In a world where Artificial Intelligence (AI) is the star of the show, it’s natural to want to jump on the AI bandwagon. You’ve probably heard about AI changing industries, making incredible things possible, and shaping the future. But let’s be honest…when you think about starting your journey into AI, confusion may set in.
Well, don’t worry; you’re not alone! The AI path may appear complicated, especially if you don’t have a background in the tech industry. In this short guide, I will tell you how to step into the AI path with a pragmatic approach.
Learn about AI concepts
To get started, it’s critical to understand the philosophy behind AI. Where it came from, why it began, and where it’s going. This knowledge is like having a map to guide you as you move forward in this field. It helps you make smart choices and navigate the path more effectively, just like knowing the lay of the land helps a traveler find their way. “AI For Everyone” on Coursera is a great introductory course to answer those questions. The tutor, Andrew Ng, explains AI concepts in short videos with different interesting quizzes and exercises. I have taken various courses with Andrew Ng and learned a lot from him. He is very good at explaining complex concepts with simple words.
Price: Audit for FREE
Approx. 10 hours to complete
However, if you prefer to learn the basics by reading and doing practical exercises, I suggest “Elements of AI” by the University of Helsinki. I really liked their course’s minimal and interactive design, as well as the intuitive way they explained AI concepts using creative analogies.
Price: FREE
Approx. 4-8 hours to complete
Besides the mentioned introductory courses, If you are willing to pay some bucks, Brilliant is one of the most intuitive existing learning platforms for learning various machine learning and deep learning concepts. They have a variety of interactive courses that feel like you’re playing a game while learning! Some courses, like “Introduction to Neural Networks” or “Artificial Neural Networks” are a great complement to the other introductory courses I mentioned.
Price: 24.99$/m
Approx. 4 hours to complete
Learn some programming
In addition to understanding the philosophy and concepts behind Artificial Intelligence (AI), another valuable skill to add to your toolkit is programming. Python is the language of choice for many AI projects due to its simplicity and extensive libraries designed specifically for data analysis and manipulation. Learning Python can significantly enhance your journey into the world of AI. You can learn Python while you are learning the theoretical concepts. This makes the learning process more fun and exciting.
Since you want to learn Python for AI practices, instead of taking some fundamental courses that bombard you with a lot of concepts in programming that you might never use, I recommend you take “Python for Data Science, AI & Development” by IBM. This short course familiarizes you with most of the necessary concepts you need for AI programming.
Price: Audit for FREE
Approx. 23 hours to complete
Dive Deeper into AI: Deep learning
Once you have learned the main concepts of AI and some Python programming, you are ready to connect these two dots in Deep learning. It is a subfield of AI that focuses on neural networks, which are computational models inspired by the human brain’s structure and functioning. These networks are capable of learning patterns and representations from data, enabling them to perform tasks like image recognition, natural language processing, and much more.
Some people might recommend that you learn machine learning before deep learning. Although it can be beneficial since machine learning forms the foundation upon which deep learning is built, I do not think it is essential to learn it. Most of the new AI trends focus heavily on deep learning due to its remarkable capabilities for handling complex tasks. Therefore, diving directly into deep learning could also be a valid approach. You won’t miss much by skipping machine-learning techniques!
“Neural Networks and Deep Learning” by Andrew Ng, is an excellent resource to delve further into the world of deep learning. This course builds upon the foundational knowledge you gained in “AI For Everyone” by the same tutor and takes you on a deeper exploration of neural networks and their applications.
Price: Audit for FREE
Approx. 23 hours to complete
Put your knowledge into practice
I think at this point, you have equipped yourself with enough skills to start doing some practice projects. In order to really learn what you have learned in the courses you took, it is necessary to put your knowledge into practice and have your skin in the game!
You can start doing some projects in Kaggle in your field of interest. It is an excellent platform for hands-on AI projects. You can participate in various competitions or just try your hand at the datasets available. You’ll get feedback from the community, learn from projects shared by others, and improve your skills.
Price: FREE
This was a general roadmap for anyone with any background who wants to step into the world of AI. I aimed to make this guide concise and practical. I’m considering crafting more customized roadmaps to cater to specific needs of those interested in the AI domain. For instance, I could create a roadmap for no-code AI enthusiasts, one for product owners delving into AI, and more. Feel free to share your thoughts, and if you desire a tailored roadmap, don’t hesitate to request one in the comments!