to structured, reusable workflows that improve consistency, quality, and productivity while maintaining human oversight.
  
• Evaluate and prioritize AI opportunities
  Measure AI value through ROI, quality, and risk, and identify where AI can meaningfully enhance existing processes.

Resulting Capability

Participants complete the course with the ability to evaluate AI tools realistically, design structured AI-assisted workflows, apply governance and security best practices, and prioritize AI adoption to improve productivity while managing risk. These skills are essential for knowledge managers, program leads, operations staff, and functional leaders.

Learning Objectives

• Understand model behavior, limitations, and responsible deployment
  Examine AI model capabilities, failure modes, bias risks, and security considerations to ensure safe and reliable implementation in technical environments.
  
• Design AI-enabled workflows and integrations
  Build structured prompt patterns, manage context effectively, and design human-in-the-loop and systems-integrated workflows using APIs and tool orchestration.
  
• Apply AI in development and product delivery
  Leverage AI-assisted coding, testing, documentation, and experimentation to accelerate technical workflows while maintaining quality.
  
• Evaluate performance, value, and architectural tradeoffs
  Assess reliability, cost, scalability, and risk when integrating AI into products or enterprise systems.

Resulting Capability

Participants complete the course with the ability to integrate AI into development workflows, design structured prompt and context systems, evaluate model performance and risk, and contribute to technically sound, responsibly deployed AI-enabled applications. These are skills relevant to developers, product managers, analysts, and technical program leads.

Active duty service members, government civilians, reservists and national guard service members can apply to take modular courses.

Government contractors and civilians are not permitted.

Each course lasts 2 weeks, M-F from 0900 – 1700 CST.

100% attendance for the duration of the two weeks is required for successful completion of any modular course. No absences will be permitted. Should there be an emergency situation, the Galvanize team will make a case by case decision. 

Attendance means: 

• Present during all class hours (0900 – 1700 CST) with the consistent use of a webcam
• Completion of 100% of required learning and assignments
• Active engagement with instructors and peers 
• Completion of all required feedback processes

You will need to utilize a personal computer that meets these minimum specifications:

• Reasonably new, within the last 4-5 years
• 16 GB RAM (8 GB acceptable, but not recommended)
• Mac or Windows OS
• Video/Audio Capable Webcam (can be a separate webcam device)

Additionally, you will need a reliable, strong internet connection.

You must work with your direct leadership, as they retain administrative control during the program, to determine an appropriate location for you to complete the course. We highly encourage a workspace with minimal distractions. 

Personal leave is not allowed during the modular courses, due to their length. Full-time attendance is required for successful completion of the course.