12/18/2015 Learning Python for Data Analysis and Visualization

https://www.udemy.com/learningpythonfordataanalysisandvisualization/ 1/8

Learning Python for Data Analysis and VisualizationLearn python and how to use it to analyze,visualize and present data. Includes tons of sample code and hours of video!

303 ratings, 22530 students enrolled

Instructed by Jose Portilla (https://www.udemy.com/u/view-popup/?userId=9685726)Development (https://www.udemy.com/courses/development/) / Programming Languages(https://www.udemy.com/courses/development/programming-languages/)

 

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Lectures 106

Video 20 Hours

Skill level All level

Languages English

Includes Lifetime access 30 day money back guarantee! Available on iOS and Android Certificate of Completion

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12/18/2015 Learning Python for Data Analysis and Visualization

https://www.udemy.com/learningpythonfordataanalysisandvisualization/ 2/8

What are the requirements?

Basic math skills.Basic to Intermediate Python SkillsHave a computer (either Mac, Windows, or Linux)Desire to learn!

What am I going to get from this course?

Over 106 lectures and 20 hours of content!Have an intermediate skill level of Python programming.Use the Jupyter Notebook Environment.Use the numpy library to create and manipulate arrays.Use the pandas module with Python to create and structure data.Learn how to work with various data formats within python, including: JSON,HTML, and MS Excel Worksheets.Create data visualizations using matplotlib and the seaborn modules with python.Have a portfolio of various data analysis projects.

What is the target audience?

Anyone interested in learning more about python, data science, or data visualizations.Anyone interested about the rapidly expanding world of data science!

Curriculum

Section 1: Intro to Course and Python

Lecture 1 Course Intro Preview (https://www.udemy.com/lecture/view/?lectureId=2338236&paymentPlanId=0) 03:52

Lecture 2 Note on Python. Preview (https://www.udemy.com/lecture/view/?lectureId=3797042&paymentPlanId=0) Text

Section 2: Setup

Lecture 3 Installation Setup and Overview 14:43

Lecture 4 iPython Notebook Overview 05:42

Lecture 5 Course Environment Overview 02:36

Section 3: Learning Numpy

Course Description

NOTE: IF YOU ARE A COMPLETE BEGINNER IN PYTHON-CHECK OUT MY OTHER COURSE "COMPLETE PYTHONBOOTCAMP"!

This course will give you the resources to learn python and effectively use it analyze and visualize data! Startyour career in Data Science!

You'll get a full understanding of how to program with Python and how to use it in conjunction with scientificcomputing modules and libraries to analyze data.

You will also get lifetime access to over 100 example python code notebooks, new and updated videos, as well asFull details (javascipt:void(0))

12/18/2015 Learning Python for Data Analysis and Visualization

https://www.udemy.com/learningpythonfordataanalysisandvisualization/ 3/8

Lecture 6 Intro to numpy Text

Lecture 7 Creating arrays 07:27

Lecture 8 Using arrays and scalars 04:41

Lecture 9 Indexing Arrays 14:19

Lecture 10 Array Transposition 04:07

Lecture 11 Universal Array Function 06:04

Lecture 12 Array Processing 21:48

Lecture 13 Array Input and Output 07:59

Section 4: Intro to Pandas

Lecture 14 Series 13:58

Lecture 15 DataFrames 17:46

Lecture 16 Index objects 04:59

Lecture 17 Reindex 15:54

Lecture 18 Drop Entry 05:41

Lecture 19 Selecting Entries 10:22

Lecture 20 Data Alignment 10:14

Lecture 21 Rank and Sort 05:38

Lecture 22 Summary Statistics 22:35

Lecture 23 Missing Data 11:37

Lecture 24 Index Hierarchy 13:32

Section 5: Working with Data: Part 1

Lecture 25 Reading and Writing Text Files 10:03

Lecture 26 JSON with Python 04:12

Lecture 27 HTML with Python 04:36

Lecture 28 Microsoft Excel files with Python 03:51

Section 6: Working with Data: Part 2

Lecture 29 Merge 20:31

Lecture 30 Merge on Index 12:36

Lecture 31 Concatenate 09:19

Lecture 32 Combining DataFrames 10:20

Lecture 33 Reshaping 07:51

Lecture 34 Pivoting 05:31

Lecture 35 Duplicates in DataFrames 05:54

Lecture 36 Mapping 04:12

Lecture 37 Replace 03:15

Lecture 38 Rename Index 05:55

Lecture 39 Binning 06:16

Lecture 40 Outliers 06:52

Lecture 41 Permutation 05:21

12/18/2015 Learning Python for Data Analysis and Visualization

https://www.udemy.com/learningpythonfordataanalysisandvisualization/ 4/8

Section 7: Working with Data: Part 3

Lecture 42 GroupBy on DataFrames 17:41

Lecture 43 GroupBy on Dict and Series 13:21

Lecture 44 Aggregation Preview (https://www.udemy.com/lecture/view/?lectureId=2346212&paymentPlanId=0) 12:42

Lecture 45 Splitting Applying and Combining 10:02

Lecture 46 Cross Tabulation 05:06

Section 8: Data Visualization

Lecture 47 Installing Seaborn 01:44

Lecture 48 Histograms 09:19

Lecture 49 Kernel Density Estimate Plots 25:58

Lecture 50 Combining Plot Styles 06:14

Lecture 51 Box and Violin Plots 08:52

Lecture 52 Regression Plots 18:39

Lecture 53 Heatmaps and Clustered Matrices 16:49

Section 9: Example Projects.

Lecture 54 Data Projects Preview 03:02

Lecture 55 Intro to Data Projects 04:34

Lecture 56 Titanic Project - Part 1 17:06

Lecture 57 Titanic Project - Part 2 16:08

Lecture 58 Titanic Project - Part 3 15:49

Lecture 59 Titanic Project - Part 4 02:05

Lecture 60 Intro to Data Project - Stock Market Analysis 03:13

Lecture 61 Data Project - Stock Market Analysis Part 1 11:19

Lecture 62 Data Project - Stock Market Analysis Part 2 18:06

Lecture 63 Data Project - Stock Market Analysis Part 3 10:24

Lecture 64 Data Project - Stock Market Analysis Part 4 06:56

Lecture 65 Data Project - Stock Market Analysis Part 5 27:40

Lecture 66 Data Project - Intro to Election Analysis 02:20

Lecture 67 Data Project - Election Analysis Part 1 18:00

Lecture 68 Data Project - Election Analysis Part 2 20:34

Lecture 69 Data Project - Election Analysis Part 3 15:04

Lecture 70 Data Project - Election Analysis Part 4 25:57

Section 10: Machine Learning

Lecture 71 Introduction to Machine Learning with SciKit Learn 12:51

Lecture 72 Linear Regression Part 1 17:40

Lecture 73 Linear Regression Part 2 18:21

Lecture 74 Linear Regression Part 3 18:45

Lecture 75 Linear Regression Part 4 22:08

Lecture 76 Logistic Regression Part 1 14:18

Lecture 77 Logistic Regression Part 2 14:25

12/18/2015 Learning Python for Data Analysis and Visualization

https://www.udemy.com/learningpythonfordataanalysisandvisualization/ 5/8

Lecture 78 Logistic Regression Part 3 12:20

Lecture 79 Logistic Regression Part 4 22:22

Lecture 80 Multi Class Classification Part 1 - Logistic Regression 18:33

Lecture 81 Multi Class Classification Part 2 - k Nearest Neighbor 23:05

Lecture 82 Support Vector Machines Part 1 12:52

Lecture 83 Support Vector Machines - Part 2 29:07

Lecture 84 Naive Bayes Part 1 10:03

Lecture 85 Naive Bayes Part 2 12:26

Lecture 86 Decision Trees and Random Forests 31:47

Section 11: Appendix: Statistics Overview

Lecture 87 Intro to Appendix B 02:44

Lecture 88 Discrete Uniform Distribution 06:11

Lecture 89 Continuous Uniform Distribution 07:03

Lecture 90 Binomial Distribution 12:35

Lecture 91 Poisson Distribution 10:55

Lecture 92 Normal Distribution 06:24

Lecture 93 Sampling Techniques 04:54

Lecture 94 T-Distribution 05:09

Lecture 95 Hypothesis Testing and Confidence Intervals 20:08

Lecture 96 Chi Square Test and Distribution 02:53

Lecture 97 Bayes Theorem 10:02

Section 12: Appendix: SQL and Python

Lecture 98 Introduction to SQL with Python 09:59

Lecture 99 SQL - SELECT,DISTINCT,WHERE,AND & OR 09:58

Lecture 100 SQL WILDCARDS, ORDER BY, GROUP BY and Aggregate Functions 08:25

Full curriculum

Reviews

Instructor Biography

(https://www.udemy.com/user/view-popup/?userId=9685726)

Jose Portilla (https://www.udemy.com/user/view-popup/?userId=9685726) , Data Scientist

(https://linkedin.com/in/jmportilla)Jose Marcial Portilla has a BS and MS in Mechanical Engineering from Santa Clara University and over 3 yearsexperience as a teaching assistant for various engineering classes. He has publications and patents in various fieldssuch as microfluidics and materials science. Over the course of his career he has developed a skill set in analyzing data,specifically using Python and a variety of modules and libraries. He hopes to use his experience in teaching and datascience to help other people learn the power of the Python programming language and its ability to analyze data, asFull biography (javascipt:void(0))

Average Rating

4.8

12/18/2015 Learning Python for Data Analysis and Visualization

https://www.udemy.com/learningpythonfordataanalysisandvisualization/ 6/8

4.8303 ratings

Details5 Stars 268

4 Stars 29

3 Stars 3

2 Stars 1

1 Stars 2

Miguel Batista

1 dayago

·

Great info

Very detailed. Will be great to check even after completion.

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Tim Maytom

1 dayago

·

A few surprises

I'd like to start off by saying that this course has an overwhelming amount of useful information. Unfortunately, thelecturer wasn't as organized or professional as I would have hoped. Most of the lectures were created more as videoreferences than actual lessons which left me feeling a bit disappointed. I was horrified to discover that a couple of thelectures had loud security alerts or other popups on his computer which were very distracting. I would have expectedhim to either edit out those moments or taken some time to re-record those segments of the lecture. Theseshortcomings would have been easily forgiven if this was a free youTube series, but I expected more from a paidcourse.

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Vik M

1 dayago

·

Excellent course

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12/18/2015 Learning Python for Data Analysis and Visualization

https://www.udemy.com/learningpythonfordataanalysisandvisualization/ 7/8

Show more reviews

Carlos Avila

1 dayago

·

Carlos Avila

Excelente Curso!

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Oleg Korsak

2 daysago

·

some parts are outdated, but course is ok

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