Technical Skills Required for Transition into Data Science
There are a lot of skills which are required by people to become a data scientist but some of the Major technical skills that are required by people to switch their career from non CS to Data Science are as follows:
- Programming: Python is an essential in the field of Data Science and it simply is used majority of times due to its number of libraries like NumPy, pandas, Scikit-learn, and TensorFlow, this language allows data manipulation very easily. People who don’t like python language can also prefer R language. People should learn how to efficiently handle the datasets that are further analyzed in Data Science. Also, people must learn about the transformation of Data, handling of missing values, and inconsistency, and many more.
- Maths and Statistics: One should be having a great statistical foundation with concepts that include Probability , regression analysis , time series analysis and hypothesis testing and some of the other mathematical concepts that are important for people are Calculus, Linear Algebra, etc.
- Machine Learning: Understanding algorithms based on machine learning is a must do thing in data science and some of the examples of these can be linear regression, decision trees, k-nearest neighbors, and support vector machines.
- Some libraries: There are a lot of libraries provided by python and apart from Numpy, Pandas, people must also have knowledge about applications like Tableau and PowerBI which also come into picture in today’s data science field.
- Frameworks or other skills: A data scientist should possess skills in designing, training, and fine-tuning neural networks for various use cases, as well as knowledge of different neural network architectures and frameworks.
- Learning DevOps: Devops is a technique of developing software that places a strong impact on teamwork and communication between the development and growth teams and it is an important part of the roadmap for becoming a Data Scientist.
- Understanding Tools: Analytical tools are one of the most helpful data scientist skills for extracting valuable information from an organized data set like SASHive, Pig, R etc are the most popular data analytical tools that data scientists use and learning these skills help in Data Analysis.
How to become data scienctist if you are non cs student?
A data scientist is a person who does research part on projects to be able to process big data using the tools of technology, mathematics, business, and communications. Companies use this information in better decision-making, solving complex questions, and growing better. They are responsible for collecting, analyzing, and interpreting large and complex data sets to identify patterns, trends, and relationships that can help organizations make informed decisions.
Through this blog, let us discuss various questions that people ask about a data scientist like how to become a data scientist or how to become a data scientist if people are non-CS students.