How to learn AI and get RICH in the AI revolution

Learning to use AI tools like ChatGPT can make you more productive at your job, while learning to build AI tools like ChatGPT ensures job security. Building AI tools would likely be one of the last jobs AI can replace, making it crucial for future-proofing. OpenAI, the company behind ChatGPT, pays AI engineers almost 1 million dollars, highlighting the potential in this field.

Human Intelligence and Artificial Intelligence both stem from interconnected nodes—Neurons and Neural Networks, respectively. To build AI tools like ChatGPT, understanding Neural Networks and Deep Learning is essential. Deep Learning involves training neural networks with data to make predictions, such as predicting the next word in a sentence.

Machine Learning is built on three pillars, with Mathematics being the first. Knowledge of Linear Algebra, Calculus, and Probability Theory is crucial for understanding Machine Learning algorithms. While these concepts may seem daunting, they are fundamental for implementing Machine Learning effectively.

Statistics plays a key role in Machine Learning, covering concepts like Probability Distributions, Central Limit Theorem, and Regression. A foundational understanding of Statistics is necessary to delve into Machine Learning effectively, and courses like Introduction to Statistics by Stanford University can provide the required knowledge.

Python is the preferred programming language for Machine Learning due to its versatility and popularity. Basic programming skills in Python, including understanding if statements, loops, functions, and classes, are sufficient to start learning Machine Learning. Platforms like learnpython.org offer hands-on exercises for mastering Python basics.

To dive into Machine Learning, Andrew Ng's Machine Learning Specialization on Coursera is highly recommended. This specialization covers supervised learning, unsupervised learning, and advanced algorithms like Neural Networks. Hands-on practice on platforms like Kaggle allows for project exploration and portfolio building, essential for showcasing skills in Data Science and Machine Learning.

To build AI tools like ChatGPT, expertise in Deep Learning is needed. Andrew Ng's Deep Learning Specialization delves into training Neural Networks, Convolutional Neural Networks for Computer Vision, and Transformer architecture for Natural Language Processing. By completing this specialization, one can acquire the skills required for a successful AI career.