Why the need for data scientists?
About a year or two ago and before that, the rate of data generation was low and most of the data is structured so it can be easily analyzed with simple tools like BI. But in today’s world, where the amount of data is not only doubling every two years but is mostly unstructured and semi-structured, companies need complex tools and experts who are data scientists and get the job done.
Who is a data scientist?
A data scientist is a professional who is able to extract hidden information behind data and can use that data to achieve the desired results using a combination of different tools, algorithms, and machine learning principles.
The main part of the work of data scientists is to understand the problem, collect the necessary data, prepare and interpret the collected data, design and analyze it, evaluate the displayed data and finally deliver it to the desired environment. The work begins by discussing the problems a data scientist must face by asking the right questions. Translating, cleaning, and transforming unstructured data is challenging but fun at the same time. Although model development is considered the main activity in the whole process, observation and communication are necessary for the client to understand the data presented.
What does a data science degree include?
Data science is about solving problems using data, so expertise in statistics, programming languages, and economics are important. Therefore, the training focuses on all planning tools in dealing with the programming language Python and machine learning. SQL is used for analytical work, along with SAS, Tableau is considered the best for creating repeatable and readable charts. Ingestion work is done with effective tools like Excel and R, and the Hadoop system is well-represented in extracting large amounts of data. Other tools that make the work of data scientists easier are Minitab, XL Miner, Spark, etc.
This course includes a comprehensive practical study of all concepts of data science by industry experts with many years of professional experience. Many webinars and live projects are designed to get students working in a real business environment. In addition, the cell works together with leading IT companies to support the students in their job search immediately after their training period.
A person trained in data science has many options to choose from. He/she can work in a range of fields such as data analysis, software programming, machine learning engineering, etc. and these options will grow many times over in the future.
Why Consider Data Science as a Career?
It would not be wrong to say that the future depends on data science. There is currently a shortage of skilled workers, and it is estimated that there will be a shortage of over 200,000 skilled workers worldwide by 2021. While IT industries such as e-commerce, social media, communications, robotics, artificial intelligence, etc. need data scientists at their peak, other fat industries such as health sciences, technology, entertainment, aviation, and weapons, etc. also need to be nurtured. Your business uses data. Companies pay high wages for skilled professionals, and with career growth so rapid, there’s no better time to learn science than NOW!
Credit: Schalini M
SIMCEL ONLINE 
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