Different roles under data science field and skill sets required for each of them

Career Coaching
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“Data science is an interdisciplinary field that uses scientific methods, processes, Machine learning algorithms and systems to extract knowledge and insights from data in various forms, both structured and unstructured data”

Three segments of DS and the Skills needed

  1. Data Engineering :

•Database and bigdata Infra knowledge (GCP, AWS,Azure)

•Scripting language like python,shell

•SQL and ETL tools

  1. Analytics

•SQL

•R/Python

•Statistics

•Business knowledge

•Excel

•Presentation skill using visualization tools like PowerBI , Tableau and etc

  1. ML/AI

•SQL

•ML algorithms

•Strong knowledge of statistics and mathematics

•Model deployment

•R /Python

•Business knowledge

Hope this will clear the most common doubt of all the aspirants.
Please feel free to ask any questions.

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Step wise guide to get into Analytics/Data Science role | Step 1
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One should know how to set up the data infrastructure, how to provide data analysis and creating data visualisations.

Understanding of data wrangling or data munging and the related tools.

One should have a basic understanding of SQL or MySQL, Hive or Pig, R or Python programming languages, linear algebra, calculus and probability), hypothesis testing and summary statistics.

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To be a successful data science expert, it is essential to have an understanding of specific programming languages such as R and/or Python. Other popular languages to master include MATLAB, SQL, Java, etc.

Fingertips data science masters course you will get in depth knowledge on how data scientists work with a wide range of complex data samples, including structured and unstructured datasets, and they use their data wrangling, programming, and other talents to clean, sort, and manage data. To engage with big data, one must prepare, distribute, or process data using Hadoop or Spark. Most data scientists prefer Spark because it provides quick real-time data processing. Regardless of which big data tool one uses, they must learn and practice data exploration, data filtering, data sampling, data summarization, and so on.

As a , one needs to work on data visualization to represent data in pictorial forms of charts and graphs that are easy to understand. Popular tools for data visualization include Power BI and Tableau. Machine Learning with Artificial Intelligence & Deep Learning enables data scientists to handle complex data for predicting insights. To be a skilled professional, one must have these skills and use machine learning and AI principles to work on diverse algorithms and data-driven models while handling enormous datasets.

It is crucial to have strong communication skills to be successful in one’s work and for the business to profit from their services. Data scientists must be able to effectively communicate with their team members and other individuals in the organization. One must also have problem-solving skills to discover and generate unique and effective solutions when necessary. Working with a team is also essential to become an excellent data scientist and use one’s data science learnings to increase the speed of output to assure the organization’s long-term growth.