Udemy – Python Step by Step: Build a Data Analysis Program (2015)

 This is a new Udemy course published on August 4, 2015.Are you struggling to create a real-world Python program?Are you interested in using Python for working with any kind of data?You don’t know where to start?Do you need to learn the basics and then jump into a real world program, all in one course? If any of the above identifies with you, then this is the Python course you have been looking for. In this complete course, you will learn how to program with Python starting from the basics and slowly shifting into practical concepts such as handling multiple files and data containing millions of rows and extracting and visualizing information from them.

This course avoids teaching you through trivial traditional examples. Instead, as you progress through the course, you will be guided step by step on building a program that uses real world data containing hundreds of files and millions of records. These data will be downloaded, extracted, cleaned, manipulated, analyzed, aggregated and visualized. And all these operations will be done by the Python program which you will learn to build as the course progresses.

What are the requirements?

• A working computer and internet connection

What am I going to get from this course?

• Over 43 lectures and 4 hours of content!
• Learn how to easily install Python and its libraries.
• Learn the fundamental programming blocks of the language such as variables, datatypes, loops, conditionals and functions.
• Batch download files from FTP sites, extract, rename and store them locally.
• Import data into Python for analysis and visualizations from different sources such as CSV and delimited TXT files.
• Keep the data organized in easily managable data frames.
• Merge large datasets taken from various data file sources.
• Create pivot tables out of large datasets.
• Modify and create new data columns out of existing ones.
• Query data from Python pandas dataframes.
• Export modified datasets into different formats such as text, CSV, and Excel files
• Keep the data organized in easily managable data frames.
• Merge large datasets taken from various data file sources.
• Visualize data by generating various graph image files.
• Create KML Google Earth files out of CSV files.

What is the target audience?

• This course is ideal for those who want to leverage the power of the Python programming language for handling data.
• Ideal for those need to learn the Python basics and want to quickly gain the skills to perform data cleaning, analysis and visualizations with Python.
• Ideal for those need to learn the Python basics and want to quickly gain the skills to perform data cleaning, analysis and visualizations by building a real data analysis program.
• NOT for those who plan to use Python on domains such as game and web development.
• NOT for those who don’t have a basic understanding of programming fundamentals such as variables, strings, integers, functions and loops.
• This course is ideal for those who want to leverage the power of the Python programming language for handling data analysis.

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