Artificial Intelligence (AI) – What Is It & How Do I Learn it?

There’s no doubt that artificial intelligence – or AI as it is usually referred to – is one of the buzziest terms in tech. these days. But what is AI exactly? And more importantly, how can you learn about it and use AI skills in your own work? In this post, we’ll give you a heads up on the key things you need to know about AI and who knows – it might spark some ideas for you in terms of potential applications in your own industry. Here’s the whistle-stop-tour!


What is Artificial Intelligence and What does it do?

Artificial Intelligence (AI) has been at the forefront of computer science research for over 50 years. In recent years, a confluence of breakthroughs in hardware capability and algorithm design have made the early promise of intelligent machines a reality. AI is one of the fastest growing areas in ICT and it has the potential to positively transform every aspect of our lives – from smart cities and autonomous vehicles, through to improved healthcare services and low-carbon economies.

Artificial Intelligence (AI) is already at the heart of many transformational business and technical applications, typically employing a combination of data analytics and machine learning.  At the same time design and development activity for AI systems is growing exponentially, constrained mainly by the limited availability of skilled professionals – now there’s a thought!


Types of Artificial Intelligence

AI is an umbrella term for the study of artificial intelligence. It summarises how computers can think and make decisions like humans, leading them to have human-like actions as well being able to potentially solve problems much faster than we could with the limits of human intelligence.

Artificial intelligence is generally broken into two categories, narrow or weak form and general automated knowledge processing also known as general-purpose intelligent systems (AGI). More recently there’s been a third type introduced known as conscious AI. Let’s look at each of these branches of AI and consider what’s involved.


Narrow AI

Narrow AI, also known as weak artificial intelligence (AI), it is the application of technologies to enable a high functioning system which has been designed with the ability to imitate and replicate human Intelligence for one specific purpose. As they have been designed for the purpose of performing one specific thing, with the help of machine learning principles, over time they become extremely efficient and “intelligent” in terms of doing that task. However, they are unable to perform other functions, and this is why they are often referred to as weak artificial intelligence.


Examples of Narrow AI include;

  • Google search
  • Personal Assistant Tools like Siri and Alexa
  • Image recognition software.


Artificial General Intelligence

The concept of AGI is very different to narrow AI in that the AGI is an intelligent form of learning that can be applied to many tasks. The machine is capable of reasoning about different topics based on its accumulated experience, which could mean anything from cleaning your home to building Excel spreadsheets!

The quest to create an artificial intelligence with human-level thinking capabilities is ongoing. But many researchers in this field believe that it will be possible soon enough, and some say they’re close! It’s exciting for those who want a glimpse at what the future may hold – especially if you work as part of a company seeking out new ways to improve business operations. But for all of us, it’s fascinating to have our curiosity piqued by the developments in this field.


Conscious AI

This is the pursuit of building robots which some people believe will eventually become more humanlike in their actions than other iterations – because they’re not solely based on data analysis but instead use intuitive judgement like we do with our own thoughts!

Conscious AI is an elusive concept that researchers are only beginning to explore. It refers not just to self-awareness, but to conscious awareness – or the ability for a machine to have a unique mindset and therefore thoughts and feelings about itself as well its surroundings. This is still to be realised but it is considered to be the holy grail for many AI experts and maybe someday one of you out there will be the one to crack this code!


How to Learn Artificial Intelligence?

If you want to further your career in this field, there are a number of technical skills that you will need to master first. As this is a complex area, you’ll probably have a steep learning curve – depending on where you are starting from. But if you’re hungry for knowledge, have an aptitude for this kind of work and are ambitious to succeed – AI is an area that is both intrinsically rewarding and commercially lucrative. So, let’s take a brief look at the topics you’ll need to study on your journey to successful career in AI.


The Fundamentals:

Before jumping into the deep-end, it’s important to brush up on the basics when it comes to maths and coding, for example:

  • Algebra fundamentals
  • Calculus
  • Graph Theory
  • Vectors
  • Statistics & Probability
  • Python
  • Pandas/NumPy/matplotlib
  • Virtual Environments


Once you are comfortable with the fundamentals, you can begin to familiarise yourself with the various techniques that can be used to convert raw data into structured data. This is an important step as once you know how to create structured data you can apply machine learning to gain insights. These techniques include:

  • Principal Component Analysis
  • Dimensionality Reduction
  • Normalisation
  • Data Scrubbing/handling missing values
  • Unbiased estimators
  • Features Extraction
  • Denoising & Sampling


Now it’s time to decide which direction you want to take within the field of AI. Typically, there are 3 subfields to choose from for your area of specialisation – Machine Learning Engineer, Data Scientist and Data Engineer.

While there are those who have successfully managed to teach themselves AI, as you can see it is a vast and complex area of study. Therefore, enrolling in a recognised AI course or degree can help you to master these skills with the latest knowledge base and streamline your learning trajectory. A proven, practical course will save you time and money and short-circuit the many winding routes that people often go down trying to establish a career in AI.