IT SPECIALIST: ARTIFICIAL INTELLIGENCE

This practical program helps professionals, managers, and technical teams understand how to adopt AI responsibly and effectively. It focuses on real-world business use cases, governance, and workforce upskilling. Designed for professionals and managers and focused on practical business applications. The training aligns with industry-recognized AI competency frameworks.

Fort Lewis College has partnered with Certiport, the market leader in preparing learners with demonstrable, in-demand skills. In corrdination with the GMetrix skills management system, Certiport provides high-quality learning and practice materials along with industry-recognized certification exams. System requirements for the online learning program can be found here. Please ensure you have access to an IT system that meets these requirements before registering. 

This training is online and asynchronous, allowing you to learn at your own pace. After completing your coursework, you’ll be prepared to take an in-person, proctored certification exam at Fort Lewis College. 

This program entails the following phases and topics:

Phase 1: Business Readiness & AI Strategy: Learn how to identify business challenges suited for AI, define success metrics, and assess organizational readiness. 

• Know when AI adds value 
• Define clear AI-driven objectives
• Understand risk, compliance, and ethics

 Phase 2: Data Strategy & Preparation: Build a strong data foundation for AI initiatives.

• Improve data decision-making and governance
• Assess data readiness
• Reduce risk from poor data quality or bias

Phase 3: Model Development & Business Insight: Explore AI model options and interpret performance metrics without coding.

• Participate in model selection
• Evaluate performance and explain results
• Communicate AI-driven insights confidently

Phase 4: Deployment & Operational Integration: Prepare for real-world AI adoption and workflow integration.

• Integrate AI into existing operations
• Enhance collaboration between technical and business teams
• Minimize deployment risks

Phase 5: Monitoring, Impact & Continuous Improvement: Learn to monitor AI systems, measure impact, and manage lifecycle changes.

• Track performance and value
• Manage AI responsibly over time
• Make strategic decisions for long-term AI investments