Training & workshops
Nineteen courses built from real market and hiring data, mapped to high impact workflows, emerging systems engineering regulations, and strict security compliance requirements. Be ready for what's next.
Request training infoOur mission
We bridge the gap between academic theory and practical, workflow-integrated execution. Every module is world class and standard aligned, built for immediate impact across private enterprise, defense systems, and public sector technology. Every course runs as a two day weekend intensive or a four day distributed format, four hours a day, so your team can apply what they learn immediately without stepping away from the job for a full week.
Enterprise AI productivity and workflow automation
Practical, workflow-first courses that put AI to work in the tools your team already uses.
Building AI fluency: foundations, boundaries, and effective prompting
Move beyond treating AI as a black box and build a real technical understanding of modern AI, including machine learning, deep learning, and generative systems. Participants learn context engineering: structuring clear, context hygienic prompts using the TRACI framework to reduce hallucinations, manage automation bias, and get more out of everyday AI use.
The A.S.K. Framework™: mapping workflows and pinpointing automation value
Learn to systematically evaluate daily processes for AI driven efficiency gains. Using task analysis and workflow mapping, participants apply UnDesto AI’s proprietary A.S.K. Framework™, Automate, Share, Keep Human, to audit their own roles, identify high value automation opportunities, and move them into secure, AI augmented workflows.
Workflow automation with Copilot and Power Platform
Bridge the gap between AI theory and day to day execution. This hands on course walks participants through building automations for low complexity, high volume tasks, using Microsoft Power Automate, Power Apps, and Copilot to manage data extraction, document synchronization, and multi system notifications.
AI-augmented operations: maximizing business unit ROI
Built for operational leadership, this course shows how to restructure department workflows to capture real time savings. Participants study real world upskilling benchmarks, learn to delegate tasks to AI responsibly, and implement human in the loop validation that scales departmental output without creating new bottlenecks.
Mastering agentic AI: prompting, orchestration, and workflow integration
Bridge the gap between simple prompting and enterprise grade orchestration. Participants build the skills to design autonomous multi-agent systems, set clear boundaries for LLM APIs, and configure automated output evaluation, then integrate agents directly and safely into existing enterprise software.
AI security, red teaming, and model defense
Practitioner level training for the people who have to defend AI systems, not just build them.
AI red teaming and model defense
Traditional network perimeters cannot secure modern machine learning models. This course introduces the standardized threat taxonomies of the MITRE ATLAS framework and the OWASP LLM Top 10. Participants run security validation audits, model hardening routines, and defensive filtering to protect deployed pipelines from adversarial inputs, prompt jailbreaks, and data poisoning.
AI hardening and threat modeling: defending against injection and model exploits
A deep focus on software security engineering for deployed machine learning applications. Participants master threat modeling across the AI software supply chain, identifying where training data, model weights, and inference are vulnerable, then build active sanitization layers, monitor model API endpoints in real time, and implement cryptographically secure model pipelines.
Mission assurance: aerospace and satellite cyber security
Protect mission critical space infrastructure and satellite payloads from active cyber adversaries. This course addresses the full space system attack surface, covering vulnerabilities across the space link, ground segments, and user terminals. Participants learn to implement RF security, execute space to ground key management, and deploy edge based AI anomaly detection.
Systems engineering and advanced standards
For engineers building the models, safety cases, and physical systems underneath the AI.
Model-based blueprints: SysML and MBSE mastery
Stop relying on static, disconnected documents to manage complex systems. This course teaches modern Model-Based Systems Engineering (MBSE) discipline. Participants build live, executable system architectures using SysML and UML to define precise requirements, structural blocks, behavioral state machines, and parametric constraints.
Lifecycle security: unifying ISO 15288, safety, and cyber
Break down the silos between product safety and cybersecurity across the engineering lifecycle. Using ISO/IEC/IEEE 15288 as a structural baseline, participants learn to integrate functional safety standards (ISO 26262, IEC 61508) and cybersecurity frameworks (ISO/SAE 21434, DO-326A), and run joint Hazard Analysis and Threat Analysis (HARA and TARA) to balance design trade-offs.
Generative systems design and AI simulation
Use predictive artificial intelligence and generative modeling to optimize physical design performance. This course covers the core disciplines of AI driven digital engineering, showing how to integrate machine learning simulation loops, stress testing algorithms, and automated design adjustments directly into CAD, CAE, and digital twin environments.
Lean AI: streamlining operations and shop floor flow
Unite lean manufacturing discipline with predictive artificial intelligence to eliminate industrial waste. Participants learn to design, train, and deploy predictive maintenance systems, vision based defect detection, and adaptive production scheduling, and to manage sensor drift while building reliable edge pipelines.
AI governance, compliance, and trust
Policy, risk, and compliance training for the people accountable for how AI gets used.
Strategic AI integration: maximizing enterprise ROI and vendor evaluation
Equip executives with a framework for guiding corporate AI strategy safely. Participants learn to run quantitative business feasibility audits, analyze total cost of ownership, and evaluate vendor solutions, then apply that work to build procurement criteria that protect intellectual property and data ownership.
Establishing trustworthy AI: governance, ISO/IEC 42001, and regulatory compliance
Build the organizational policy needed to deploy AI safely, ethically, and responsibly. Grounded in the NIST AI Risk Management Framework, participants learn to build governance structures, conduct AI impact assessments, align with the EU AI Act, and secure institutional data.
Bias auditing and trustworthy AI validation
Give your data teams the methods to verify, audit, and explain machine learning outcomes. Participants learn to evaluate models for demographic bias, ensure statistical group fairness, and implement explainable AI frameworks (SHAP, LIME) to defend model outcomes to regulators.
ISO/IEC 42001: operationalizing AI governance (AIMS)
Build a globally recognized AI management environment. This compliance focused course teaches risk leads to design, audit, and continually improve an ISO/IEC 42001:2023 compliant AI Management System (AIMS), including formal Clause 8 impact assessments and mapping required controls.
Architecting AI risk guardrails: NIST RMF and policy
Operationalize the NIST AI Risk Management Framework, AI RMF 1.0, inside federal, state, and corporate organizations. Participants get a practical blueprint for mapping, measuring, managing, and governing AI related risk, preparing teams to meet modern policy requirements.
GovTech compliance: in-house deployment under federal mandates
Address the security, ethical, and regulatory requirements of AI use in state, local, and federal agencies. Aligned with federal guidance and the NASCIO State AI Blueprint, participants learn to build secure, isolated model sandboxes, vendor verification frameworks, and regulatory impact statements.
Public sector data stewardship: foundations of AI readiness
Address the real barrier to public sector AI: fundamental data literacy and governance. Participants learn to manage structured databases, curate reliable schemas, enforce clear data lineage, and configure automated PII redaction so services can be delivered safely.
Let's build this.
Every course is scoped to your team before it is delivered. Tell us where you are starting from, and we will help you find the right fit from the catalog above.