Data Sciene & Data Analytics overview
While data analysts and data scientists both work with data, the main difference lies in what they do with it. Data analysts examine large data sets to identify trends, develop charts, and create visual presentations to help businesses make more strategic decisions.
Data visualization techniques
A: The visualization techniques include Pie and Donut Charts, Histogram Plot, Scatter Plot, Kernel Density Estimation for Non-Parametric Data, Box and Whisker Plot for Large Data, Word Clouds and Network Diagrams for Unstructured Data, and Correlation Matrices.
Statistical Analysis and Business Applications
Statistical analysis is the collection and interpretation of data in order to uncover patterns and trends. It is a component of data analytics. ... In the context of business intelligence (BI), statistical analysis involves collecting and scrutinizing every data sample in a set of items from which samples can be drawn.
Mathematical Computing with Python
The Python math module provides functions that are useful in number theory as well as in representation theory, a related field. These functions allow you to calculate a range of important values, including the following: The factorials of a number. The greatest common divisor of two numbers.
Scientific computing with Python
Scientific computing in Python builds upon a small core of packages: Python, a general purpose programming language. It is interpreted and dynamically typed and is very well suited for interactive work and quick prototyping, while being powerful enough to write large applications in.
Data Manipulation with Pandas
Pandas is an open-source python library that is used for data manipulation and analysis. It provides many functions and methods to speed up the data analysis process. Pandas is built on top of the NumPy package, hence it takes a lot of basic inspiration from it.
Machine learning is a branch of artificial intelligence (AI) and computer science which focuses on the use of data and algorithms to imitate the way that humans learn, gradually improving its accuracy. ... Machine learning is an important component of the growing field of data science.
Natural Language Processing
Natural language processing is a subfield of linguistics, computer science, and artificial intelligence concerned with the interactions between computers and human language, in particular how to program computers to process and analyze large amounts of natural language data.