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May 12, 2021

Skills Required To Become A Data Scientist | Data Science Daily | Episode 25

Skills play a pivotal role when it comes to data science. Most of the recruiters need candidates who have experience in tackling real-life problems regarding data analysis.

 

1.    Multivariable linear algebra and calculus

The vast majority of the data science model, machine learning is designed with different variables. A significant understanding of multivariable calculus is found to be a boon while building a machine learning model. A few topics in maths that will facilitate acquiring data science skills are:

·         Cost function

·         Vector and scalar

·         Tensor and Matrix functions

·         Finding values of a function

·         Stepwise function and Rectified Linear Unit Function

·         Gradients and Derivatives

 

2.    Wrangling of data

Raw data is not prepared for modeling purposes. So the scientists have to prepare the data for more examining i.e., transforming and mapping the data like raw to cooked form. For the purpose of data wrangling, one needs to acquire and combine them from relevant sources, and then cleanse them.

So, coming to the Importance of data wrangling in data science:

·         It enables data scientists to focus more on the analysis activity then the cleansing process

·         This remedy is helpful in revealing good quality data from several sources

·         It shortens extraction time, response time, as well as processing time

·         This results in a solution that is data-driven as well as supported by accurate data or information

3.    Cloud computing

The practice of data science includes cloud computing. Data scientists require the services of computing to process information. The daily tasks of data scientists include data examination and visualization that is found in cloud storage.

Cloud computing and data science work in close tandem because it helps data scientists to avail platforms, like AWS, Google Cloud, and Azure. This is beneficial in giving access to operating tools, Databases, Programming frameworks, and languages.

4.    Basic understanding of Microsoft Excel

Microsoft Excel is now one of the fundamental needs for any job related to the back and front office. It is the primary platform for a defined data algorithm.

Excel proves to be the ideal editor in 2-D data and also allows live communication to a continuing A spreadsheet in Python. Additionally, it makes the manipulation of data relatively simple than any other platform.

So, having a good understanding of MS Excel can be your savior without much effort.

 

5.    DevOps

Half of the population considers that DevOps doesn’t have relevance to data science and a DevOps person can never switch to data science. Well, let me tell you this is a myth because the DevOps board closely works with the developers for controlling the cycle of applications.

DevOps team provides accessible clumps of Apache Hadoop, Apache Spark, Apache Airflow, and Apache Kafka for managing the collection as well as a transformation of data.

 

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