As a tech professional, you may be wondering where to start when it comes to artificial intelligence (AI). With so many open-source tools and models being created every day, and the impending launch of Microsoft Co-Pilot, which brings AI to all Microsoft Office applications, it's understandable to feel overwhelmed. However, if you want to stay ahead of the curve and be in a position to build things with AI rather than just consume it, there's no time like the present to start learning.
AI, or generative AI to be more specific, is a subset of machine learning and deep learning that has the ability to write code, generate stunning images, write music, diagnose rare conditions, create outlines for presentations, and much more. Companies are looking for AI solutions to solve specific problems, and there is a gold mine of opportunity for those who have the knowledge and know-how to build things with AI.
While there may not be a one-size-fits-all roadmap for learning AI, there are certain fundamental concepts that are essential for anyone looking to get started. First and foremost, learning the basics of programming with Python is crucial. Python is one of the most, if not the most, used programming languages for machine learning, deep learning, and AI. Having a solid understanding of Python will be essential for working with AI.
In addition to Python, learning about Git version control, using APIs, and having a high-level theoretical understanding of AI and its subfields such as machine learning, neuron networks, and deep learning is also important. Understanding the main concepts of neuron networks, such as forward propagation, back propagation, gradient descent algorithm, and how weights are updated in the network is also important.
As you learn these concepts, it's important to build relevant projects to get hands-on experience and challenge your understanding. Building a real-world application, such as a document retrieval app or a chatbot, is a great way to apply what you've learned and gain practical experience.
In addition to learning the technical skills, it's also important to develop mental models around AI and stay informed about important topics and developments in the field. Reading books, following newsletters, and watching videos are great ways to stay informed and gain a well-rounded background in AI.
The field of AI is constantly evolving and the only way to keep up is to continuously learn. By starting now and building a solid foundation in the fundamental concepts of AI, you'll be well on your way to being able to build things with AI and stay ahead of the curve in your field.