Data Analysis with Python Essential Training

SkillsFuture Course - Data Analysis with Python Essential Training 

The world generates data at an increasing pace. Consumers, sensors, or scientific experiments emit data points every day. In finance, business, administration and the natural or social sciences, working with data can make up a significant part of the job. Being able to efficiently work with small or large datasets has become a valuable skill.

Working with bigger datasets is getting simpler and sharing research findings and creating interactive programming notebooks has never been easier. It is the perfect moment to learn about data analysis in Python. This course will let you get started with a few core libraries of the PyData ecosystem: Numpy, Pandas, and matplotlib.

Module 1 Python Data Analysis Libraries

• Data Analysis Components
• Data Analysis Steps
• Python Data Analysis Libraries

Module 2 Overview of Numpy

• What is Numpy?
• 1D and 2D Array
• Array Arithmetics
• Special Functions
• Math Functions
• Selecting and Slicing Array Elements
• Filtering Array Elements
• Transforming Array
• Statistics

Module 3 Data Analysis with Pandas

• Series
• Data Frame
• Selecting/Slicing Data
• Import/Export Data - CSV, Excel, Internet
• Filtering Data
• Missing Data
• Removing Duplicated Data
• Joining Data from Different Sources
• Transforming Data
• Aggregating Data
• Pandas Statistics

Module 4 Data Visualization with Matplotlib & Seaborn

• Overview of Matplotlib & Seaborn
• Plot Types
• Plot Attributes
• Object Oriented Plots
• Time Series Plot

Module 5 Intro to Machine Learning with Scikit-Learn

• Overview of Scikit-Learn
• Supervised and Unsupervised Learning
• Classification
• Regression
• Clustering 
• PCA