Official Recap: Summer 2025

CV & NLP
A peak into the AI's Brain

An introduction to Artificial Intelligence through hands-on experience tinkering with the AI Brain. Focused on computer vision and Natural Language Processing for non-technical high school students.

View 2026 Programs

Primary Learning Goals

What our students mastered during the bootcamp.

AI Fundamentals

Distinguishing Narrow AI, AGI, and ASI, plus pattern-based ML logic.

Master the Pipeline

Internalizing Data Collection, Model Training, and Model Testing cycles.

CV & NLP Pillars

Gaining practical experience with Computer Vision and Language Processing.

Real-World Intuition

Using relatable analogies like "Dimmer Switches" and "Word Maps."

2025 Core Modules

The 10-session deep dive into applied intelligence.

01

Intro & Data Collection

Session 1

Concepts

  • • History of AI (1956 - Today)
  • • Narrow AI vs. AGI

Labs

  • • Rock Paper Scissors Classifier
  • • Facial Expression Detector
02

Applied Computer Vision

Sessions 2 & 4

Concepts

  • • How machines "see"
  • • Convolutional Neural Nets (CNNs)

Labs

  • • Cats & Dogs Binary Classification
  • • MNIST Digit Recognition
03

Inside the Black Box

Sessions 4 & 6

Concepts

  • • Neurons, Layers & Activation
  • • Supervised vs. Unsupervised

Labs

  • • The 'Dimmer Switch' Exercise
  • • Training a Neural Network
04

NLP & Embeddings

Sessions 7 & 8

Concepts

  • • Tokenization & Word Embeddings
  • • Transformer Architectures

Labs

  • • The Tokenizer Challenge
  • • The Word Map Adventure
05

Modern Ecosystems

Sessions 9, 10 +

Concepts

  • • Hugging Face & Open Source
  • • Gen parameters (Temperature)

Labs

  • • Running Gemma-2 in Python
  • • Secure API Management

Student Voices

First-hand experiences from our 2025 cohort.

"What stuck with me most was that AI consists of neurons inside a network... similar to the way the human brain works. A fascinating fact was learning that computers only understand numbers."

S.M.

Stylianos M.

GCSC Student

"We made our own AI model and trained it! I learned that the result is more effective if you have many samples and an 80/20 train/test split."

G.G.

Giorgos G.

GCSC Student

"The point of view of a computer and the manner in which it thinks were fascinating... learning how to use Gemini and Python to run AI models offline."

O.V.

Orestis V.

GCSC Student

"What I liked most was how AI models think with perceptrons... Understanding embedding spaces and how models look for similar words was great."

S.L.

Stefanos L.

GCSC Student

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