Python Data Analysis
This tutorial will teach you the basics of Python and how to use it for data science. You’ll learn how to work with data sources, data cleaning techniques, how to perform statistical analyses, data visualization, and predictive analysis.
By the end of this course, you'll be able to:
- Basic and intermediate programming concepts
- How to clean and visualize data
- Probability and statistics for data analysis
Learn Python for Data Analysis
Python for Data Analysis: Fundamentals
Learn the basics of Python programming and data analysis.
Pandas & NumPy Fundamentals
Learn how to analyze data using the pandas and NumPy libraries.
Exploratory Data Visualization
Learn how to explore data by creating and interpreting data graphics. This course is taught using matplotlib and pandas.
Data Cleaning and Analysis
Learn how to clean and combine datasets, then practice your skills.
APIs & Web Scraping
Learn how to acquire data from APIs and the web.
Project: Build your own Amazon scraper
Learn to combine the skills you learned to build a scraper which would extract reviews from Amazon.
Statistics: Fundamentals
Learn about sampling, variables and distributions.
Statistics Intermediate: Averages & Variability
Learn to summarize distributions, measure variability using variance or standard deviation, and compare values using z-scores.
Sentiment Analysis: Introduction
Learn to do sentiment analysis using the library vader sentiment.
Project: Download reviews from Amazon and do a sentiment analysis
Learn to combine the skills you learned to do a sentiment analysis on the reviews obtained from Amazon
