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.  

Applied AI, Agents & Automation 

Course 3 of 3

Engineer intelligent systems—not just models. This advanced course pushes you into the world of production‑grade AI engineering. You’ll build autonomous agents, orchestrate workflows with both code and low‑code tools, fine‑tune open‑source LLMs, and implement Retrieval‑Augmented Generation (RAG) for long‑term memory. Finally, you’ll containerize a multi‑service AI system and deploy it on a GPU‑accelerated Kubernetes cluster. This is where developers become AI engineers. Ideal for: Software developers who want to specialize in Artificial Intelligence and Large Language Model (LLM) integration. Data scientists looking to operationalize their models and move them from notebooks to production web services. DevOps engineers who need to understand the specific infrastructure requirements of AI workloads, including GPU orchestration. Graduates of Course 2  ready to apply their full-stack and DevOps skills to the cutting edge of AI technology. 

Prerequisite Skills  

This is an advanced course that combines software engineering with data science. To ensure success, students should have: 

Full-Stack Development Experience: Strong proficiency in Python, web frameworks (Flask/FastAPI), and API design, as covered in Course 2: Cloud-Native App Deployment. 

Containerization & DevOps Skills: A solid understanding of Docker, GitLab CI/CD pipelines, and basic Kubernetes concepts. 

Database Knowledge: Comfort with SQL and interacting with databases programmatically. 

Understanding of Machine Learning Basics: While we teach advanced techniques, a conceptual understanding of what a model is (from Course 1: Python AI Fundamentals or equivalent experience) is helpful. 

Additional Courses in AI Development Track:

1: Python AI Fundamentals: 9/7/26 – 11/29/26

2: Cloud Native App Deployment  10/5/26 - 12/27/26 or 2/22/27 - 5/23/27

This course is designed to provide the basic skills in AC / DC motors and motor control and provides an understanding of the operation of AC and DC motors and motor control circuits. Course topics include AC / DC motor operations, control circuit components, motor control wiring, connections, ladder diagrams, and interpretation of electronic motor control schematics. The course also introduces the student to variable frequency drives (VFDs) and provides practical skills in programming one of the more commonly used drives. Students should have prerequisite knowledge and experience in electrical fundamentals. 

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.

Strong teams don't happen by chance—they are built through effective leadership. This interactive workshop equips supervisors with practical strategies to build trust, strengthen collaboration, foster accountability, and address conflict before it affects team performance. Participants will learn how to create a positive team culture, set clear expectations, improve communication, and lead teams that are engaged, productive, and focused on shared goals.

The interactive course is for helping professionals and direct service workers in healthcare, behavioral health, education or other people centered professsions who want practical skills for building trust, even in tense or resistant client interactions.  

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: 9/7/26 – 11/29/26

3: Applied AI, Agents & Automation  10/19/26 - 1/17/27 or 2/22/27 - 5/23/27

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: 9/7/26 – 11/29/26

3: AI Infrastructure & Security 10/19/26 - 1/17/27 or 2/22/27 - 5/23/27

Students will have the opportunity to learn the theory and hands-on skills to gain the foundational knowledge of Hydronic and Forced Air Heating systems. The successful completion of the 75-hour HVAC module I course will allow and prepare students to take the more advanced 75-hour HVAC module II course.

Topics include the following:

• Safety
• HVAC Tools
• Mathematics for HVAC
• Theory of Electricity - I
• Blueprints and wiring diagrams
• Soldering, Braizing and Welding
• Piping Materials and Fittings
• HVAC Career Opportunities
• Introduction to HVAC Equipment - Boilers, Furnaces & AC
• Fundamentals of HVAC Equipment- Boilers, Furnaces, Valves and Meters
• Radiant Heat Systems
• Troubleshooting HVAC Equipment
• Customer Service
• Soft Skills
• Work Ethic