is not a futuristic robotics center — it is a structured computing environment designed to teach: 

• Programming for AI 

• Machine Learning fundamentals 

• Data handling 

• Model training & evaluation 

• Introductary AI deployment 

Key Characteristics: 

• 24 high-performance workstations (rows or U-shape) 

• Instructor station at front 

• Large display / projector 

• Dedicated server rack corner 

• Whiteboard for mathematical explanations 

• Strong cooling (AI workloads generate heat) 

Hardware Requirements (Fundamental Level) 

You do NOT need a supercomputer. 

Student Workstations (24 Units) 

Minimum: 

• CPU: i7 / Ryzen 7 

• RAM: 32GB (important for ML datasets) 

• Storage: 1TB SSD 

• GPU: NVIDIA RTX 3060 or similar (8–12GB VRAM) 

Why GPU? 
Machine learning frameworks like TensorFlow and PyTorch use CUDA acceleration. 

If budget is limited: 

• Start without GPUs 

• Use cloud-based AI training (AWS, Azure, Google Colab) 

AI Server (Optional but Recommended) 

Specification: 128GB RAM, Multiple GPUs (2–4 RTX or A-series), High-speed NVMe storage 

10Gb network (optional) 

Purpose: Shared model training, Capstone projects, Research simulations,  

• For a vocational school, one strong GPU server is enough. 

Software Stack (Core) 

Programming & Frameworks 

• Python (primary language) 

+ Jupyter Notebook, Anacond, TensorFlow, PyTorch, Scikit-learn, Pandas,   NumPy and Matplotlib 

Development Tools : VS Code, Git, Docker (for model deployment basics) 

Operating Systems : Ubuntu Linux (preferred for AI), Windows (optional dual boot) 

Curriculum Structure for a Fundamental AI Lab (Focus: Hands-on labs > theory). 

Level 1: Foundations 

• Python programming 

• Linear algebra basics 

• Statistics for AI 

• Data cleaning 

• Visualization 

Level 2: Core Machine Learning 

• Supervised learning 

• Regression 

• Classification 

• Model evaluation 

• Overfitting & bias 

Level 3: Intro to Deep Learning 

• Neural networks 

• Image recognition 

• Basic NLP 

• Simple AI deployment 

What Makes It “Fundamental” ?

A fundamental AI lab is: 

• Educational, not research-grade 

• Focused on applied ML 

• Designed for skill development 

• Built around Python ecosystem 

• Integrated with industry certification paths 

It is not: A robotics lab, a humanoid lab, a robotics factory or a data center ! 

Contact us for a detailled quotation if you want to upgrade or convert your Computer / IT Department with an AI Fundamental option. 

Your DMH-Team !