Data Science vs Artificial Intelligence: 9 Differences

Data-Science-vs-Artificial-Intelligence

In this digital era, terms like “data science” and “artificial intelligence” are often used interchangeably, but they are not the same.

As we further move into this article, you get to learn more about data science vs artificial intelligence. However both are from the same branch known as computer science, but there are many dissimilarities between them. If you’re interested in pursuing a career in tech, whether it is data science or artificial intelligence, In that case, you may be looking at different aspects of both to see which area is better for you.

While data science may contribute to some aspects of AI, it does not reflect all of them. Moreover, data science is the most popular field in the world today. However, real artificial intelligence is far from reachable, but nowadays, it is possible. Let’s first know what data science and artificial intelligence are. After that, we will explore Data Science vs Artificial Intelligence and their key differences to clear all your confusion. 

So without wasting any time, let’s get started!

What is Data Science?

Simply data science is a collection of data to analyze, and we decide on behalf of it. Data Science is a subset of Artificial Intelligence. 

In simple terms, Data science involves various fields like mathematics, statistics, and programming. Therefore, a data scientist must be proficient in understanding the trends and patterns in the data.

Data science is believed to have brought about a fourth industrial revolution. On the other hand, it is now at the heart of business decision-making. Companies have realized the enormous value of data processing and analysis. 

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You’ll use data science when:  

  • Need for exploratory data analysis (EDA)
  • The situation calls for fast mathematical processing
  • Patterns and trends need to be identified
  • Statistical insight is a requirement
  • You need to use predictive analytics

What is Artificial Intelligence?

Artificial Intelligence is the intelligence that is owned by machines. Artificial Intelligence uses the algorithms made by humans to perform autonomous actions. On the other hand, Artificial Intelligence also uses several software engineering principles for developing solutions to problems that are already existing.

Recently, many major technologies like Amazon, Google, and Facebook have been leaning toward Artificial Intelligence to develop autonomous systems.

You’ll use AI when:

  • You need to perform a risk analysis
  • Precision is required
  • Repetitive tasks are involved
  • Fast decision-making is needed
  • You require logical decision-making without emotional interference

What’s The Difference Between Data Science & Artificial Intelligence?

Data Science and Artificial Intelligence are two separate fields, each with its own unique set of skills. Below are some key differences between data science and artificial intelligence.

  • The significant difference is that data science involves preprocessing, analysis, prediction, and visualization. In contrast, AI implements a predictive model to foresee events. 
  • Data science is an umbrella term for statistical, design, and development methods. On the other hand, Artificial intelligence involves algorithm design, development, efficiency, conversions, and deploying these designs and products.
  • Data science is primarily concerned with data analysis and data analytics (where it uses past and present data to predict future data). Whereas, Artificial intelligence is concerned with machine learning. 
  • If we talk about data science, it is a broad discipline that includes the study of AI. On the other hand, artificial intelligence is just one niche area of data science. 
  • If we talk about data science, it was developed to find hidden patterns and trends in data. On the other hand, artificial intelligence handles data freely, removing the human from the entire task to work on its own.
  • Using data science, complex models can be built for extracting various facts, insights, and statistical techniques. On the other hand, artificial intelligence is meant for building models that have more human understanding to a certain level.
  • R and Python are the tools used in data science. Kaffee, TensorFlow, and sci-kit-learn are tools used in AI. 
  • Data science does not apply much scientific processing compared to AI.
  • Data Science deals with structured and unstructured data. Whereas Artificial Intelligence uses logic and decision trees. 
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Data Science vs Artificial Intelligence Salaries Expectation

Jobs are expected to grow in all areas of the economy. Data science and artificial intelligence are at the top of the list in rapidly growing fields. The reason is that there are so many jobs in these fields nowadays because the world is transforming into the era of big data. So, let’s know who earns more AI or Data science. Below is a quick comparison of salaries between data scientists and artificial intelligence engineers as per the payscale.

Data Science Salary:

The starting salary is rapidly increasing due to the heavy demand for data scientists. The average salary of a data scientist is approximately $97,579 per year. On the other hand, an entry-level or beginner data scientist can earn as much as $69,000 per year, while experienced data scientists make as much as $136,131 per year.

Artificial Intelligence Salary:

As career opportunities for Artificial Intelligence engineers rapidly expand. As a result, AI engineers’ salaries will continue to climb. Similarly, the average annual wage of an artificial intelligence engineer is well above $125,000. However, an entry-level artificial intelligence can earn as much as $82,000 annually, while experienced data scientists make as much as $211,526 annually.

Data Science vs Artificial Intelligence: Google Trends

Data science is marked as blue, and artificial intelligence is marked as red on the graph. It shows the “ups and downs” of both in the form of blue and red lines.

This graph shows the data for the past five years worldwide as per google trends. So, the popularity of artificial intelligence is higher than data science. But it does not mean that AI is better than data science. Both have their disadvantages and advantages over the other. 

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Difference Between Data Science vs Artificial Intelligence: Tabular Form 

Parameters Data ScienceArtificial Intelligence
BasicsData Science is a detailed process mainly involving pre-processing analysis, visualization, and prediction.AI is the implementation of a predictive model to forecast future events and trends.
Types of dataData Science will have various data types, including structured, semi-structured, and unstructured data.Whereas, AI uses standardized data in the form of vectors.
Tools usedThe tools utilized in Data Science are far more vast than those used in AI. The tools used in AI are less vast as compared to Data Science.
The technique usedData science uses the technique of data analytics, Data analysis.On the other hand, AI  uses a lot of machine learning techniques.
ApplicationsIts applications are advertising, marketing, Healthcare, etc.Its application is robotics, automation, etc.
Decision-makingData Science looks for patterns in data to make decisions.Artificial Intelligence looks to intelligence reports to make decisions.
Examples of ToolsPython, R, etc., are some of the tools used in data science.Whereas Kaffee, TensorFlow, and sci-kit-learn are tools used in AI. 
ExamplesFinancial analysis, Process optimization, and Customer trends are some examples.Chatbots, Robots, online gaming, and voice assistants are some examples.

Data Science vs Artificial Intelligence Job Roles

Artificial intelligence (AI) is often used interchangeably with data science. However, that is not entirely accurate. While data science is informed by the historical significance of AI, their goals and methodologies are somewhat different. AI explores whether a computer program can acquire human-like faculties such as learning and problem-solving. Data Science, on the other hand, is an umbrella term for extracting knowledge from data to make an intelligent decision. The two fields are similar in that they both involve extracting knowledge from data, but their approaches are different. 

On the other hand, some of you are interested in  Data science and Machine learning. So don’t worry here’s the difference between Data science vs machine Learning.

Data Science Job Roles

Some of the top-most, high-paying jobs available in 2022 in the data science world include:

  • Data Scientist
  • Data Engineer
  • Data Architect
  • Statistician
  • Data Analyst
  • Machine Learning Engineer
  • Database Administrator
  • Business Analyst

Artificial Intelligence Job Roles

Like Data Science, this field has various job roles in leading high-paying organizations. A few of these roles are mentioned below:

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

Conclusion

 Let’s recap what we have learned. This article explains some important differences between Data Science and Artificial Intelligence. In this data science vs artificial intelligence comparison, we learn the two terms are used interchangeably. Data Science is a field that uses AI to generate predictions, but it also focuses on transforming data for analysis and visualization. On the other hand, artificial intelligence is a tool for creating better products and enhancing their autonomy.

I hope you liked our explanation of Data Science vs Artificial Intelligence. 

FAQs 

Q1. Which is easy data science or Artificial Intelligence?

Compared to traditional statistical analysis techniques, machine learning has evolved as a better way of extracting and processing the most complex big data sets, thereby making data science easier and less chaotic.

Q2. Is data science same as Artificial Intelligence?

No, both data science and artificial intelligence are not the same. Data science and artificial intelligence are two technologies that are part of computer science, transforming the world continuously. 

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