11 ways novices can start the process of learning AI programming

Artificial intelligence systems represent a pretty exciting area of study: There is a good-sized call for people with the skills needed, and the technology is still developing and growing. However, it can be difficult to figure out how best to get involved with the tech, especially if you’re wanting to learn on your own.

Fortunately, there are plenty of resources available for beginners to build up their knowledge and skills—or even figure out whether this path is for them. To find out more, we asked a panel of Young Entrepreneur Council the following:

What is the most important thing novices or programmers should know if they’re interested in learning more about AI development?

Here’s what they said:

1. Understand The Math Behind Machine Learning

AI development professionals must grasp probabilities, which serve as the foundation for machine learning. Traditional software developers often use functions from online libraries which relieves them from having to actually do the math themselves. AI developers need to be able to write and understand complex algorithms so that they can move on to finding insights and patterns inside data. – Blair Thomas, eMerchantBroker

2. Build a Strong Foundation, First

Before starting with AI, a strong foundation needs to be laid down for it. Get down with mastering the basics of programming (Python is one of the best programming languages for machine learning) and mathematics (linear algebra, statistics and calculus). Hone your abstract thinking. You don’t need a professional degree to master AI and ML, but you do need boundless passion. – Rahul Varshneya, ResumeSeed

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3. Brush Up On Python

AI is developing at a rapid pace and those that can work with AI will find themselves ahead of the competition. Python is the programming language of choice as it is easy to understand and write, has many libraries and has a significant user community. Python supports advanced machine learning and deep learning implementations of popular frameworks like TensorFlow, PyTorch and Keras. – Susan Rebner, Cyleron, Inc.

4. Search The Internet For Free Resources And Online Courses

If you are interested in learning more about AI development, start very simple: Google. There are tons of free resources, articles and online courses one can find to introduce themselves to the quickly growing world of AI development. Free resources offer a new programmer an easy, low-risk way of getting involved in AI to see if it is something you would like to explore. – David Chen, Sharebert

5. Get Comfortable With Abstract Thinking

Abstract thinking or deep reasoning is when machines are capable of understanding implicit relationships between things. This goes is more “fuzzy” than just learning logic, statistics or mathematical equations. If you understand relational reasoning, in addition to more explicit and direct rules, you’ll better understand the nuances and complexities of AI development. – Shu Saito, Godai

6. Start Building Simple Things With AI Algorithms

One of the key success factors of learning AI is to build a strong intuition for how AI systems work. One way to develop such intuition is to simply build things. For example, take on a project that interests you and requires a simple AI algorithm, and build that algorithm from scratch. There might be a learning curve, but you will learn a lot along the way and the long-term benefit is significant. – Sean Hinton, SkyHive

7. Learn How Human Insight And Computer Programming Intersect

In order to be a strong AI developer, you must have a solid foundation in statistics and data science. In order to program languages that are effective within AI, you must know more than basic math and be able to interpret the data at hand. You must be able to combine computer programming with human insight in order to be successful with AI development. – Jared Weitz, United Capital Source Inc.

8. Learn How To Gather The Right Data

AI is excellent at processing large amounts of data at once. When you’re thinking about creating AI software, think about tasks that require data points like customer service and marketing, and create a software that makes data-heavy tasks fast and easy. – Syed Balkhi, WPBeginner

9. Join Online Communities

Kaggle is an online community for data scientists and machine learners. The platform allows users to find and publish data sets, build models in a web-based data-science environment, communicate with other machine learning engineers and more. It’s a great way to learn from others in the field and you can even compete in competitions to boost your skills. – Stephanie Wells, Formidable Forms

10. Familiarize Yourself With Different Types Of AI

Artificial intelligence has so many different sectors you can study that it’s better to pick and choose which ones to start out with before diving in and feeling overwhelmed. Do your research on the different types so you can learn one step at a time and avoid experiencing burnout, since there’s a lot to learn. – Chris Christoff, MonsterInsights

11. Have Reasonable Expectations

There’s a lot of hype surrounding AI development nowadays that’s causing people to exaggerate its current potential. Although it is a very exciting frontier for software development and business, anyone looking to learn more about this technology will quickly discover its limitations. It’s important to approach this topic with reasonable expectations if you don’t want to lose interest. – Bryce Welker, The Big 4 Accounting Firms