In this Data Science vs Artificial Intelligence blog, you will cover the topics mentioned below:
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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.
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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.
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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.
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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 Factor | Data Science | Artificial Intelligence |
| Meaning | Data Science aims to curate massive data for analytics and visualization | Artificial Intelligence helps in implementing data and the knowledge of machines |
| Skills | You need to use statistical techniques for development and design | You must use algorithms for development and design |
| Technique | Data Science makes use of the Data Analytics technique | AI uses Deep Learning and Machine Learning techniques |
| Observation | It looks for patterns in data to make well-informed decisions | It imposes intelligence in machines using data to make them respond as humans do |
| Solving Issues | It utilizes parts of a loop or program to solve particular issues | AI, however, represents the loop for planning and perception |
| Processing | It uses a medium level of data processing for data manipulation | It uses high-level processing of scientific data for data manipulation |
| Graphic | It allows you to represent data in several graphical formats | It helps you use an algorithm network node representation |
| Tools Involved | Data 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. |
| Applications | Applications 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. |
With the help of this comprehensive comparison table, you can make a choice of pursuing your career in either Artificial Intelligence or Data Science. If you want to pursue your career in AI, keep a glance at our blog on Artificial Intelligence Course Syllabus.
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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:
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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
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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
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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.
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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.
Also read – Data Mining vs. Data Science
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.
Prepare yourself for the industry by going through this top Artificial Intelligence Interview Questions and Answers!
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 focuses on creating smart algorithms, while data science emphasizes deriving insights from data.
Which is better CSE data science or artificial intelligence?
It depends on personal interests and career goals. AI is geared towards machine learning and automation, while data science focuses 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 earn anywhere from $70,000 to over $150,000 annually, depending on experience, location, and the employing organization.
Who earns more AI or data science in India?
Generally, AI specialists might earn more due to the specialized nature of their skills, but both fields are highly lucrative with substantial earning potential.
What is the salary of AI engineer in Google?
Salaries for AI engineers at Google can range from $110,000 to over $200,000 annually, depending on experience, location, and the specific role within the company.