Taking a deep look at the current IT landscape will enable you to get an idea about the increasing significance of data science in today’s economy. Data scientists are crucial parts of a company, and they play a role in the company’s growth. However, starting a career as a data scientist is exciting and challenging. And to pursue a promising career as a successful data scientist, you need to enroll your name in a data science course. In Kolkata, many data science institutes are there. However, when you want to get data science training in Kolkata or any other place, learn it from the best institute, following some steps is suggested. Take a detailed look at them in the upcoming part. Also, know relevant details about this profession.

What are the Key Skills of a Data Scientist?

A successful data scientist is the combination of a trend-spotter, mathematician, and computer scientist. The prime work of these persons is to explain the current trends in the data science sector and to make the best use of them for business growth. Soft skills a data scientist should possess are:

• Ability to take the right decisions 
• The capacity of critical thinking 
• Team management skills
• Communication capacity with both the non-technical and technical audience 
• Clear business sense

Hard skills these persons must possess are:

Proper knowledge of all the data science concepts. Things they should be acquainted with: 

Familiarity with Programming Languages

To be a skilled data scientist, exceptional skills in using programming languages are a must. The most commonly used language in the data science sector is Python. So, learning it is a must. Other languages a data scientist should master are C, C++, SQL, Shell scripting, and so on.

Machine Learning and Deep Learning

Machine learning can be considered the heart of data science. Besides, an understanding of the advanced version of ML known as deep learning is also needed. Deep learning draws inspiration from the human brain and uses them for complex data. Data scientists should come with great knowledge about different algorithms, working on datasets, checking their utility, etc. 

Data Visualization

“Picture says 1000 words” is the ideal saying for data scientists. A data scientist should create effective graphs or charts that can present patterns properly. Different tools like PowerBI, QlikSense, Tableau are there for the proper pattern identification. Open-source python libraries like Matplotlib & Seaborn also can be tried.

Acquaintance with EDA

EDA or Exploratory data analysis is another crucial aspect of the widespread data field. The EDA process focuses on analyzing different data, patterns, and trends and extracting the required data from them. EDA finds out the different patterns that might be missed by the ML algorithms. It includes data manipulation, analysis, or data visualization.

So, if you think of dealing with these people, don’t forget to look for these must-have qualities. Move to any other option if one lacks these features.

Helpful Steps to Learn Data Science Properly 

Before you contact any data science training institute, you should get a notion about the ways to learn it properly. Here is a handy guideline that would come to your help.

Know the Reasons to Learn It

Don’t join a data science course in a hurry only because your friend does the same. Get an idea about its demand first. Here are some stats that will encourage you to learn data science. Keep on reading.

By the end of 2025, more than 75 billion IoT-connected devices will be in Use

As per the survey done by McKinsey, 47% of business owners become able to give a competitive edge to businesses using data science.

According to the BCG-WEF project report, for productivity enhancement, 72% of companies count on data science.

Study report predicts , the market size of the data science platform will reach 322.9 USD billion by 2026.

Focus on Basic Skills Development

As said before, a proper understanding of the programming languages like C, Python , C++ is needed for any data scientist. So, before you join a data science learning course, give time to do basic studies on them. It will make your learning journey smoother.

Improve the Database Management Skills

Data organizing, storing, and retrieving are the prime purposes of a DBMS system. To navigate data from it, you need skills like data manipulation, troubleshooting or encryption. DBMS gives access to organized data that you can analyze or understand.

Know about Data Analysis

Different methods are available for data analysis. Some look at it for assessing past events that correspond with the diagnostic analysis. Others also use data for future prediction and for synchronizing with predictive analysis methods. 

Besides, other data analysis methods are also there that create statistical models to get an idea of the recent events of any organization. You can get these results by using different purposes. Quantitative or qualitative methods can be used. 

Qualitative analysis involves the process of working with non-mathematical data that includes test docs, videos, etc. Different software programs like NVivo and HyperRESEARCH 2.8 are used for this data analysis. 

And quantitative data analysis works with numerical data sets and creates statistical models to find data trends.

Try to Get Familiar with Different Data Science Tools

A range of data science tools is available thinking of the expected results of data analysis. Listed are some notable of them. Get a brief notion about them.

MATLAB– Engineers and scientists use MATLAB, and they prefer it for its capacity for data analysis and visualization. 

D3.js– This data analysis tool is well-known for its user-friendly nature and uses HTML. This javascript library is used for producing engaging and interactive data visualization in several web browsers. It uses HTML 5, cascading style sheet formats, and scalable vector graphics.

Apache Spark- This data processing and analytics engine can handle a huge data amount. And due to this reason, it can process the streaming content in real-time. This open-source and unified analytic engine ensures quick performance in every data stage as well.

Polish Communication Skills

Communication is essential to present findings properly after analyzing the data. When working with qualitative data, an understanding of the data is needed before the analysis of any software tool. However, communication skill means more than conversational skills. It also means different forms of data visualization and event creation as well. 

So, while joining any institute to learn data science, be sure you get the proper guidance for improving this skill. 

And you can get this guidance from a trusted source that offers data science training in Kolkata or elsewhere. And to find a reputable learning source, go through different online review platforms, and also you may take recommendations as well. Don’t hurry while selecting such an institute. And check the reviews and what the earlier students say.