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How to become a Data Scientist?

HomeResourcesBlogHow to become a Data Scientist?
July 9, 2019 | Data Science

Data is getting generated in abundance through various sources these days, creating giant data repositories that hold potentially valuable information. The information obtained can be used to grow businesses and transform business processes. Enterprises all across the globe are looking forward to derive insights from data available to them and transform their business models to improve operational processes and ROIs. Data is the most valued asset in the 21st century, ‘Data Scientists’ are the most valued and in demand professionals and ‘Data Science’ is the most trending field.

How to become a Data Scientist?
Data Science is a field that merges statistics, business logic, programming and analytic knowledge to solve complex data-driven problems. Deep knowledge is derived and built upon through data exploration and inference which helps in building strong decision making capabilities.

“Data scientists solve complex data problems by employing deep expertise in some scientific discipline.” – Forbes

Data Scientists are part mathematician and part computer scientist; they have the skill-set that incorporates both the business as well as the information technology sectors. Data scientists extract meaningful information from structured, unstructured, and semi-structured data that flows into the enterprise. They use verbal and visual communication skills to portray their findings to stakeholders who may or may not understand the statistical jargon. Thus, data scientists should also be excellent communicators.

How to become a ‘Data Scientist’?
Becoming a data scientist will require a lot of concept building and learning various skills to work with different tools and programing languages. To establish a career in data science, an individual needs to focus on three main areas –

  1. Mathematics: The job is all about crunching numbers and extracting information hidden in-between the lines. A data scientist’s major task is to mine the data, bring out insights and create models and mathematical expressions that can be used to build logic and algorithms.
    Areas to be focused on are linear algebra, calculus, probability, neural networks, etc.
  2. Technology: This encompasses programming skills and knowledge of using tools specific to data science. Aspiring data scientists need to be fluent in popular programming languages, such as, Python, R, Java, MATLAB, C++, Scala, Julia, etc. and tools like TensorFlow, Apache Spark, NLTK, etc. Being well-versed with concepts of machine learning and deep learning would definitely be an added advantage.

    How to become a Data Scientist?
    Source: LinkedIn

  3. Business knowledge: Data scientists routinely implement logic and algorithms using various programming languages and tools to build insightful reports derived through analysis and predictions. This helps transform the existing business models or build new ones. It is important for a data scientist to know the business domain to be able to derive the most relevant predictions and perform analysis.

Once all skills are acquired, it is time to explore the practical realms of data science:

  • It is recommended to participate in the development of open-source projects
  • Analyze use-cases and projects that are available online
  • Experiment and build pet projects which are domain specific
  • Try to gain as much experience and exposure to varied domains as possible
  • Keep practicing data mining, data cleaning, stocking, etc.
  • Learn new topics and technologies, and never halt the learning process 

Why choose to be a data scientist?

Apart from being deemed as the hottest career of the 21st century by the Harvard Business Review, the ‘Most promising jobs of 2019’ report by LinkedIn ranked ‘data scientists’ at the top, and entitled the role as the most promising job for 2019 in the US. The demand for skilled data scientists is shooting up steeply. The scenario is such that there are fewer proficient data professionals compared to the number of open positions available across the globe. There really couldn’t be a better time to take up a career in data science.

There could be various paths to get a kick-start in this field, but the best 5 magic steps to start off are:
How to become a Data Scientist?
Cognixia offers comprehensive training and certification programs for aspiring data scientists to build a successful career. To explore more about the different trainings Cognixia offers please visit : https://cognixia.com/courses/data-science-with-python-certification-training-course

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