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Data Science Tutorial

Introduction to Data Science

In this Data Science tutorial, you will learn Data Science from the basics. Data Science is a multidisciplinary domain that includes working with huge amounts of data, developing algorithms, working with machine learning and more to come up with business insights. You will work with huge amounts of data. You will clean the data, prepare it, convert it into a format through which you can derive valuable insights from it.

Recommended audience

You need an inquisitive mind, ability to work with huge amounts of data, ask the right questions, and arrive at a solution through the application of various tools, technologies and skills.

Prerequisites

Anybody can learn data science since there are no prerequisites for learning this domain.

Why is Data Science so widely used?

In this Data Science tutorial, you will also learn about the importance of Data Science in today’s digitally-driven world. Due to the incessant amount of data that we are creating, there is an urgent need to derive valuable insights from this data. Data is the oil of our generation. With the right tools, technologies, algorithms we can make sense of data and convert it into a distinctive business advantage.

Learn Data Science in 28 hrs from experts

Check this table to find out the highlights of data science:

Criteria How data science accomplishes it
Making sense of data Through use of various tools, techniques, algorithms
How it is connected to AI Machine learning techniques are used widely here
Type of domain Is both an art and a science
Business importance Is extremely important in a data-driven world

Type of Data Science jobs

In this Data Science tutorial, you will not only learn Data Science but will also find out about the various roles in the domain of Data Science which are listed as below.

Data analyst

A data analyst is entrusted with the responsibility of mining huge amounts of data, look for patterns, relationships, trends and so and come up with compelling visualization and reporting for analyzing the data to take business decisions.

Data engineer

The data engineer is entrusted with the responsibility of working with large amounts of data. He should be available to clear data cleansing, data extraction and data preparation for data business for working with large amounts of data.

Machine learning expert

The machine learning expert is the one who is working with the various machine learning algorithms like regression, clustering, classification, decision tree, random forest and so on.

Data scientist

A data scientist is the one who works with huge amounts of data to come up with compelling business insights through the deployment of various tools, techniques, methodologies, algorithms, and so on.

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Applications of data science

Some of the major applications of data science are as below:

  • Internet search
  • Personalized recommender systems
  • Image recognition
  • Fraud detection
  • Optimization techniques
  • Stock market analysis
  • Pathological diagnosis

Qualities of a Data Scientist

If you want to learn Data Science you should also be aware of the various strengths of a Data Scientist. In this Data Science tutorial you will also see that there are a lot of skills that you need to master in order to become a successful data scientist. Some of the skills that an accomplished data scientist will possess include, technical acumen, statistical thinking, analytical bent of mind, curiosity, problem-solving approach, big data analytical skills and so on.

How to learn Data Science to be an expert?

If you want to be an expert data scientist, then you need to practice the following things:

  • Familiarize yourself about real world data science problems

Like one famous person once said that the whole world is one big data problem. So as a data scientist it is your job to learn more and more about the various data science problems in the real world. This way you will have an inside understanding of this domain.

  • Participate in data science forums and competitions

There are a lot of competitions and forums that are regularly hosting data science contests and competitions for data scientists. You would do well not only learn Data Science but also participate in these highly exciting contests. That way the knowledge that you get from this Data Science tutorial can be built up and put to practical use also.

  • Regularly work on huge data sets

There is a huge amount of data that is available on the internet. It could be real data or just practice data set. But whatever the nature of the data, it will be very well to work on these data sets to implement your knowledge of data science and get hands-on practice in the domain of data science.

  • Have a collaborative and interactive approach

Since data science is a very vast field, in the initial days it could be very good to have a collaborative approach to learn data science. That way you will learn in an interactive and collaborative way and will be on your way to becoming an accomplished data scientist.

  • Practice every day and gain a definitive edge

In this data science tutorial, you will learn data science to help you get started, but that would not be enough. If you want to build your skills and hone it to perfection, then you need to practice every day since as we all know that practice makes a man prefect. And to learn data science it is not much different, you need to practice a lot to achieve perfection.

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Comparison of Data Science with Data Analytics

Criteria Data Science Data Analytics
Various skills required Data capturing, statistics, mathematics, problem-solving Analytical, mathematical, statistical
Need to be experts in Data mining Data visualization
Type of data used All types of data Structured & mostly numeric data
Standard lifecycle Explore, discover, investigate & visualize Report, predict, prescribe & optimize

A lot of people confuse the role of a data scientist with the role of a data analyst. There are a lot of similarities but there are a lot of difference as well. So the above table gives you a high-level understanding of what are the major difference between a data scientist and a data analyst. One more key difference between the two domains is that data analysis is a necessary skill for data science. Thus data science can be thought of a big set while data analysis can be thought of as a subset of it. In this data science tutorial you will learn top tools, technologies, skills needed to be a successful data scientist. So this is your preliminary step to learn data science and become an accomplished data scientist.

Download Interview Questions asked by top MNCs in 2018?

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"8 Responses on Data Science Tutorial"

  1. Rekha says:

    According to me Data Science is the practice of formulating hypothesis, Defining the data & Identifying the type of analysis, Am I right?

  2. Rajeev says:

    I want to learn data science ..Can you please tell me what is the prerequisites for learning Data Science?

  3. Rakesh says:

    I heard that in data science there is no codeing, is it true ? Because I am a non programming background.

  4. monika says:

    I want to learn about data science in simplest manner. Can you help me how should I go with it?

  5. Om says:

    In-depth, comprehensible and coherent! Each topic is explained in a straightforward manner through appropriate examples. Great Job!!!

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