Artificial intelligence is becoming crucial for businesses that want to compete and survive. In fact, if you’re not using AI in 2021, there’s a good chance you lose out to your competitors.
Of course, that makes AI development a highly sought after career, as more companies need to hire skilled developers to help them incorporate AI in their company, products, and services.
So how do you get started in AI development, and what skills do you need?
A mathematics background is crucial
When you look at AI and machine learning, it’s clear that you will need a solid background in mathematics. In particular, a clear understanding of linear algebra and calculus is a must. Besides, probability, statistics, and algorithms will all come into play.
There are many courses available on sites like the edX platform and Coursera. In particular, these resources will help you to learn the fundamentals in preparation for AI development:
- MIT’s Calculus courses, starting with differentiation
- Probability and statistics, such as MIT’s Probability—The Science of Uncertainty and Data
- Linear Algebra (University of Texas)
In addition to these, resources such as MIT OpenCourseWare provide the syllabus and supporting materials for a wide range of mathematics and computer science courses.
Once you’ve covered mathematics foundations, it’s time to start diving into AI specifics. Andrew Ng created a series of courses that are worthy of your attention. His Neural Networks and Deep Learning is part of the Deep Learning specialization at Coursera. Columbia offers an Artificial Intelligence MicroMasters course that is also considered a must.
In addition to courses, a variety of textbooks and other learning materials are also available, including:
Python and more
Once you have a solid understanding of mathematics, it’s time to learn a programming language so you can start creating your solutions.
While different programming languages are available, many libraries and toolsets – such as PyTorch – rely on Python, so that’s a good place to start.
MIT’s Introduction to Computer Science and Programming Using Python is a good place to begin especially if you have some programming background. If you’re completely new to it, Programming for Everybody (Getting Started with Python) will give you a much gentler entry to Python.
The R programming language is also useful. R is commonly used for a variety of data science tasks. For instance, many tasks associated with organizing and cleaning data use R. Harvard’s Data Science certificate provides a useful framework to follow.
As you begin to work with AI, you’ll no doubt come across TensorFlow. Originating from the Google Brain team within Google’s AI organization, Google offers various tutorials to get started with TensorFlow using the high-level Keras API. You can run TensorFlow locally or on Google Cloud.
Finally, Kaggle is a popular learning resource, and completing Kaggle challenges is a great way to understand how to develop, test, and measure your AI developments.
This is not an exhaustive list by any means. Still, a solid background in mathematics, understanding how to program in languages such as Python, and taking part in challenges to hone your skills are all great ways to get started.
