• Articles
  • Tutorials
  • Interview Questions
  • Webinars

Data Science vs Artificial Intelligence

Data Science vs Artificial Intelligence

In this Data Science vs Artificial Intelligence blog, you will cover the topics mentioned below:

Introduction to Data Science

Data Science is a reigning field in the IT industry and has conquered almost every industry today. It is a broad field that mainly pertains to data processes and data systems, and it aims to work on these datasets to derive valuable information from them. In this domain, data acts as the fuel that helps in extracting useful and meaningful insights regarding companies and in identifying current market trends

This technological field consists of several topics, including mathematics, statistics, and programming. Hence, to pursue a career in Data Science, you must be proficient in these subjects to be able to extract patterns from the given data and conceive them usefully.

You have learned the basics of Data Science now. However, I am sure you would want to know the several steps involved in this technology. These steps include extraction, manipulation, maintenance, and visualization of data that allow you to forecast future occurrences of events.

After learning about Data Science, there might be a question stuck in your head: What is the need to study and understand data?

Let’s take a real-life Data Science use case, Facebook. This example will help you understand why Data Science is necessary and how it helps not only the IT industry to grow but also other industries, including e-commerce, finance, telecommunication, etc.

Level Up Your Tech Career: Specialize in AI Engineering
Dominate AI with Our In-Demand Certification
quiz-icon

Facebook Revolutionises Social Media with Data

Today, Facebook is the leader in the social media world. Having millions of users signed up to the platform from across the globe, it uses a vast amount of research via Data Science to extract information regarding the social interactions of its users. It uses advanced Data Science techniques to understand the behavior of the users and, further, to improve their product or application. This is just one use case scenario of this technology among the lot. Hence, with this, you can conclude that Data Science is among the highest-utilized fields today.

Now, let’s take a look at Artificial Intelligence and what it means.

What Do You Understand from Artificial Intelligence?

Traditional algorithms in AI were given a set of goals for developing themselves. However, more recent and trending algorithms like Machine Learning and Deep Learning allow you to understand the trends and patterns in the given data and, thus, find the aim of the data.

In Artificial Intelligence, there are mainly three steps involved: learning, reasoning, and self-correction. Moreover, the frameworks in AI can be used for deep neural network computations.

To understand this technology a little better, let’s take an example of using AI in the real world. Here, let’s discuss the use and implementation of AI in the field of personal security.

Use of AI in Personal Security Systems

Have you recently been a part of a big public event or traveled in flight? If you did, you must have noticed the long queues for security checks. Many a time, this must have been inconvenient and frustrating for you, and with a pandemic like Covid-19 hitting the world, it can get scary. With Machine Learning, a subset of AI, false alarms can be eliminated. Also, these machines can detect things that human scanners tend to miss during the process of screening in airports, concerts, stadiums, etc. This can help in speeding up the security processes and saving a lot of time for the security in charge, as well as the passengers or the attendees of the events.

After learning in detail about both of these technologies, you can decide between Data Science and Artificial Intelligence courses and learn the technology best suited for you.

You have read about both Data Science and Artificial Intelligence. Now, let’s discuss the differences between them.

Difference Between Data Science and Artificial Intelligence

After learning about these technologies, you might be wondering, “Which is better, Data Science or Artificial Intelligence?” Below is a comparison table that aims to help you decide. It consists of some of the key differences between the two most sought-after technologies:

Comparison FactorData ScienceArtificial Intelligence
MeaningData Science aims to curate massive data for analytics and visualizationArtificial Intelligence helps in implementing data and the knowledge of machines
SkillsYou need to use statistical techniques for development and designYou must use algorithms for development and design
TechniqueData Science makes use of the Data Analytics techniqueAI uses Deep Learning and Machine Learning techniques
ObservationIt looks for patterns in data to make well-informed decisionsIt imposes intelligence in machines using data to make them respond as humans do
Solving IssuesIt utilizes parts of a loop or program to solve particular issuesAI, however, represents the loop for planning and perception
ProcessingIt uses a medium level of data processing for data manipulationIt uses high-level processing of scientific data for data manipulation
GraphicIt allows you to represent data in several graphical formatsIt helps you use an algorithm network node representation
Tools InvolvedData Science makes use of tools, such as SAS, SPSS, Keras, R, Python, etc.AI uses tools viz. Shogun, Mahout, Caffe, PyTorch, TensorFlow, Scikit-Learn, etc.
ApplicationsApplications of Data Science are dominantly used in Internet search engines, such as Yahoo, Bing, Google, etc. AI applications are used in several industries, including transport, healthcare, manufacturing, automation, etc.
Build the Future of AI & Become an AI Engineer
Realize Your AI Ambitions with Our Elite Certification
quiz-icon

Data Science and Artificial Intelligence Jobs

Both AI and Data Science are lucrative career choices especially because of their exponential growth rate. Although, both these fields are interrelated and not mutually exclusive. When considering the skills required to find jobs in these fields, they generally coincide with each other.

Data Science Job Roles

Some of the top-most, high-paying jobs available in 2021 in the Data Science world include:

Prerequisites for Data Science Job Roles

Some of the skills that you need to have to pursue a career in Data Science associated job roles are as follows:

  • Programming skills in languages such as C, C++, Python, and R
  • Reporting and visualization of data
  • Knowledge of statistics and mathematics
  • Experience in risk analysis
  • Understanding of Machine Learning techniques
  • Knowledge of data structures and data warehousing

Artificial Intelligence Job Roles

Like Data Science, even this field has a varied range of job roles available in leading organizations with high salaries. A few of these roles are mentioned below:

  • Data Scientist
  • Robotics Scientist
  • Machine Learning Engineer
  • Big Data Engineer
  • Software Developer
  • Business Intelligence Developer
  • AI Research Scientist

Prerequisites for Artificial Intelligence Job Roles

Following are the must-have technical skills necessary to build a career in AI:

  • Skills in any programming language, such as C++, Python, or Java
  • Knowledge of data evaluation and data modeling
  • Experience in probability and statistics
  • Understanding of distributed computing
  • Expert knowledge of Machine Learning algorithms

You will notice that the skill requirements in both fields overlap as mentioned earlier. Now, let’s take a look at the salaries earned by professionals in these trending technologies.

Artificial Intelligence vs Data Science Salary

As per Glassdoor, the salary of Data Scientists in the United States is about US$113k per annum and it may rise up to about US$154k per annum. On the other hand, AI Engineers earn approximately US$76k per annum. This amount may increase to about US$107k per annum depending on experience, performance, and the company you work for.

In this blog on ‘Data Science vs Artificial Intelligence,’ you have learned about these technologies in detail. Further, you gained knowledge of the several differences between AI and Data Science. Moreover, you came across the job opportunities available in these domains and identified the Artificial Intelligence skills you need to have to assuming the job roles in the respective domains. So, master these technologies by taking up a course we offer and build your career in any of these popular fields.

Get 100% Hike!

Master Most in Demand Skills Now!

Conclusion

In this Data Science vs AI blog, we covered all the details of the two subjects and how they are interchangeably used. While Data Science tools deal with the computational calculations performed on data, an AI tool generates predictions based on the data. Both fields are highly in-demand in today’s scenario.

The only thing that you need to understand is the field of your interest. If you are someone who is good with the analysis of data then you may develop an inclination toward data science, whereas, if you are someone who likes the concepts of AI and the immense potential it holds, then a job in the same field will suit you better.

Frequently Asked Questions (FAQs)

Which is better data science or artificial intelligence salary?

Both fields offer lucrative salaries, but artificial intelligence roles often command higher salaries due to the specialized skills and potential impact of AI technologies.

Is data science easier than artificial intelligence?

Data science may be more accessible initially, while artificial intelligence may require a deeper understanding of complex algorithms and machine learning techniques.

Which branch is better artificial intelligence or data science?

Both are valuable; choosing between them depends on personal interests. AI concentrates on creating algorithms, while data science emphasizes acquiring insights from data.

Which is better CSE data science or artificial intelligence?

It depends on individuals interests and their career goals. AI is suited towards machine learning and automation, whereas data science aims on analytics and insights.

Can data science be replaced by AI?

AI can automate some data analysis tasks, but the interpretation and strategic decision-making aspects of data science are irreplaceable.

Which branch of CSE has the highest salary?

Typically, specializations in artificial intelligence, machine learning, and data science are among the highest paying branches in Computer Science Engineering.

What is the salary of artificial intelligence in India per month?

Salaries vary widely, but AI professionals in India can earn between INR 50,000 to over INR 150,000 per month, depending on experience and the employer.

What is the salary of AI ML engineer?

AI/ML engineers can have an average payroll ranging anywhere from $70,000 to over $150,000 annually. This pay depends on multiple factors like experience, location, and organization as well.

Who earns more AI or data science in India?

AI specialists may have a better payroll, as they need to have some specialized skill set. Though, both need highly experienced and knowledgeable personnel’s, and have a high and substantial earning.

What is the salary of AI engineer in Google?

An AI engineer at Google earns somewhere from  $110,000 to over $200,000 annually. This depends on the factors like experience, expertise and locations

About the Author

Principal Data Scientist

Meet Akash, a Principal Data Scientist with expertise in advanced analytics, machine learning, and AI-driven solutions. With a master’s degree from IIT Kanpur, Aakash combines technical knowledge with industry insights to deliver impactful, scalable models for complex business challenges.