Udemy - Data Analysis Bootcamp - Python, Seaborn and Pandas

Learn hundreds of methods and attributes across numerous pandas objects
Resolve common issues in broken or incomplete data sets
Description
Are you interested to learn how zetabytes of data are processed by top tech companies to analyze data in order to boost their business growth? Well, for a beginner you are at the right place and this is most probably the right time for you to learn this.
The average data scientist today earns $123,000 a year, according to Indeed research. But the operating term here is "today," since data science has paid increasing dividends since it really burst into business consciousness in recent years.
Learn how to analyze data using Python. This course will take you from the basics of Python to exploring many different types of data. You will learn how to prepare data for analysis, perform simple statistical analyses, create meaningful data visualizations, predict future trends from data, and more!
You will learn how to:
Import data sets
Clean and prepare data for analysis
Manipulate pandas DataFrame
Summarize data
Build machine learning models using scikit-learn
Build data pipelines
Data Analysis with Python is delivered through lectures, hands-on labs, and assignments. It includes the following parts:
Data Analysis libraries: will learn to use Pandas DataFrames, Numpy multi-dimensional arrays, and SciPy libraries to work with various datasets. We will introduce you to pandas, an open-source library, and we will use it to load, manipulate, analyze, and visualize cool datasets. Then we will introduce you to another open-source library, scikit-learn, and we will use some of its machine learning algorithms to build smart models and make cool predictions.
Who this course is for:
Data analysts and business analysts
Anyone who wants to learn Data Analysis
Excel users looking to learn a more powerful software for data analysis
Beginner Data Analyst

Homepage

https://www.udemy.com/course/data-analysis-bootcamp-python-seaborn-and-pandas/