To study Data Science as a beginner you need to get hold of the basic important languages. Here’s a listing of tools that every data analyst should acknowledge-
1. Statistics: Statistics is the method of analyzing historical data, like customer search history.
- Descriptive Statistics: It helps to understand the data. By quantitative summarization of your data through numerical representations and graphs, data can be properly described. It includes Normal Distribution, Central Tendency, Kurtosis, and Variability.
- Inferential Statistics: Data is not of any use if you can't draw a conclusion out of it. Making inferences about the population through a smaller sample can be done through this. The methods it includes are Central Limit Theorem, hypothesis testing, ANOVA and Quantitative Data Analysis.
2. Mathematics for Machine Learning: Machine Learning theory is a field that intersects Linear Algebra and Calculus. With the right procedure through the practical implementation of maths, it can be quite fun!
3. Programming Knowledge: Last but not least is the programming. These are the essential ingredients for Data science.
- Python: Python is an interpreter based language as it interprets the Python code line by line.
- R: R is customized to generate statistical models for analyzing a large amount of data.
- SQL: SQL helps to retrieve and manipulate data from the database.
If you want to know more about Data Science then do check out our data scientist which will help you in learning Data Science from scratch:
And if you are more into videos then you can check out this video tutorial which will help you in learning Data Science from the beginning:
And if you are beginner and more into reading blogs then you can check out this blog which will provide you a brief introduction to Data Science.
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