AI Learning Roadmap

A structured curriculum from the dawn of ImageNet to the future of AGI.

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Module 01: History & Legacy

The ImageNet Revolution

Understand the historical context and the “Big Bang” of modern AI. Why did deep learning suddenly work in 2012?

01
The Evolution of ImageNet: How It Changed AI Forever The story of the dataset that started it all.
02
Key Milestones in Computer Vision History From early pixels to the Deep Learning explosion.
03
The Role of Large-Scale Datasets Why data quantity matters as much as algorithms.
04
How ILSVRC Revolutionized Global Research The competition that united the global scientific community.
05
Looking Back: The Visionaries Behind ImageNet Profiles of the pioneers who saw the future.

Module 02: Foundations

Master the core technologies. How do Convolutional Neural Networks (CNNs) actually see and process the world?

06
Deep Learning Architecture: CNNs and Beyond Deconstructing the neural networks that power vision.
07
Object Detection vs. Image Classification A comprehensive guide to the core tasks of vision AI.
08
How Machines “See”: Digital Image Processing The science of turning pixels into meaning.
09
Transfer Learning: Using Pre-trained Models How to teach old models new tricks efficiently.
10
The Importance of Data Annotation The unsung hero of accurate AI model training.

Module 03: The New Wave

Move from recognition to creation. Explore the cutting edge of Diffusion Models and Multimodal AI.

11
From Recognition to Creation: Generative AI The paradigm shift from analyzing data to creating it.
12
Computer Vision and LLMs Synergy When eyes meet language: The birth of visual understanding.
13
Diffusion Models Explained How noise becomes art: The tech behind Stable Diffusion.
14
Multimodal AI: Integrating Vision, Text, Audio Towards AGI: Systems that sense the world like humans.
15
The Future of Autonomous Systems Robotics and self-driving cars powered by Vision AI.

Module 04: Society & Ethics

Apply knowledge to the real world. Understanding responsibility, bias, and industrial transformation.

16
AI Ethics and Bias in Visual Datasets Navigating the challenges of fairness in machine learning.
17
Real-World Applications in Healthcare Saving lives with computer vision diagnostics.
18
AI Impact on Security & Face Recognition Balancing safety and privacy in the digital age.
19
Transforming Retail and E-commerce The revolution in shopping experiences powered by AI.
20
Sustainable AI: Reducing Environmental Impact Building a greener future for large-scale model training.

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