Python Step by Step: Build a Data Analysis Program by Udemy

Python Step by Step: Build a Data Analysis Program Udemy

(Not Rated)

About Course

If you don't know how to start learning Python and you want to learn and master the language by building real world programs, then this is the Python course you have been looking for.

Review by Jess Nault: "Course is learning by doing from an interesting and concise instructor. He's not verbose, he doesn't bore you with extraneous/unnecessary detail, or useless slides. Well organized, sequential, bite-sized presentations that build on previous learning. While this is not all inclusive python language tutorial, the syllabus is accurate, and the learning gives you enough to feel confident to take on more. Students: don't reward crappy teaching (monitone slide show, outdated material/technology, verbose explanations, sometimes little to no demonstrating...)!! Instead, reward teachers like this one. He puts you in the driver's seat and teaches you to drive. So to speak. I don't often give a 5 star rating, so this guy is highly recommended."

In this complete course, you will learn Python starting from the basics and slowly shifting to more practical concepts such as handling files and data that contain millions of records, and extracting and visualizing crucial information from them.

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. You will also make you own scripts by applying your skills on some US census income data. Quite a lot of fun!

More specifically, you will learn to use various Python libraries such as ftplib, os, glob, pandas, numpy, patoolib, matplotlib, seaborn and simplekml.

What are the requirements?

A working computer and internet connection

What am I going to get from this course?

Those who come from any technology field that deals with any kind of data.
Those who want to leverage the power of the Python programming language for handling data.
Ideal for those who need to learn the Python basics and want to quickly advance their skills by learning how to perform data cleaning, analysis and visualizations with Python - all in one single course.
Those who want to switch from languages such as R, Matlab, etc. to the freedom of coding with Python.
NOT for those who plan to use Python on domains such as game and web development.

What is the target audience?

Those who come from any technology field that deals with any kind of data.
Those who want to leverage the power of the Python programming language for handling data.
Ideal for those who need to learn the Python basics and want to quickly advance their skills by learning how to perform data cleaning, analysis and visualizations with Python - all in one single course.
Those who want to switch from languages such as R, Matlab, etc. to the freedom of coding with Python.
NOT for those who plan to use Python on domains such as game and web development.

About Instructor

https://www.udemy.com/user/adiune/

Curriculum

Section 1

Lecture 1

Course Introduction

Lecture 2

A few words about Python

Lecture 3

Installing Python and Python libraries

Lecture 4

Python editors - Spyder and iPython

Quiz

Section quiz

Section 2

Lecture 5

Variables

Lecture 6

Strings and numbers

Quiz

Variables, strings, and numbers.

Lecture 7

If, else, and indentation

Lecture 8

Functions

Lecture 9

Storing a function for later use

Quiz

Conditionals and functions

Lecture 10

Sequences

Lecture 11

Collections

Lecture 12

Working with sequences and strings

Lecture 13

Iterating

Quiz

Sequenes, collections, strings and iterations

Section 3

Lecture 14

Working with files

Lecture 15

Handling files easily

Lecture 16

Exercise

Lecture 17

Exercise solution

Lecture 18

Working with folders

Lecture 19

Manipulating directory paths

Lecture 20

Iterating through files

Section 4

Lecture 21

Section intro

Lecture 22

Browsing FTP files

Lecture 23

Storing Python code

Lecture 24

Creating an FTP function

Lecture 25

Downloading an FTP file

Lecture 26

Practical No.1: Creating a FTP File Downloader

Section 5

Lecture 27

Extracting ZIP, TAR, GZ and other archive file formats

Lecture 28

Extracting RAR files

Lecture 29

Practical No.2: Creating a batch archive extractor

Section 6

Lecture 30

Section intro

Lecture 31

Reading delimited TXT and CSV files

Lecture 32

Exporting data back to files

Lecture 33

Reading fixed width TXT files

Lecture 34

Exporting data back to HTML and other fIle formats

Lecture 35

Data Analysis Exercise: 1 of 6

Lecture 36

Solution: 1 of 6

Section 7

Lecture 37

Introducing pandas - the great Python data analysis library

Lecture 38

Practical No.3: Calculating and adding columns to CSV files

Lecture 39

Data Analysis Exercise: 2 of 6

Lecture 40

Solution: 2 of 6

Section 8

Lecture 41

Practical No.4: Concatenating multiple CSV files

Lecture 42

Data Analysis Exercise: 3 of 6

Lecture 43

Solution: 3 of 6

Lecture 44

Practical No. 5: Joining data based on a matching column

Lecture 45

Data Analysis Exercise: 4 of 6

Lecture 46

Solution: 4 of 6

Lecture 47

Data Analysis Exercise: 5 of 6

Lecture 48

Solution: 5 of 6

Section 9

Lecture 49

Practical No. 6: Pivoting large amounts of data

Section 10

Lecture 50

How to perform visualizations in Python

Lecture 51

More visualization techniques

Lecture 52

Practical No. 7: Generating an image file graph

Lecture 53

Data Analysis Exercise: 6 of 6

Lecture 54

Solution: 6 of 6

Section 11

Lecture 55

Creating KML Google Earth files

Lecture 56

Practical No, 8: Creating KML Google Earth fIles from CSV

Section 12

Lecture 57

User interaction

Lecture 58

Exercise: User interaction

Lecture 59

Solution: User interaction

Lecture 60

Practical No. 9: Polishing the program, I

Lecture 61

Practical No. 10: Polishing the program, II

Lecture 62

Practical No. 11: Creating a Python module out of your program

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Python Step by Step: Build a Data Analysis Program Udemy

About Course

What are the requirements?

What am I going to get from this course?

What is the target audience?

About Instructor

Curriculum

Section 1

Section 2

Section 3

Section 4

Section 5

Section 6

Section 7

Section 8

Section 9

Section 10

Section 11

Section 12

About Provider