The terms ‘data science’ and ‘artificial intelligence’ have been one of the trendiest words in the past few years. As both these branches come under Information technology, many people think they are the same. However, there are a lot of things that differentiate data science from artificial intelligence. Do you want to make a career in either of these? You may need to know the similarities and differences in both these fields in every aspect. To help you understand it in detail, we have discussed the similarities and differences between data science and artificial intelligence in this blog.
Data science is extracting important data and analyzing it to get meaningful insights. These meaningful insights help organizations make business decisions, such as increasing sales, efficiency, and profits and reducing losses, expenditures, discrepancies, etc. Data science is one of the strongest pillars of almost every business today.
As the name suggests, artificial intelligence is where a computer or a computer-controlled robot performs the tasks commonly associated with humans. In simple words, the computer working in a way a human thinks or works is called artificial intelligence. In today’s world, artificial intelligence is everything about advancements and innovations. Since it makes the human task easy, it has been gaining huge popularity all over the globe.
You may also like to read how artificial intelligence re-invents the IT industry.
Data science comprises artificial intelligence. Hence, artificial intelligence is a part of data science. Hence, there will be a few common factors between these two. They are explained as follows.
The main goal of data science and artificial intelligence involves researching a problem, analyzing it, and finding an algorithmic solution. In addition, both of these run on cloud-based platforms.
The data scientist and AI scientist must have similar soft skills, such as strong communication, time management, problem-solving, decision-making, critical thinking, interpersonal skills, analytical thinking, leadership skills, etc.
The qualification requirement for both data science and artificial intelligence is the same. Both careers can be pursued with a bachelor’s or master’s degree in software engineering, computer science, or any other IT-related degree.
The most common data science and artificial intelligence tools are programming tools such as Java, Python, TensorFlow, Scikit-learn, etc.
In data science vs artificial intelligence, these terms have a lot of differences in terms of goals, types, models, applications, uses, etc. that are explained below:
Data science is a process where you gather and analyze existing data to find meaningful insights. In contrast, artificial intelligence is a process where you analyze future patterns and trends of the data.
Data science uses all kinds of data, including structured, unstructured, and semi-structured data. On the other hand, artificial intelligence uses only standardized forms of data.
The different kinds of tools used in AI and data science are as follows:
The methods and techniques used in data science are mostly based on mathematics and statistics, whereas artificial intelligence uses most machine learning algorithms to find solutions.
Data science builds statistical models for decision-making, whereas artificial intelligence builds automated models that ease human efforts.
Data science applications are mostly used for search engines such as Google and Yahoo. They are also used in various data-driven fields such as marketing, advertising, banking, information technology, etc. On the other hand, artificial intelligence applications are used in industries such as healthcare, finance, manufacturing, transport, logistics, etc.
Data science can be used when you need a quick mathematical computation, exploratory data analysis (EDA), predictions, and analysis of trends and patterns. Artificial intelligence is used when making quick decisions or conducting a risk assessment.
Some examples of data science are process optimization, market trends, financial analysis, etc. The most famous examples of artificial intelligence are chatbots, voice assistants, robots, etc.
Know more about the role of artificial intelligence in the digital marketing.
Which field are you inclining toward – data science or artificial intelligence? The answer here will depend on your plans and interests. Due to increasing digitalization, the demand for both data science and artificial intelligence has been reaching the sky. Both these fields are quite different in terms of job roles, career opportunities, and pay packages. Hence, these fields as career options have often been in cut-throat competition. Make sure to choose any of these, depending on your area of interest. If you are interested in mathematics and statistics, data science is your best option. However, artificial intelligence is the right fit for you if you are interested in deep learning and algorithms.
Today, data science and artificial intelligence are two of India’s most sought-after career options after college. With data science, you will be eligible for data scientist and data analyst roles. On the other hand, by learning artificial intelligence, you get to work as an AI specialist, AI engineer, machine learning engineer, etc. Hence, machine learning engineer vs data scientist, both the job roles are highly in demand today. Opting for either of these will lead to a successful career path.
Online Manipal is the best platform for students wishing to graduate and build a career in data science or artificial intelligence. Here, we provide you with various degree programs and certifications in data science and machine learning from top-rated Manipal Academy of Higher Education (MAHE) which will help you master all the key concepts and get real-life industry experience in learning the same. Check out our courses today!
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