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The World’s Economic Forum’s Future of Work Report 2020 predicts that by 2025, one of the hottest jobs with the highest demand will be in the field of Data Science.

The spread of the internet has already increased to a huge level {Click here to learn more about the working of Internet} and continuing to rise. This increases the number of Internet Users, which leads to a huge collection of Data. Now, the question arises that:

What we can do with this Data?

How this Data can be made beneficial for the company’s goal?

What Insights can be drawn from it?

How to work and implement strategies based on those insights?

And so on……..


1. What is Data Science?

2. What is the significance of Data Science?

3. What does a Data Scientist do?

4. What are the required skills in a Data Scientist?

5. What are the various roles offered in the field of Data Science?

What is Data Science?

Data Science is the study of Data, i.e. conversion of given Data into Meaningful Insights. It involves developing methods of recording, storing, and analyzing data. In this field of study, one learns to convert given data into meaningful insights, along with strategies and ideas to work over it. Its study makes you able to gain insights from any kind of data, whether structured or unstructured. One who studies and applies this knowledge in the real world is known as Data Scientist.

“Data Scientist is a person who is better at statistics than any Software Engineer and better at Software Engineering than any statistician.”


Now, we will learn more about it in an upside-down way, i.e. first find out why we are learning it and its application, and then we will see how to do it.

What is the significance of Data Science?

Data Science plays a major role in today’s world with its great contribution in various fields –

● Prediction of Disease Outcome, when provided with the medical history of a patient.

● Protection from traps and false reports, claims, etc.

● Assures Security through Fraud Detection.

● Save time by suggesting the best route to travel, whether by roadways or by airways. Also enhances our traveling experience.

● Widely used in Automation of Self-drives Car.

● Help out the retailers to study the purchasing manners of consumer and their preferences while placing orders. This helps them to grow and improve their business.

What does a Data Scientist do?

  1. Define the problem:

Firstly, know what the problem is, what the goal is and what are the obstacles blocking you to achieve it.

2. Obtain Accurate Data:

Get the data required to solve the issues. Collecting data covers 19% of the total time spent on the entire project.

3. Data Preparation:

It involves cleaning and filtering the data. And its conversion from one format to another, such as missing numbers, incorrect values, etc. In this step, data is cons sized to one standard format, ready to analyze. It takes about 60% of the total time.

4. Data Analysis:

It includes studying trends over a while. Also involves consideration of different data types and drawing pattern based on the study.

5. Data Modeling:

Data Modeling is to create the most efficient method of storing information and producing it in an explanatory & simple way. It also includes training the models on the Training Dataset & testing them to select the best out of them.

6. Data Visualization:

Representation of Data information with the help of data visualization tools such as charts, graphs, maps, etc. This makes it easy for others to understand and suggest modifications.

7. Deploy and Maintenance of Data:

It includes testing the data in a pre-production area before its departure to the production area. After a period of deployment, the reports are studied and monitored to maintain project performance.

What are the required skills in a Data Scientist?

To make a career in Data Science, we must learn the following things:

(Hard Skills)

1. Mathematics and Statistics:

Look after basic statistics from books like “Hines”. Learn about topics like probability, calculus, statistics, linear algebra, statistics, etc. for the mathematics section.

2. Programming:

Learn Python basics, and OOP’s concepts {Click here to learn more about OOP’s.} Take a glance over libraries such as Numpy, Pandas, Matplotlib, etc. For this, you can take the help of various amazing YouTube channels such as Code with Harry, Simplilearn, Great learning, Krish Naik, Code for cause, and Apna College. (Personal suggestions)

3. Data Visualization tools:

This makes you familiar with Handling Data. One can start with using Excel for handling small data. Whereas for handling Big Data useful tools are Tableau, Hadoop, AWS offerings, etc.

4. Machine Learning and Deep Learning:

Here, we can learn how to build a neural network in TensorFlow and use tensorflow_hub & TensorBoard. Various Courses might help you such as Free Courses by Google, Kaggle, Coursera, etc.

5. Linux & Version Control:

Learn the working and Functioning on Linux and Git Version Control. {Click here to more about Version Control}

(Soft Skills)

1. Interpretation Skills: Here, it is converting the data we gathered by seeing, hearing, and understanding into representative form by the method of Modeling. This means to be effective for the non-tech audience, it is also known as Data storytelling.

2. Communication Skills

3. Curiosity to ask different questions and find the answer to unknown questions.

4. Critical Thinking

5. Creativity

Thank you for reading this blog.


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