Study artificial intelligence or data science to prepare for the future.

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As artificial intelligence and data science continue to become more prevalent

in society, many people are asking the question of whether or not they should

study AI or data science to prepare themselves for the future job market. If you

are one of these people, you’ll want to consider the pros and cons of both fields

before making your decision. With that in mind, here’s a guide to help

you choose between studying artificial intelligence or data science if you’re trying

to get ahead in the workforce.

Why learn either AI or data science?


AI and data science are two of today’s most popular—and important—fields.

Data scientists use AI in their work, and vice versa. So why would you want

to become an expert in one over another? You might be considering a career that

falls under one of these umbrella titles (or maybe both) but isn’t sure which is

right for you. In some cases, those differences will be small enough that it won’t

make much difference in terms of job duties or salary; other times, they can mean

very different jobs with very different salaries and skill sets. Here are five key

considerations

Why not both?


It’s possible that many positions will be replaced by machines in due time,

but it will also result in more jobs being created. In order to stay relevant

and employable, employees should focus on becoming adaptable and learning

new skills as they emerge. Because of how rapidly industries are changing, it’s

a good idea to study both artificial intelligence and data science. Both fields

use coding languages such as Python and R programming and give people a

solid foundation from which they can build their technical knowledge on top of.

It’s worth noting that those who learn more than one skill have an easier time

finding jobs within STEM fields, according to Forrester Research—even if they

don’t work directly with technology!

What type of job will AI and data science give me in the future?


Data science is more than just a buzzword: there are, according to McKinsey &

The company, six distinct disciplines in it. AI, which stands for artificial intelligence,

is one of those. A person who focuses on AI may focus on developing systems that can

learn and respond like humans do (through machine learning)or that use computational

methods inspired by biology (known as neural networks). These days, a lot of people

have started thinking about how we might use these technologies in our lives–whether

they’re being used to answer medical questions or to drive our cars. This has created

some confusion over what it means to be a data scientist. As such, some people have taken

up arms against calling themselves one.

What are the skills to learn first if I choose AI/data science?


There are many tools that people who want to learn AI and Data Science can

start with. R, Python, Tableau and Microsoft Power BI are great options. If

a person is very interested in developing games they should try out Unity.

Once a person is comfortable with coding they can either go into deep

learning if they want, or move on to project management software such

as Jira and Trello.

Which tools should I use (R, Python)?


Artificial intelligence (AI) and machine learning (ML) are quickly

gaining traction in both academia and in commercial environments.

However, before jumping into AI, it’s important to understand how ML

is being used. It should also be noted that when people say machine

learning they don’t always mean AI – they could mean statistical

techniques such as neural networks or regression. Machine learning

encompasses any application of computer systems that improve

automatically through experience and from past performance, rather than

following explicit programming instructions.

Where can I find help with learning AI/data science online?


If you want to learn more about AI, Dataquest, and Andrew Ng’s Machine

Learning courses are a great place to start. If you have programming experience,

Coursera’s Deep Learning Specialization is a fantastic way to put your skills into

practice. However, if you are new to both AI and coding, I would advise studying

Python. It’s one of the most popular languages used in machine learning and deep

learning applications today. It’s also relatively easy to pick up, which means you

can focus on more complex concepts instead of wasting time getting up to speed

with syntax. To help get started, check out free online resources like Udacity’s Intro

to Computer Science: Building Programs and Codeacademy’s Python track.

Useful Books on AI/Data Science


Looking into artificial intelligence and data science? Here are some books on these

topics that can help you get started.

Learn More

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