How to Get Started in AI and Machine Learning

Once upon a time, artificial intelligence jobs were a pipedream. Today, AI and machine learning jobs are among the most coveted roles in the world.

AI and machine learning aren’t just passing trends in an ever-evolving digital landscape – they are critical aspects of the future of our planet.

Rapid development in AI has already transformed many industries, and it will continue to do so, with Forbes projecting that AI will create 58 million jobs by 2022.

This technology is here now, and a lot of people want to get involved.

What may surprise you is that it’s possible to get a job in AI or machine learning without a specialized degree. Some of the biggest companies in the world, including Google, Apple, and IBM are hiring people without a college background.

In this article, we’ll show you how to get an introduction to machine learning, and give you the actionable tips you need to start your AI career.

5 Core Skills for Getting a Job in AI and Machine Learning

The idea of an AI career may sound uber-cool in a slick, futuristic kind of way, but behind the scenes, AI and machine learning jobs entail tasks and abilities that may not have everyone leaping out of bed on a Monday morning.

To truly succeed in an AI career, you must have some core skills. Moreover, you should have a genuine passion for the work that is involved.

Consider the following:

1. Probability and Statistics

To say you should have a head for numbers is an understatement. Ideally, you should be excited to read about statistical theories and get giddy on probability problems.

2. Applied Math

We’d love to tell you that machine learning is a bit like creating your own levels on an Xbox game. However, it’s mostly about high-level mathematics. When you’re learning about complex things like algorithms and gradient descent, you should only yawn because it’s too easy.

3. Programming Proficiency

Python is the best language to learn when you want to start a career in machine learning or AI. Down the line, you should build your skills in common programming languages such as C++ and Java.

4. Distributed Computing

The real gold behind AI and machine learning is data. Unfortunately, data is only as useful as humans can make it. So, the world needs smart programmers who can handle massive data sets that are spread over several computers. If you can sharpen your distributed computing skills, you’ll have a much better chance of getting an AI career.

5. Unix

The vast majority of AI processing is done on Linux machines. If you’re an Apple Mac baby who has never toyed around with Unix systems, the road ahead will be a tough one. Get acquainted with Unix functions and tools in your spare time before going any further.

What to do Before You Apply for an AI Job

As mentioned, a degree is not essential for an AI career. Of course, it would certainly boost your chances, especially as competition for artificial intelligence jobs increases in the years ahead.

However, if you don’t have the resources for a full-time degree, you can still make it into the AI and machine learning industry.

It won’t be easy – but then nothing worth having ever is, right?

1. Online Study

If you’re truly motivated to get an AI career, you can undertake self-directed study. There is a plethora of fantastic options online now. Here are a few gems:

• Learn with Google AI – Get a great introduction to machine learning and find out what AI is all about. This is tailor-made for beginners, and will give you a feel for things without breaking the bank – because it’s completely free!
• Machine Learning by Stanford University – Coursera is shaking up higher education, allowing people to get top-level college degrees online. This in-depth course is from Andrew Ng, the founder of Google Brain.
• Fundamentals of Deep Learning for Computer Vision by Nvidia – This discipline teaches you how to create computers that are capable of analyzing visual information in the same way as the human brain. Sounds awesome, right?

2. Personal Projects

It is possible to get an AI job without a degree, but it’s not likely to happen without experience. But how can you get experience in machine learning or AI without a job?

Say hello to GitHub – the world’s leading software development platform.

Employers will care more about your work on here than they will about any CV or certificates.

The idea of starting your own AI project may seem impossible at first. However, as you study machine learning and develop your abilities in programming, statistics, and software design, the best way to grow is to actually practice.

Here are some pointers for your next GitHub project:

• Pick a project that is relevant to your current skills, so it will help you learn in the process.
• It should not take any longer than one month to complete.
• The code must be clean, commented, and modular.
• Create a ‘Read Me’ doc, and detail the dependencies, referenced tutorials, and technology you used.

Simple projects will give you goals to work towards, and through your mistakes and the community feedback, you will progress much faster. Once you have solidified your knowledge and learning with some projects, you’ll stand a much better chance of finding an AI job.

How to Find a Job in AI or Machine Learning

A great way to crack any industry is through an internship. This is no different in the tech space, and AI and machine learning internships are aplenty. 

You get the chance to work alongside experienced engineers, data scientists, and programmers, gaining valuable experience on smaller projects before securing a long-term role.

Here’s how to find an internship or entry-level job in AI or machine learning:

1. Build Your Network

You don’t need to be told how to do Google searches for jobs. But many people tend to overlook their own professional network. Think about these avenues:

• LinkedIn – A strong network in your field holds great potential. Seek to build yours on a consistent basis by adding people on similar career paths. From fellow students and tutors to industry influencers and market leaders. Soon enough, opportunities will arise.
• Join AI communities – Kaggle and GitHub are great for practicing your skills, but also to develop connections. Jobs are advertised on these sites too, and you can get referrals and news from other people in these communities.
• Attend events – Keep an eye out for meetups that involve AI professionals and students, especially in major cities. These may happen at universities or at dedicated tech conferences.

2. Create a Shortlist

In addition to simple Google searches, you will discover companies that are looking for AI and machine learning professionals as you build your network through communities, events, and social media groups.

For each company, do research around their website and social media channels to discover more about their products, services, and the brand itself.

You must determine if it is a company you want to work for. If it is, add it to your shortlist. Rinse and repeat until you have at least 20-25 companies on the list.

3. Judge Yourself

Next, explore the companies in more detail to discover what they need. Take the following steps:

• Look at the descriptions for artificial intelligence jobs and machine learning internships, and consider the required skills and experience.
• Take note of terms, qualifications, skills, and experience points that are present in several different roles from several companies.
• Ask yourself how your experience and knowledge compares.

Ultimately, if you are to succeed in getting an AI job, you must be able to show that you can add value to an existing company. If you don’t already tick the boxes to apply for the jobs you want, then you must continue working on your skill-set.

4. Continued AI Career Development

Here are a few ways to get to the level you need to be at to secure an internship or entry-level job:

• Portfolio – Create a personal website that showcases your projects and skills. This will act as a live platform to present yourself to prospective employers.
• Blog – You can have this on your portfolio website. It will allow you to discuss aspects of AI and machine learning in your own style and offers people more insight into your technical know-how and passion for the industry.
• Freelance Work –  Freelance platforms such as Upwork have thousands of paid projects, which can help people gain experience in the industry. Over time, a strong freelance profile bolstered by good reviews often leads to bigger opportunities.

The World Needs People to Start AI and Machine Learning Careers

It’s not easy to get a job in AI or machine learning. Even if you have a degree or relevant qualifications, you must work hard to build a very specialized, high-level skill-set. Then, you must develop a strong portfolio of personal projects that demonstrate you have what it takes.

It’s hardly surprising that the bar is so high when you think about what AI and machine learning is capable of. It’s already tackling major global issues like climate change and cancer.

But here is the good news:

There is an AI skills shortage. As mentioned earlier, there are millions of artificial intelligence jobs to be filled in the years ahead, but at present, we don’t have the people.

So, if you have the motivation to work hard, and study harder, then you may well make it. With generous compensation waiting for you, it’s certainly worth the effort.

Plus, you may even change the world.

So, are you ready for an AI career?

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