How to learn Data Science? Kickstart Your Career | Happy Learning

As we all know Data Science is one of the topmost trending technologies of the era, it becomes equally important to know how to learn Data Science from scratch to become a professional. There are multiple skills that you need to master to become an expert in Data Science. In this blog, we will look at the learning path for Data Science, where to learn Data Science basics, and try to know how to efficiently learn Data Science from scratch. Also,  we will discuss about the prerequisites to learn Data Science for beginners.

Why should you learn Data Science?

There are multiple questions popping up in your head such as why should you learn Data Science, how to learn Data Science, and many more. Now, let me put it in a simple way. In 2020, data is considered as one of the most essential resources for any business organization. Due to this, Data Science is emerging as the best career option in the IT industry. Today, most of the organizations from small scale to huge enterprises implement Data Science methodologies in their business to enhance profits. Data Science helps them to collect, analyze, and extract meaningful insights from various types of data.

Data Science allows organizations to quickly understand and analyze customer’s requirements to provide them the services they want. This helps organizations to improve businesses by making better decisions. The future of Data Science is very bright as every organization has started applying Data Science techniques. Implementing Data Science techniques in the business require professionals who can extract business insights from large amounts of data. This has led to a high increase in jobs of Data Scientist. Also, the pay scale of a Data Scientist is high in comparison to other job profiles. This is the reason you should learn Data Science to make a bright career as a Data Scientist.

How to learn Data Science efficiently?

Data Science requires knowledge of various fields such Statistics, Calculus, programming languages, database languages, and many more. But for acquiring multiple skills there should be a systematic approach that you should keep in mind. In this section, we will discuss about few of the approaches where you will understand how can you effectively learn Data Science and they are:

1. Learn to choose appropriate data

As we already know Data Science is nothing without data. Thus, it becomes necessary to extract appropriate data for solving a particular problem. If the data is inappropriate, you will find it difficult to implement Data Science techniques in it and end up messing all the things. Therefore, to get the most out of the Data Science field you must learn to choose data properly. For this, you should start with common datasets such as weather prediction, insurance cost prediction, product recommendation, fraud detection, and customer churn. Understand these basic datasets and try to draw meaningful conclusions from them.

2. Learn by implementing

This is the best answer for the question how to learn Data Science. The best way of learning Data Science is by implementing all the techniques in a project. There are multiple techniques such as data extraction, manipulation, visualization, and building models using ML algorithms. Pick up any interesting project of your choice and start working on it. This will help you to strengthen your implementation skills. Start with data cleaning and visualization of data. Then, build predictive models using various Machine Learning algorithms. Also, working on projects will help build a decent portfolio as a Data Scientist.

 3. Constantly increase the degree of difficulty

Working on simple datasets will not make you an expert in Data Science. You need to increase the level of difficulty. There are multiple datasets available that require strong implementation skills and an in-depth understanding of multiple fields. Therefore, working on varieties of complex data will help explore the field of Data Science.

 4. Learn from the Data Science community

You can find a large community for Data Science as it is one of the most popular technologies in the world. There are Data Scientists who shares their knowledge and experience of working in Data Science projects. Also, the aspiring Data Scientist posts wonderful ideas and solutions for Data Science competitions. It will help gain more knowledge of various approaches to get the best solution and find the mistakes that you are doing.

Till now, you must have got a clear idea about how to get started with Data Science. Further, let us have a quick glance at top 10 skills for Data Science aspirants.

Top 10 skills for Data Scientist

An aspiring Data Scientist should have a thorough knowledge of all the tools and techniques that can be used to solve real-world problems.

Here is the list of all the skills that a Data Scientist should have:

  1. R programming
  2. Python
  3. Machine Learning
  4. Artificial Intelligence & Deep Learning with Tensorflow
  5. Big Data Hadoop and Spark
  6. Tableau Desktop 10
  7. Data Science with SAS
  8. Advanced Excel
  9. MongoDB
  10. MS-SQL

Essentials for Data Science Enthusiasts

For becoming a Data Scientist you must follow the below practice suggested by top Data Scientist all around the world:

1. GitHub Profile Building

Creating a GitHub portfolio allows aspiring Data Scientist to store their projects. It helps other people to see the codes and the approach for solving a problem. It shows the level of skills a Data Scientist has and takes you to the limelight of recruiters.

2. Practice via competitions

As you already know, “Practice makes the man perfect.”, thus, becoming a Data Science professional needs a lot of practice. There are a lot of online resources where you can practice and learn Data Science. Also, there are Data Science tutorials where you can start learning.

3. Discussion Forums

Data Science is not new technology and it has a huge community of Data Scientists. Therefore, participating in various discussion forums helps expand knowledge by Data Science experts. Also, by participating in the Data Science community you can clear your doubts on various concepts and get assistance for making projects.


If you are getting started with Data Science, then, here are the major prerequisites to learn Data Science and make a career as a Data Scientist:

  1. You should have a high interest in crunching real-world data.
  2. You must be highly enthusiastic to solve real-world problems using data analytics.
  3. As Data Science requires analysis of every information, you must have a focused mind to understand each and every data point.
  4. The Data Science enthusiasts must have a learning attitude to get a thorough knowledge of the Data Science field.

Otherwise, no one can stop you from learning anything!

Still, if you have a little bit of knowledge of Statistics then it would be an advantage. If not, then there are various Youtube tutorials where you can learn Statistics for Data Science.

Who should get into Data Science field?

Here is the list of individuals who can learn Data Science:

  1. Undergraduate Students
  2. Working Professional
  3. Software Engineer’s looking to upgrade themselves to meet the industry requirements
  4. Data Analysts and Statisticians
  5. Programmers
  6. Professionals looking for a career switch

Finally, in this blog, we have discussed all the important points that you must remember while starting your Data Science journey.
Stay tuned with Bridle Academy to learn more about new technologies!

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