Early bird pricing - save $200

New Supervisor Training focuses on the skills needed by emerging, new, or recently appointed team leaders or first line supervisors. The program is ideal for employees who are new to planning, coordinating, and directing the work of others. This comprehensive 4-day program is a combination of lecture, hands-on exercises, group exercises, and tools for future success. Participants will have a pre-class assignment before each session and will receive a one hour 1-on-1 coaching session with the instructor after completing the program.  

Register by May 19,2026 for Early Bird Pricing

Basic Lab course covers a review of basic chemistry principles on pH, alkalinity, chlorine residuals, treatment and water quality regulations. Workshop covers water quality topics on disinfection and public notification. Water Treatment Operators Grade IA / IIA are required to complete a 0.5 CEU Basic Lab course every 3 years.

This session will review calculating rate of filtration and backwashing. It includes the examination of filter media efficiency to meet the filter turbidity rule and cleaning filter media as well as selecting and applying chemicals.

This session will review treatment and distribution operations for flows, pressure, storage capacity, operations and maintaining drinking water quality.

This course is designed for operators of distribution systems serving greater than 1,000 people. Topics include pressure zones, booster stations, storage tanks, fire protection and disinfection.

AI Infrastructure Track  

The AI Infrastructure Track prepares students to design, build, and manage the modern systems behind AI deployment. Across three hands-on courses, students progress from foundational networking to full cloud ‑native‑ orchestration, gaining the practical skills needed to support real-world AI workloads.  

AI Networking Fundamentals 

Course 1 of 3 

Build the backbone of tomorrow’s AI. This 10-week, hands-on course builds the essential networking foundation required for modern AI systems. Students being directly in ‑their own virtual network environment, learning core concepts like IP addressing, routing, DNS, DHCP, and using firewalls for security. Develop troubleshooting and management skills using professional tools. The course ends with students beginning their journey to designing an AI network architecture by deploying a full monitoring stack that will be used in their “AI Incubator” environment. 

Ideal for: Junior System Administrators and IT Technicians wanting to deepen their networking knowledge.· Help Desk professionals aiming to move into Network Operations or DevOps. Linux enthusiasts who want to understand how to connect and secure Linux systems. 

Prerequisite Skills 

This course is fast-paced and hands-on. To ensure success, students should have: 

Basic Computer Literacy: Comfortable working with operating systems (like Xubuntu) and navigating a desktop interface. 

Fundamental Networking Awareness: A conceptual understanding of what an IP address is, what a router does, and the difference between the Internet and a Local Area Network (LAN). 

Introductory Command Line Experience: Familiarity with opening a terminal and running basic commands (like ls, cd, or mkdir). You do not need to be a Linux expert, but you should not be afraid of the command line. 

Logical & Mathematical Aptitude: Ability to perform basic binary math calculations (essential for understanding subnetting). 

Troubleshooting Mindset: The patience and curiosity to investigate why something isn't working and the persistence to try different solutions. 

Additional Courses in AI Infrastructure Track:

2: Linux & Cloud Foundations 7/13/26 - 10/4/26 or 8/31/26 - 11/22/26

3: AI Infrastructure & Security 7/27/26 - 10/25/26 or 11/23/26 - 2/21/27

AI Development Track   

The AI Development Track is a hands-on journey that takes students from Python fundamentals all the way to becoming a professional AI Engineer. Over three intensive courses, you'll master the complete AI development lifecycle and have a portfolio of production-ready applications. This program is designed for those ready to move beyond using AI to building the intelligent applications of tomorrow.  

Course 1: Python AI Fundamentals 

Course 1 of 3. Recommended first course.

Build your future in AI—starting with code. This hands-on course takes you from basic programming knowledge to writing real, production ready Python applications. You’ll master professional tools like Git and VS Code, build your first commandline AI app, and complete a full machine learning project using industry standard libraries like Pandas, Scikitlearn, and PyTorch. The perfect launchpad for anyone entering AI development, data science, or automation.  

Ideal for: IT and Network professionals looking to transition into a data-focused or AI development role. Analysts and researchers who want to move from analyzing data in spreadsheets to building predictive models. Developers from other domains who want to add machine learning and data science skills to their toolkit. Ambitious tech enthusiasts who want a comprehensive, project-based introduction to modern AI development. 

Prerequisite Skills 

This course is comprehensive and fast-paced, designed to take you from programming fundamentals to AI fundamentals in 10 weeks. To ensure success, students should have: 

Basic Programming Literacy: You understand the core concepts of programming in any language (e.g., variables, loops, if/else statements). Experience with Excel formulas, VBA, JavaScript, or any scripting language is ideal. 

Logical Reasoning Skills: The ability to think through a step-by-step process to solve a problem. The course begins by teaching you how to formalize this with pseudocode. 

Comfort with Installing Software: You can download and install applications like Python and a code editor (like VS Code) on your own computer and are not intimidated by configuration files. 

Basic File Management: You are comfortable creating, finding, and moving files and folders on your operating system (Windows, macOS, or Linux). 

A "Can-Do" Mindset: This is a challenging but rewarding course. A willingness to engage with complex topics, troubleshoot errors, and persist through challenges is essential for success. 

Additional Courses in AI Development Track:

2: Cloud Native App Deployment  7/13/26 - 10/4/26 or 8/31/26 - 11/22/26

3: Applied AI, Agents & Automation  7/27/26 - 10/25/26 or 11/23/26 - 2/21/27

Students will program basic machine movements and create programs using common canned cycles using G&M Code programming. Students will also learn to write programs for the lathe that include macros, sub programs, live tooling cycles, and calls for automation 

No class 7/6 - 7/10.