How to Learn AI on Your Own (a self-study guide) - Towards Data Science

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Thu VuTowards Data Science

If your hands touch a keyboard for work, Artificial Intelligence is going to change your job in the next few years.

In this blog post, I’ll be sharing with you a roadmap for expanding your AI skillset, together with the learning resources.

This roadmap goes down to the basics, so even if you don’t have any background in machine learning, mathematics or programming, I hope you’ll walk away with some useful ideas of where to start.

👉 Note: You can also watch the video version of this blog post and download the full Roadmap PDF on my Youtube channel:

Now, let’s get started! 💪

Why Should You Learn AI?

Artificial Intelligence, Machine Learning and Deep Learning have been around since 1950s. This area has taken off in the last decade (and much in the recent years) due to advancements in algorithms, computing power and especially, the abundance of data.

The AI we often talk about today is Generative AI, which is a subset of Machine Learning and Deep Learning.

Relationship between Generative AI, Deep Learning, Machine Learning, and AI. Image by author.

Generative AI can now write code, generate stunning images, writing music, diagnosing rare conditions, creating outline for presentation, reading images and much much more.

Companies around the world are racing to capture value from generative AI, trying to use it to create better services and products, improving processes and automating time-consuming tasks.

Large enterprises are rushing to implement AI solutions to solve their specific problems. This is a gold mine because everything is still very new. If you have the knowledge and know how to build things with AI, you can create huge impact.

As with anything in its early days, AI models still have many issues that need to be solved. They are not yet reliable or stable, they potentially possess biases among other things. That is why we need more people who have in-depth understanding and can get to the bottom…

Summary
The article discusses the impact of Artificial Intelligence (AI) on various professions and provides a roadmap for individuals to expand their AI skillset. It emphasizes the increasing importance of AI due to advancements in algorithms, computing power, and data availability. The article highlights Generative AI as a subset of Machine Learning and Deep Learning, capable of tasks such as writing code, generating images and music, diagnosing conditions, and automating tasks. It also mentions the rush of companies to implement AI solutions and the potential for individuals with AI knowledge to create significant impact. However, it acknowledges that AI models still have issues such as reliability, stability, and biases, emphasizing the need for more people with in-depth understanding of AI to address these challenges.