Almost two decades ago, people were amazed by laptops with 40 GB of storage. Today, smartphones hold about 30 GB of data and top-range Apple iPhones have over 500 GB of storage. Gigabytes may be a thing of the past since data in the world is growing exponentially. Now, businesses use terabytes, petabytes, exabytes, and zettabytes. This article at Analytics Insight speaks about five ways learning data science and artificial intelligence can boost your career.
Data Science and Artificial Intelligence Are Booming
New-age technologies support three vital business needs. Those are automating processes, understanding customer behavior through data analysis, and engaging with customers effectively. Thus, it is leading to a spike in demand for skilled individuals and widening the gap between supply and demand in data and AI fields. Therefore, offering freshers and professionals a chance to upskill and further their careers. Here are five ways data science and AI will jump-start your career:
Demand for Artificial Intelligence and Data Science Professionals
Almost all sectors utilize artificial intelligence and data science technologies to improve their performance. Regardless of size, all companies are looking for ways to monetize their data. Therefore, they are constantly looking for individuals to collect, read, and analyze data actively.
Talent Supply and Demand
The shortage of AI and data science talent has led to high demand for skilled professionals. Large companies are also increasing their AI and data science training and hiring efforts to bridge that gap.
Step Outside Your Comfort Zone
On Kaggle, it is okay to look at other people’s code. You will not understand it all right away, but that is okay too. If you are comfortable with only the code in your notebook, you are not learning anything new.
Learn the Basics
Learn basic machine learning (ML) algorithms to understand how these algorithms work. Soon, you will be able to apply ML without knowing its mathematical formulas. Therefore, understanding the reasoning of ML models will help you in using these algorithms.
With Python, R, SQL, and ML expertise, you have the expertise to analyze any dataset. However, the most challenging part is to build the data pipeline and integrate it with cloud services to push it into production.
To read the original article, click on https://www.analyticsinsight.net/5-ways-learning-data-science-ai-can-help-you-succeed-in-your-career/