Artificial Intelligence (AI) is one of the most powerful technologies of our time. In this third lecture of the free AI course, we dive deep into how AI actually works—how it learns from data, makes decisions, and improves over time.
AI systems are built on algorithms that process large amounts of data. They identify patterns and use those patterns to make predictions or take actions. For example, an AI trained on thousands of cat photos can learn to recognize a cat in a new picture.
The key steps in how AI works are:
- Data Collection: AI needs data to learn. This could be text, images, numbers, or any other information.
- Training: The AI model is fed the data and adjusts its internal parameters to reduce errors.
- Inference: Once trained, the AI can make predictions or decisions on new, unseen data.
- Feedback Loop: Many AI systems continue to learn from new data and user feedback, improving over time.
In this lecture, we explain these concepts in simple Hindi, making it easy for beginners to understand the magic behind AI. Whether you're a student, a professional, or just curious, this course will give you a solid foundation.
"AI is not magic—it's math and data. And once you understand the basics, you can build your own AI tools."
The course continues with Lecture 4 on Large Language Models (LLMs). Stay tuned!