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.

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.

Use G&M Code to program CNC mill machine movements and create programs. Students will also learn to set up tooling and offsets using work probes and indicators 

No class 7/6 - 7/10.

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.  

Cloud‑Native Application Deployment 

Course 2 of 3. 

Turn your AI ideas into real, cloud‑powered applications. Learn how modern AI-backed web apps are built and shipped. You’ll transform a Python script into a full-stack web application with Flask, SQLAlchemy, and a hand‑coded front end—and then take it all the way to the cloud. Containerize with Docker, automate with GitLab CI/CD, and deploy to Kubernetes. By the end, your work isn’t just running locally… it’s live. Ideal for Python developers looking to transition into web development or backend engineering. IT professionals who want to modernize their skillset with containerization and orchestration technologies like Docker and Kubernetes. Graduates of Course 1 who want to see their code come to life as a live, interactive web application. Aspiring DevOps engineers seeking a practical, project-based introduction to CI/CD pipelines. 

Prerequisite Skills  

This course focuses on web technologies and cloud infrastructure. To ensure success, students should have: 

Python Proficiency: A solid understanding of Python syntax, functions, and Object-Oriented Programming (OOP), as covered in Course 1: Python AI Fundamentals

Command-Line Literacy: Comfort with navigating the file system, running scripts, and managing files via a terminal. 

Git Fundamentals: Understanding of basic version control concepts like cloning, committing, and pushing code. 

Logical Thinking: The ability to understand how data flows between a client (browser), a server (API), and a database. 

Additional Courses in AI Development Track:

1: Python AI Fundamentals: 6/8/26 – 8/30/26

3: Applied AI, Agents & Automation  7/20/26 - 10/18/26 or 11/23/26 - 2/21/21

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.  

Linux & Cloud Foundations 

Course 2 of 3 

Turn your network into a living, breathing infrastructure. Learn the Linux, virtualization, and automation skills powering modern cloud environments. From user management and shell scripting to provisioning cloud-style virtual machines, you'll build and secure real services—including identity management, databases, and web apps. The ideal jump from networking into full system administration.  

Ideal for: Network technicians who want to expand their skill set into system administration.· IT professionals seeking to formalize their Linux knowledge for cloud and DevOps roles.· Students who have completed Course 1 and are ready to build the services that run on the network. 

Prerequisite Skills:  

This course builds directly upon the networking foundation. To ensure success, students should have: 

Completion of Course 1 (AI Networking Fundamentals) or equivalent networking knowledge: 

• Understanding of IP addressing, subnetting, and CIDR notation 
• Familiarity with core network services (DNS, DHCP) 
• Knowledge of routing concepts and static routes 
• Experience configuring firewalls and understanding basic security principles 

Basic Command-Line Literacy: 

• Comfort opening a terminal and navigating directories (cd, ls, mkdir) 
• Ability to view files (cat, less) and edit simple text files 

Understanding of Virtualization Concepts: 

• Conceptual knowledge of what a Virtual Machine (VM) is and how it differs from physical hardware 
• Basic understanding of hypervisors (like Proxmox, VMware, or VirtualBox) 

General Computer Literacy: 

• Comfort installing operating systems (Xubuntu) and software 
• Ability to troubleshoot basic technical issues independently 

Additional Courses in AI Infrastructure Track:

1: AI Networking Fundamentals: 6/8/26 – 8/30/26

3: AI Infrastructure & Security 7/20/26 - 10/18/26 or 11/23/26 - 2/21/21

This session covers selecting coagulate chemicals, coagulant aids, turbidity and solids residuals.