Data

What are data professionals planning to learn this year? Python, deep learning, yes. But also…

4 min read

One thing that every data professional absolutely dreads is the day their skills are no longer relevant in the market.

In an ever-changing tech landscape, one must be constantly on the lookout for the most relevant, industrially-accepted tools and frameworks. This is applicable everywhere – from application and web developers to cybersecurity professionals.

Not even the data professionals are excluded from this, as new ways and means to extract actionable insights from raw data are being found out almost every day. Gone are the days when data pros stuck to a single language and a framework to work with their data. Frameworks are more flexible now, with multiple dependencies across various tools and languages. Not just that, new domains are being identified where these frameworks can be applied, and how they can be applied varies massively as well.

A whole new arena of possibilities has opened up, and with that new set of skills and toolkits to work on these domains have also been unlocked.

What’s the next big thing for data professionals?

We recently polled thousands of data professionals as part of our Skill-Up program, and got some very interesting insights into what they think the future of data science looks like.

We asked them what they were planning to learn in the next 12 months. The following word cloud is the result of their responses, weighted by frequency of the tools they chose:

What data professionals are planning on learning in the next 12 months

Unsurprisingly, Python comes out on top as the language many data pros want to learn in the coming months. With its general-purpose nature and innumerable applications across various use-cases, Python’s sky-rocketing popularity is the reason everybody wants to learn it.

Machine learning and AI are finding significant applications in the web development domain today. They are revolutionizing the customers’ digital experience through conversational UIs or chatbots. Not just that, smart machine learning algorithms are being used to personalize websites and their UX. With all these reasons, who wouldn’t want to learn JavaScript, as an important tool to have in their data science toolkit? Add to that the trending web dev framework Angular, and you have all the tools to build smart, responsive front-end web applications.

We also saw data professionals taking active interest in the mobile and cloud domains as well. They aim to learn Kotlin and combine its power with the data science tools for developing smarter and more intelligent Android apps. When it comes to the cloud, Microsoft’s Azure platform has introduced many built-in machine learning capabilities, as well as workbench for data scientists to develop effective, enterprise-grade models. Data professionals also prefer Docker containers to run their applications seamlessly, and hence its learning need seems to be quite high.

[box type=”shadow” align=”” class=”” width=””]Has machine learning with JavaScript caught your interest? Don’t worry, we got you covered – check out Hands-on Machine Learning with JavaScript for a practical, hands-on coverage of the essential machine learning concepts using the leading web development language. [/box]

With Crypto’s popularity off the roof (sadly, we can’t say the same about Bitcoin’s price), data pros see Blockchain as a valuable skill. Building secure, decentralized apps is on the agenda for many, perhaps.

Cloud, Big Data, Artificial Intelligence are some of the other domains that the data pros find interesting, and feel worth skilling up in.

Work-related skills that data pros want to learn

We also asked the data professionals what skills the data pros wanted to learn in the near future that could help them with their daily jobs more effectively. The following word cloud of their responses paints a pretty clear picture:

Valuable skills data professionals want to learn for their everyday work

As Machine learning and AI go mainstream, so do their applications in mainstream domains – often resulting in complex problems. Well, there’s deep learning and specifically neural networks to tackle these problems, and these are exactly the skills data pros want to master in order to excel at their work.

[box type=”shadow” align=”” class=”” width=””]Data pros want to learn Machine Learning in Python. Do you? Here’s a useful resource for you to get started – check out Python Machine Learning, Second Edition today![/box]

So, there it is! What are the tools, languages or frameworks that you are planning to learn in the coming months? Do you agree with the results of the poll? Do let us know.

Read Next

What are web developers favorite front-end tools? Packt’s Skill Up report reveals all

Data cleaning is the worst part of data analysis, say data scientists

15 Useful Python Libraries to make your Data Science tasks Easier

Amey Varangaonkar

Data Science Enthusiast. A massive science fiction and Manchester United fan. Loves to read, write and listen to music.

Share
Published by
Amey Varangaonkar
Tags: AI News

Recent Posts

Top life hacks for prepping for your IT certification exam

I remember deciding to pursue my first IT certification, the CompTIA A+. I had signed…

3 years ago

Learn Transformers for Natural Language Processing with Denis Rothman

Key takeaways The transformer architecture has proved to be revolutionary in outperforming the classical RNN…

3 years ago

Learning Essential Linux Commands for Navigating the Shell Effectively

Once we learn how to deploy an Ubuntu server, how to manage users, and how…

3 years ago

Clean Coding in Python with Mariano Anaya

Key-takeaways:   Clean code isn’t just a nice thing to have or a luxury in software projects; it's a necessity. If we…

3 years ago

Exploring Forms in Angular – types, benefits and differences   

While developing a web application, or setting dynamic pages and meta tags we need to deal with…

3 years ago

Gain Practical Expertise with the Latest Edition of Software Architecture with C# 9 and .NET 5

Software architecture is one of the most discussed topics in the software industry today, and…

3 years ago