Can You Learn AI Without Coding?

AI is useful for an extensive range of business use cases, including gaining handy insights from otherwise useless data and using them to optimize operations and raise the bottom line. Even so, AI comes with substantial barriers to entry, not the least of which is the coding expertise needed to implement AI solutions. But as technology reaches new heights, many wonder: Can you learn AI without coding?

You can learn AI without coding. While coding is necessary to implement AI, you can understand how AI works without coding knowledge. Moreover, with the rise of no-code solutions, you can implement AI without writing any code.

This article will discuss the requirements for one to learn and use AI. I’ll also evaluate the utility of no-code solutions.

Why Coding Isn’t Necessary to Learn AI

Artificial intelligence (AI) aims to replicate and advance human intelligence. Since it began as a field of computer science, AI has been inextricably intertwined with coding. Code is the only way to tell a computer what to do, and since AI is implemented by computers, it requires coding.

However, at a high level, the principles of AI have nothing to do with coding. Think of AI as a field with separate theoretical and practical aspects. You can understand the theoretical part just fine without any coding knowledge.

Can You Implement AI Without Coding?

Can you learn AI without coding? Sometimes when people ask this question, they’re asking whether you can learn to use AI if you have no coding skills.

You don’t have to know code to understand the theoretical part, but you can’t practice AI without code.

A practical example is AI game design. AI designers with high-level AI knowledge solve gameplay problems in the design stage, but they need programmers to implement the solutions.

To a large extent, AI is about data. For AI models to learn, you have to feed them data, and you’ll need to use computer code to manipulate the data and make it suitable for use. Every stage of machine learning requires coding skills and theoretical AI knowledge.

Until recently, you couldn’t implement AI without coding knowledge. But thanks to the rise of no-code solutions, you can let AI do the coding for you, meaning you can implement AI without coding skills.

The Rationale for No-Code Solutions

The proliferation and commercialization of computers (including mobile devices) have resulted in a lot of abstraction.

For computers to be ubiquitous, they had to be easy to use. Microsoft, through its user-friendly Windows operating system, capitalized on this, making it one of the most profitable companies in the world.

Since the launch of Microsoft decades ago, user-friendliness and abstraction have been the norm. For technology to be fully commercialized and truly useful to society, it has to be made widely available.

The tech industry realized this and began democratizing AI by creating platforms that significantly reduced the workload of designing and building AI models. Google was a pioneer in this and created AutoML, an AI platform that builds machine-learning models on behalf of data scientists.

Here’s a YouTube video showing how Amazon SageMaker, a platform similar to Google’s AutoML, works:

AutoML and related technology have been incredibly useful as they slash the time and effort machine learning experts spend on repetitive and labor-intensive tasks, freeing them up to do more impactful work.

But we’ve made even more progress in the last few years. Instead of just easing the workload for AI experts, technology now empowers novices to leverage AI.

No-Code Solutions for AI Novices

Before the development of solutions like AutoML, highly qualified machine-learning experts would spend a lot of time doing repetitive, non-core tasks. According to some estimates, data scientists spend 80% of their time on data preparation tasks.

With AutoML, you’ll spend less time building your models, but you still need to have substantial machine learning knowledge to use the platform well.

No-code solutions like Obviously AI allow people without any knowledge of machine learning to implement AI.

Let’s go through one use case that Obviously.ai uses to market itself.

AI Novices Can Use Obviously.Ai to Predict the Customers Most Likely to Stop Using a Service

All you’d need is an Excel sheet with attributes like gender, type of contract, payment method, and so on — all the data you collect on your clients. You then follow this straightforward process:

Upload your data to Obviously.ai. You must ensure the file meets certain requirements. For example, it must be less than 25 MB. The data set should also have as few empty rows as possible.
Choose which type of model to build. You can build an AutoML or a Time series model. Your data set will be reviewed, and if it meets the required criteria, it will be approved for prediction.
Choose the column you want to be predicted. This will likely be the churn column. Obviously.ai will clean your data and build a custom model to make predictions within one minute.

After the process above, you’ll be able to tell:

The factors that have the highest impact on whether a customer stops using your product.
The accuracy of the prediction model.
The personas of the customer that’s most likely to stay with you and the one that’s most likely to leave.

You’ll also be able to launch the model. Once you do, you can key in the attributes of a customer, and the model will tell you how likely they are to leave. You can use such insights to increase customer retention, for example by offering incentives to those who are most likely to leave.

AI Novices Can Use Google’s Teachable Machine to Tell If Bananas Are Ripe Enough to Eat

Teachable Machine by Google is another no-code AI platform, and this one is entirely free. It allows users to train AI models on visual and audio content.

As a fun example, you can use Teachable Machine to tell if a banana is not ripe, ripe, or too ripe. Here’s an outline of the steps you’d need to follow:

Select the “Images” project type. You can train Teachable Machine to identify sounds, poses, and images.
Define the types of bananas you want Teachable Machine to identify. For example, you can use the following classes: unripe banana, ripe banana, too-ripe banana, and no banana.
Add images for each type of banana. These images are what the model will be trained on.
Train and test the model. It will use the uploaded images to determine common characteristics in all the classes you defined. If it doesn’t work the way you desire, you can tweak it by adding more training images or finding better images.

Once the model has started working, you can use it to determine the state of any banana!

No-Code AI Solutions Can Be Useful, But They Have Challenges

The biggest challenge with no-code solutions like Teachable Machine is that you can’t customize them. As a result, they may not be adequate for a use case with specific requirements.

While solutions like AutoML offer more control, there are still some things you can’t tweak. A machine learning expert with coding skills can create highly-customized models that are more effective for particular use cases.

Other challenges of no-code AI solutions include:

Limited scalability. If you need an AI solution at scale, you may need to build a customized one.
Limited integration. It may be challenging to integrate no-code solutions with your existing systems.

If you’re curious to know how programming languages such as JavaScript might be used to develop AI in real projects, it may be beneficial for you in implementing easy JavaScript code. As it is widely known for its flexibility in web development, JavaScript is a go to language for many developers.

If you want to learn more on the available frameworks in JavaScript for developing AI applications, read my article Can You Build AI With JavaScript?

Final Thoughts

You can learn AI without coding. While coding is necessary to implement AI, you can understand how AI works without coding knowledge. Thanks to no-code AI solutions, you can do a lot without coding skills. You don’t even have to know how AI works!.

While analyzing the challenges of learning AI, one would think: is AI hard to learn? Read our article ‘Is AI Hard To Learn?‘, where we have discussed the complexities associated with learning AI, providing valuable insights into this topic.

At the moment, what you can achieve without coding skills and AI theory is limited. However, as technology improves and as no-code AI continues to become mainstream, we’ll be able to use it to solve even major problems.