In 2018, Python held 65.6% of the data science market, Python in the last decade has grown from strength to strength. You will 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!
Python in Data science
Will use python 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
Will learn to use Pandas DataFrames, Numpy multidimensional arrays, and SciPy libraries to work with various datasets.
introduce you to pandas, an open-source library, and we will use it to load, manipulate, analyze, and visualize cool datasets.
Python for Data Analysis
We will use some of machine learning algorithms to build smart models and make cool predictions.
We will see how to Import Datasets
Understanding the Domain,
Understanding the Dataset , Python package for data science ,Importing and Exporting Data in Python
Cleaning and Preparing the Data ,Identify and Handle Missing Values
Data Formatting , Data Normalization Sets , Model Development, Simple and Multiple Linear Regression , Model Evaluation Using Visualization
Python for Visualization
Learning how to leverage a software tool to visualize data will also enable you to extract information
Understand the data, and make more effective decisions.