Data Science and Big Data are the biggest industry buzzwords in 2018. Experts believe that artificial intelligence (AI) systems will continue to reign supreme in the technology marathon through 2019.

“More than 40 percent of data science tasks will be automated by 2020.”

–Gartner

The data science trends for 2019 are essentially a continuation of some of the key trends of 2018, including areas such as:

• Machine learning (ML)
• Artificial intelligence (AI)
• Big data
• Edge computing
• Blockchain
• Digital twins
• Serverless computing

Because data science is so vast and challenging to navigate, we’ve compiled a list of the most popular data science articles that dominated the industry over the past 12 months. 

Top 3 Vertabelo Academy Articles

1. So You Want to Be a Data Scientist?
– Ramkumar Balasubramanian

A complete guide for anyone who wants to learn more about the prospects of becoming a data scientist. Ramkumar discusses not only the professional skills of a data scientist but also the growing need for data scientists and the scope of work of a data scientist.

2. Data Science: Market Demand or Just Hype?
– Marija Ilic

Data science is certainly trending, but how many of us actually understand what data science is about? Maria provides insight into the field of data science and clarifies common misconceptions about this field.

3. Can Python Displace R for Data Science?
– Marija Ilic

Python and R are two of the hottest programming languages for data science professionals, but which one is better? And is it possible that Python could one day replace R? Read Marija’s article to learn more about the similarities and differences between R and Python.

Top 5 Miscellaneous Data Science Articles

1. 6 data analytics trends that will dominate 2018
– Thor Olavsrud

Published by CIO.com, this article predicts that data analytics will either become more value driven or simply die out in the future. Thor talks about the implementation of robust data governance strategies and the introduction of better analytics tools to predict better quality data.

2. Data trends 2018: Three trends you should know
– Tripp Smith

With automated data science, digitized financial services, and serverless clouds, this year has certainly seen some innovative data science trends. Read Tripp’s full article to learn more.

3. Don’t worry about AI going bad – the minds behind it are the danger – John Naughton

Are you obsessed with AI? It’s everywhere, and though a threat from machines is a distant future right now, there are potentially three domains that are a cause for concern: digital security, physical security, and political security.

4. Top Skills Data Scientists Need To Learn in 2018
– Daniel Gutierrez

Data scientists are in high demand. And with attractive packages and perks, it’s no wonder that people are looking to switch careers. But competition is high, and you need to keep refining your skills to stay relevant. This article reviews the trending tech skills that every data scientists must learn in 2018: Spark, Apache Mahout, and Tableau, to name a few.

5. Will data science evolve over the next decade?
– Eric Mayefsky

As a data science professional, student or an enthusiast, are you wondering what the future holds for data science over the next 10 years? The author, Head of Data Science at Quora, answers this question in his article and explains what path this profession will take in the future. He discusses the emergence of the data scientist as a more coveted profession than data product managers and analysts. Data science as a profession will expand, and the role of data professionals in business will certainly increase.

Conclusion

There you have it! These are some of the most insightful data science 2018 articles for beginners. Follow our blog if you’re interested in staying up to date on the latest in data science. 

Looking to pursue data science skills? Be sure to check out the introductory course Introduction to Python for Data Science. It will help you sharpen your analytical thinking and combine it with data science skills.