Which is Better: Data Science or Artificial Intelligence?

These days, picking the best stream and developing a career in it have grown increasingly difficult. A poor decision while selecting a stream can cause frustration and occasionally result in mid-course withdrawal from the study.

You must take into account a variety of aspects, whether you are entering the corporate sector for the first time or are at a crossroads in your life where you need to change careers. Choosing between artificial intelligence and data science, two of the most well-liked professional fields today, has a similar effect.

Today’s world is digital, and there’s no denying that data is the new oil. Businesses gather enormous volumes of data, analyze it, and get valuable insights from it. Making better-informed business decisions is further aided by these insights. This procedure is the exclusive result of data science.

Companies are simultaneously looking for ways to enhance their procedures in order to get better results more quickly. One strategy that offers hope in these situations is automation. Here, artificial intelligence plays a significant role. As a subfield of computer science, artificial intelligence is concerned with creating tools that can effectively do manual activities without the need for supervision.

Owing to the rising popularity of these two fields, many training providers have started offering artificial intelligence courses and Data science Bootcamps online to help professionals become job-ready and advance their careers in these areas. However, you may be confused about whether to go for data science or embark on an artificial intelligence career. So, this article will tell you more about both these career options and how to make the right decision for yourself. 

A Career in Data Science 

Data science is a multidisciplinary field that combines tools, techniques, and methods to generate actionable insights from data. It incorporates the principles and practices from fields like statistics, mathematics, machine learning, and computer engineering in order to transform raw data into a usable format and analyze it to identify hidden trends and correlations.

Looking at such trends, business leaders can make better decisions, design state-of-the-art products, increase their revenue, and ensure a better customer experience. 

Stepping into the world of data science means embarking on a career as a data scientist, data analyst, data engineer, data architect, database administrator, and similar job roles. Out of these, you may have surely heard about the data scientist role – termed the sexiest job of the 21st century. Indeed, the job role of data scientist has created much hype in the technology sector and is one of the most in-demand designations of present times.

Apart from the rising demand, this job role is associated with high salaries. The reason is not everyone possesses the advanced set of skills required for a data scientist role, and companies are ready to pay higher wages when they find a suitable candidate.  

A Career in Artificial Intelligence 

Artificial Intelligence is a major driving technology of the Fourth Industrial Revolution. Even if you don’t belong to the technology sector, you must be familiar with the buzz created around artificial intelligence. Even sci-fi movies show the use of artificial intelligence and the imagination regarding how it can impact our future lives.

AI basically refers to the replication of human intelligence functions by machines, particularly computer systems. Some of the important sub-fields of AI include machine learning, natural language processing, computer vision, speech recognition, and expert systems.

When you think of a career in this domain, you can explore job roles like Artificial Intelligence Engineer, Machine Learning Engineer, NLP Specialist, AI researcher, robotics scientist, deep learning engineer, and so on. AI engineer is one of the best emerging job roles that promises bright career growth prospects.

On the other hand, a machine learning engineer can explore his skills both in data science as well as artificial intelligence. Today, the fascinating applications available on the market like voice assistants (Alexa, Siri), autonomous cars, drones, face recognition applications, and chatbots are all powered by AI and have been developed by professionals well-versed in AI and machine learning. 

Which is Better?

Now looking at both the fields, there is no definite answer to which is a better career option. Both data science and artificial intelligence are promising for the future and find good applications across business verticals. Even when it comes to job opportunities, there are plenty for data scientists as well as machine learning engineers. Both job roles, in fact, have comparative salary packages, and one can’t be declared as the best according to given factors. 

To decide between the two options, you should analyze where your interests lie. Don’t blindly go for the option that gives you a higher salary, your skills and preferences also matter. If you love experimenting with data and identifying hidden trends and patterns, then data science is suitable for you. However, if you are more interested in building AI-powered applications, meaning machines that are capable of performing human-like tasks automatically, then AI is the domain for you. 

For both data scientist and AI engineer job roles, you need to have strong technical knowledge and work dedicatedly to learn their concepts from scratch and apply them to solve real-world problems. So, take an appropriate training course and learn either about data science or AI. 

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