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Some steps or preparation to become a skilled data scientist ?

 In order to be proficient in any subject, you need a planned and well-thought-out direction, which by following properly you can build yourself proficient in that subject. Similarly, if you want to establish yourself as a wise data scientist, you also have to move forward in a planned way. And the following steps can be part of this plan. By mastering these you can become one of the best data scientists in the world I hopefully.

  •  Skills development in statistics, machine learning and mathematics : A skilled data scientist is one who has better skills in statistics than software engineers and is more proficient in software engineering than statisticians. That means you have to have a balanced knowledge of both. You don't need to be an expert in either one, but you will get an idea of ​​the basics in both. Machine learning is a little more complex and important in data science. It basically deals with data modeling i.e. data formatting, data type discovery and calculation using algorithms. As a result, machine learning has to be mastered with a little time.
  • Learning programming:To become a skilled data scientist there is no substitute for gaining an idea about computer programming. However it is essential to know statistical programming. This requires knowledge of R or SAS or any or more of the Python languages.
  • Gain knowledge about database : The first step in the work of data scientists is to sort the data from the database and then work on it. A large amount of data is stored in the database. You don't need all the data to work on a single topic. All you have to do is work on a subset of the original data with the necessary variables. That's why you need to know the query language. By learning MySQL, Postgres, MongoDB and Cassandra, you can analyze data from the database.
  • Learning to work with big data :Data scientists often have to deal with a lot of big data. There is no definition of how big data can be called big data. However, data that cannot be analyzed with a normal consumer level computer can be called Big Data. To become a data scientist, you need to acquire knowledge about various big data technologies such as Hadoop, MapReduce, Apache Spark, Hive and Pig.
  • Learning the code :Code is a means of publishing data, so it is unthinkable to become a skilled data scientist without learning the language of data and code. It is said that a good coder may not be a skilled data scientist but a good data scientist must be a skilled coder.
  • Data manipulation cleaning and visualization: After querying the data, it has to be sized. This is called data preparation or cleaning. How to clean will depend on what questions are being answered. If these are fixed in advance, less time is wasted in data cleaning. Data cleaning is also called data managing. The two most popular packages for data cleaning are dplyr and data.table.     There are ggviz packages for data visualization. And Tablo is very popular among commercial software. They also have a free version called Community Edition. Tablo is a very popular software that is widely used in the industry. Learning this will make your resume much tougher.
  • Increase communication skills : The difference between the best data scientist and the general data scientist depends on communication skills. The stronger your communication skills, the more you can move forward. You need to be able to establish yourself as a skilled data scientist, not only by analyzing data at home, but also by communicating with different organizations and learning how to deal with any inconsistencies encountered during data analysis. 
  • Exploring knowledge everywhere : A data scientist is introduced to many to carry on his work. Not everyone is proficient in all aspects, if everyone observes the type of work, learns the best techniques, then he will be able to make his debut as a diverse data scientist. So if you want to be proficient, you have to have the humanity to seek knowledge from everything. 
  • Gain practical practice and experience by working on small projects :  You need more than luck to succeed in affiliate business. You need more than luck to succeed in affiliate business. You need more than luck to succeed in affiliate business. For this, you have to do small project work and take advantage of the opportunity to participate in a competition. On the one hand, you will learn data science with pen in hand and will also gain experience, which will put you ahead of others in the workplace.
  • Keep yourself updated and stay connected to the data science community : Need to keep up to date with the data world. Data science is a rapidly changing subject. New things are constantly being added here. So if you want to survive in the market, you have to keep yourself updated. Today's data may become obsolete tomorrow. Now is the age of information technology so you can easily connect with the data science community, and you must stay connected, if you want to prove yourself as a skilled and qualified data scientist.

"I am optimistic that the steps are enough to become a skilled data scientist. If you follow the right path and show love for work, you can become the best data scientist of the age."

 

What else do you need?

And it takes a lot of curiosity. You have to be very curious. You have to have a mind to find the problem and how to solve it using data. Many times a non-technical person can solve a problem much easier than a technical person.

 It requires communication skills. You need to be able to take Insight out of the data and make it easy for ordinary people and CEOs or business leaders to understand.

I have all of them - then?
The world is looking for you. You are a data scientist.

 

  

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