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How should you learn Data Science online?

How should you learn Data Science online?

You might have come across the term Data Science and must be wondering what exactly it is. It does seem interesting but you must be thinking, how would I even start to learn Data Science!

So, these are the questions that will be answered in this blog:

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Introductory Guide to Data Science

We are living in an era of high competition where information is the key to getting our grip on the market. This information is generated by the massive amount of data collected from applications, websites, and many other sources. So, the data generated by these sources can be structured or unstructured. We need to process this massive amount of data. This can be done by designing algorithms and tools that we can use to draw out meaningful insights from the data and then make productive strategies by understanding the patterns so that we can find new market trends, enhance productivity and efficiency to make a good place among competitors. This is where Data Science comes into play. Data Science is the study of data. It involves developing methods of recording, storing, and analyzing data to effectively extract useful information.


It’s not only about business or markets where Data Science is useful but it can also be used in predictive analytics like in weather forecasting. Data collected from satellites and radars can be used for predicting the weather conditions and occurrence of natural calamities. It will help us save many lives by taking appropriate measures before time.

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Another scenario can be like if we type “Learn Data Science” in Google, it suggests more searches related to the keyword “Learn Data Science”. It is possible because Google keeps the record of the past browsing history of their user and makes a cluster of similar keywords. So, if we search for anything, we would get the relevant searches according to that.

Why Data Science?

Data Science forms the base of any type of data processing or interpretation. Having said this, it is also considered to be an enabler of data-driven intelligent business decision-making. Organizations across the globe are leveraging the use of Data Science. Harvard Business Review calls Data Science the sexiest job of the 21st century. Below are some of the reasons why learning Data Science and building a career in the same is important:

  • Career growth- These days, most organizations are analyzing, measuring and tracking, etc. based on data. Most of the companies have reported an increase in profitability and performance level because of Data Science. Hence, more and more organizations are always on the lookout for skilled Data Science professionals. Not only this, data scientists are highly paid, making it a lucrative job for many.
  • Varied branches- Developing skills in Data Science can help you explore opportunities in various branches like Machine Learning, Artificial Intelligence, Data analysis, and many more.
  • Good compensation- Data scientists have some of the best salary packages in their kitty. They are entrusted with critical jobs and responsibilities and are sometimes paid even more than the normal market rate.
  • Less competitive- Due to its highly analytical nature, Data Science attracts lesser competition. Hence, a data scientist can grow far more in this field as compared to others, provided he/she has the necessary skills.
  • Continuous growth- The field of Data Science is new, with constant advancements and discoveries. It is ever-evolving with the development of new skills, giving professionals new things to learn every day for their professional growth.

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Future and scope of learning Data Science

Today, various technologies are growing quickly and an enormous amount of data is being generated on a daily basis. The tremendous growth of Data provides a flash of the future of Data Science. This generation of data is a never-ending process. So, across various industries, there is a need for the implementation of Data Science within their organization. So, there are plenty of opportunities to grow in the field of Data Science, and learning it is a very good option for a bright career.

There are a lot of jobs for Data Scientists in India as well as in other countries, giving vast exposure to the people who want to be Data Scientists. So, the data of the top Indian Job seeking site Naukri.com says that more than 20,000+ jobs are there in India just for Data Scientist. And, in LinkedIn, there were more than 14,000+ jobs for Data Scientists in India itself and that is a huge number.

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In 2018, the estimated job vacancies were 2.9 million for the job role “data scientist”.

This clearly shows the requirement of Data Scientists across the globe.

Data Scientist Salary: The average salary of a Data Scientist in India is Rs 6,50,000/- and an experienced Data Scientist can earn up to $250,000.

How do I start learning data science?

There is going to be a huge demand for Data Scientists in the coming few years. If you are pursuing your career in this field, you need to learn Data Science from proper sources to build the foundation. There are many institutes that provide this course from where you can learn Data Science, but the most preferred way is to learn online.

So, you can enrol for the Masters in Data Science Program by Intellipaat which will help you gain relevant experience in Data Science. You can learn Data Science online with 24*7 support.


So, in this Data Science Architect course, you will start off by learning the top 3 analytical tools used in the industry.

  • So, there’s Data Science with R, where you’ll start off by learning R Programming & learn how to implement statistical analysis and machine learning algorithms with R.
  • Next up is Data Science with Python, where you’ll learn Python Programming and work on multiple Python libraries.
  • Next is Data Science with SAS, where you’ll learn SAS Programming and learn how to implement predictive analytics with SAS.

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So, once you are good with these three tools, you’d have to learn how to store and process Big Data. So, we have the Apache Spark with Scala course, where you’ll learn how to store and process Big Data in real-time.

And to be a complete data scientist, you have to know concepts of Artificial Intelligence as well. So, we have the deep learning with TensorFlow course, where you’ll learn how to implement deep neural networks with the TensorFlow and Keras API.

And finally, when you have the right information with you, your task as a data scientist would be to represent this information in the form of beautiful graphs and reports to the decision-makers. So, for this purpose, we teach you Tableau, where you’ll learn how to create customized dashboards and interactive visualizations at a rapid pace.

So, it’s obvious that the easiest and the best way is to learn Data Science online.

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Resources to learn Data Science Online

Topcoder: We get various Data Science tutorials that cover multiple topics of Data Science.

R-bloggers: Here, various R news and tutorials are contributed by R-bloggers. So, we get to know about the updates and changes in Data Science.

Data Science Weekly: This is a very helpful resource as it provides the latest data science articles, books, training resources, videos, and job postings.

Reddit: This is a community in which people share their research papers and many useful resources.

Kaggle: It consists of a huge repository of community-published data and code. Kaggle has multiple public data sets and notebooks that one can use to learn Data Science.

KDnuggets: It is an online platform for professionals, students, and researchers where millions of posts, blogs, newsletters, courses, etc. are posted by the community.

Flowingdata: It consists of free guides to learning data science and visualizations, public projects, newsletters, blogs, tutorials, etc.

What are some good books to learn Data Science from?

Now, if you still consider books to be a better resource than online classes, you can refer to these:

  1. “The Data Science Handbook: Advice and Insights from 25 Amazing Data Scientists” by Carl Shan, William Chen, Henry Wang, and Max Song
  2. “Doing Data Science: Straight Talk from the Frontline” by Cathy O’Neil and Rachel Schutt
  3. “Numsense! Data Science for the Layman: No Math Added” by Annalyn Ng and Kenneth Soo
  4. “The Art of Data Science” by Roger D. Peng and Elizabeth Matsui
  5. “Data Science For Dummies” by Lillian Pierson
  6. “Big Data For Dummies” by Judith Hurwitz, Alan Nugent, Fern Halper, and Marcia Kaufman
  7. “Data Jujitsu: The Art of Turning Data into Product” by DJ Patil
  8. “Big Data: A Revolution That Will Transform How We Live, Work, and Think” by Viktor Mayer-Schönberger and Kenneth Cukier

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Now, if you belong to the category of people who prefer online resources, then you can go through these:

Do you need certifications in Data Science?

If you only learn Data Science and you are not certified, then it reduces your job opportunity. You need to be certified if you want to pace up in your career.

So, here is the list of certifications that you can go through:

  1. Python for Data Science
  2. R Programming for Data Science
  3. Data Science Certification
  4. Artificial Intelligence Course with TensorFlow
  5. Artificial Intelligence Engineer Master’s Course in Association with IBM
  6. MS in Data Science
  7. Machine Learning Course Online using Python
  8. Data Analytics Training Course
  9. Reinforcement Learning Certification
  10. Probabilistic Graphical Models Certification
  11. Natural Language Processing Using Python Certification
  12. SAS Training

This is all about the path to learn Data Science online. So, dive deep into the sea of Data Science and stay tuned with us.

Frequently Asked Questions (FAQs)

Why do you want to learn data science interview questions?

Learning data science interview questions prepares you for job interviews, showcasing your understanding and ability to apply data science principles in solving real-world problems.

Why is it important to learn data science?

Learning data science is crucial for extracting valuable insights from data, aiding in informed decision-making, and driving innovation in a data-driven economy.

Why do you want to study data?

Studying data enables understanding patterns and trends, which are essential for making informed decisions, optimizing operations, and predicting future outcomes.

Why do you want to study data science and artificial intelligence?

Studying both fields equips you with the skills to extract insights from data and develop intelligent solutions, making you a valuable asset in the modern workforce.

What is interesting about data science?

Data science is fascinating due to its ability to unveil hidden patterns in data, solve complex problems, and contribute to data-driven decision-making in various domains.

What will I learn in data science?

You’ll learn statistical analysis, machine learning, data visualization, predictive analytics, and programming skills necessary for analyzing and interpreting complex data sets.

Why choose data science for Masters?

A Masters in data science provides advanced knowledge, enhances employability in a high-demand field, and opens doors to various industries seeking data-driven decision-making.

Who should study data science?

Individuals with a strong mathematical background, analytical mindset, and a keen interest in discovering insights from data should consider studying data science.

How do I prepare for data science profile?

Acquire foundational knowledge in statistics, mathematics, and programming. Learn tools like Python, R, and SQL. Engage in projects to build a portfolio, and network with professionals. Continuous learning and practice are key.

Why is data science a growing career field?

Data science is growing due to the surge in data generation, the need for data-driven decision-making, and the advancements in machine learning and AI technologies.

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About the Author

Principal Data Scientist

Meet Akash, a Principal Data Scientist who worked as a Supply Chain professional with expertise in demand planning, inventory management, and network optimization. With a master’s degree from IIT Kanpur, his areas of interest include machine learning and operations research.