Data Science and Artificial Intelligence (AI)7 min read

If you come in the group who have misconstrued that data science and artificial intelligence are the same? Well, that’s not the case! Data Science and artificial intelligence are different.

Data science is a field where we apply the methods to collect, analyze, and derive conclusive information from the data for the company’s betterment.

On the other hand, AI is a kind of development or intelligence of machines that imitate human intelligence.

This article details data science and artificial intelligence and their related aspects.

What is Data Science? 

Data science is a vital part of many enterprises. Data science produces massive amounts of data used in the IT industry. 

Primarily, data science is defined as the domain of study that deals with modern tools and techniques.

It is used to derive useful information and make business decisions, helping the business flourish. A simple data science course can make learning easier and more effective.

Lifecycle of Data Science 

The lifecycle of data science consists of five stages. They are as follows: 

1. Capturing: This stage includes gathering raw structured and unstructured data. The stage has different factors like data acquisition, entry, signal reception, etc. 

2. Maintaining: This stage takes up the raw data and puts it in a form that can be used further. It includes data warehousing, data cleansing, data processing, etc. 

3. Processing: In the processing stage, the data scientists take the data prepared and examine its patterns.

This helps them in determining how useful the processing is in predictive analysis. The processing stage includes data mining, clustering, data summarization, etc. 

4. Analyzing: Analyzing is the most important data science lifecycle. This stage involved data analysis in text mining, regression, predictive analysis, qualitative analysis, etc.

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5. Communication: Data reporting, decision-making, business intelligence, etc., are some important aspects of the communication stage.

This is the final stage of the data science lifecycle, wherein the analysts analyze the data in charts, graphs, reports, etc.

Now, there are certain prerequisites for data science. Let us have a look at them. 

Prerequisites for Data Science 

There are various technical concepts that a candidate must know before pursuing data science as a career. Have a look! 

1. Machine Learning 

If one wants to become a data scientist, he/she should have a great knowledge of machine learning.

Machine learning is the backbone of all the concepts of a data scientist. A solid grasp of machine learning can help candidates a lot! 

2. Modeling 

Many mathematical models enable you to make predictions and quick calculations on what the candidate knows about data science.

Modeling is an integral part of machine learning that includes identifying the algorithms to solve a given problem.   

3. Statistics 

Statistics are known as the core of data science. A stronghold on statistics can help one gain intellect and meaningful results. 

4. Programming 

One of the major prerequisites of data science is programming skills. A candidate should know some programming skills to execute a data science project.

The most common programming language that candidates can easily learn is Python.

Python is very popular because one can easily understand it and can support multiple machine learning and data science libraries. 

5. Database 

A successful data scientist needs to have complete knowledge of how the databases work and how one can manage them. 

A candidate can apply for several courses to acquire the data scientist’s skills. One should know the data science course fees in India before applying to any course.

A data scientist determines the correct set of data and variables to collect and extract data. These scientists analyze and identify the patterns and trends to find solutions to several problems. 

What is Artificial Intelligence?

Artificial Intelligence is a branch of computer science that includes building smart machines capable of completing tasks and performing better.

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Computer systems complete tasks that require human intelligence. This is what Artificial Intelligence is all about! 

Types of Artificial Intelligence 

There are four types of artificial intelligence:

1. Reactive Machines: 

Reactive machines are a form of Artificial Intelligence that perform basic operations. In this type, no learning takes place. Machine learning performs the functions that require human intelligence. 

Now, there are static machine learning models which are reactive. The architecture of such models is very easy and can be found across the web.

Such models can be downloaded, traded, and loaded into the toolkit of the developers.  

2. Limited Memory: 

Limited ability is defined as the ability of artificial intelligence to store past data and predictions.

With little memory, the architecture of machine learning can become very complex and hard to understand.

Every model requires limited memory for reactive machine types. There are three kinds of limited memory: reinforcement learning, long short-term memory, and evolutionary generative networks. 

3. Mind Theory:

We have yet not reached the mind theory type of artificial intelligence. At present, we only have the above two types of artificial intelligence.

Theory of mind can be primarily seen in self-driving cars. In such cars, artificial intelligence will be able to interact with the thoughts and emotions of human beings. 

The machine learning models do a lot for companies and individuals to interact and fulfilling tasks. 

4. Self-Aware: 

It is being said that artificial intelligence will become self-aware in the future. This kind of artificial intelligence exists in the stories till now.

A self-aware artificial intelligence can work and exist independently by doing the tasks of human beings. What will happen in the future? No one knows! 

Benefits of Artificial Intelligence 

1. Automation: 

One of the major benefits of AI is automation. It significantly impacts communication, consumer products, transportation, etc. Automation results in higher productivity and reduced lead times. 

2. Enhanced Customer Experience:

AI can help businesses to respond to consumer queries very quickly.

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AI has natural language processing technology generates personalized messages for consumers to find the best solution for their issues. This enhances the consumer experience and results in the growth of the business. 

3. Medical Advances: 

AI solutions are helping the healthcare sector by providing services like clinical diagnosis, patient monitoring, and suggesting treatments without the patient visiting the clinic.

AI also helps in determining the future effects and outcomes of different diseases. 

4. Minimizing Errors: 

AI helps in minimizing errors that humans usually make. The digital systems are becoming more efficient and are less likely to create issues in data processing and other procedures. 

5. Smart Decision-Making: 

AI has been used for making smarter business decisions, unlike humans. AI helps coordinate data delivery, analyze trends, data consistency, etc.

AI should be programmed to imitate humans; otherwise, it will not be able to make better decisions. 

So, this is all information regarding data science and artificial intelligence. Both data science and artificial intelligence are different from one another.


The major difference between data science and AI is that data science is a broad discipline that includes Artificial intelligence. On the other hand, Artificial intelligence is a niche area of data science.

You can choose the top institute in India or abroad that offer comprehensive and well-organized data science courses at affordable prices like KnowledgeHut.

With the help of these courses, you can master the tools and techniques of data science. So, don’t think much and apply for these certification courses today.

Awesome one; I hope this article answers your question.

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