Section 1 : Intro to Course and Python
Lecture 1 Course Intro 00:03:52 Duration
Lecture 2 INTRODUCTION TO BRAINMEASURES PROCTOR SYSTEM

Section 2 : Setup
Lecture 1 Installation Setup and Overview 00:07:17 Duration
Lecture 2 IDEs and Course Resources 00:10:56 Duration
Lecture 3 iPythonJupyter Notebook Overview 00:14:57 Duration

Section 3 : Learning Numpy
Lecture 1 Intro to numpy
Lecture 2 Creating arrays 00:07:27 Duration
Lecture 3 Using arrays and scalars 00:04:42 Duration
Lecture 4 Indexing Arrays
Lecture 5 Array Transposition 00:04:07 Duration
Lecture 6 Universal Array Function 00:06:05 Duration
Lecture 7 Array Processing 00:21:48 Duration
Lecture 8 Array Input and Output

Section 4 : Intro to Pandas
Lecture 1 Series 00:13:56 Duration
Lecture 2 DataFrames 00:17:46 Duration
Lecture 3 Index objects 00:04:59 Duration
Lecture 4 Reindex 00:15:52 Duration
Lecture 5 Drop Entry 00:05:42 Duration
Lecture 6 Selecting Entries 00:10:23 Duration
Lecture 7 Data Alignment 00:10:14 Duration
Lecture 8 Rank and Sort 00:05:37 Duration
Lecture 9 Summary Statistics 00:22:35 Duration
Lecture 10 Missing Data 00:11:38 Duration
Lecture 11 Index Hierarchy 00:13:29 Duration

Section 5 : Working with Data Part 1
Lecture 1 Reading and Writing Text Files 00:10:02 Duration
Lecture 2 JSON with Python 00:04:11 Duration
Lecture 3 HTML with Python 00:04:35 Duration
Lecture 4 Microsoft Excel files with Python 00:03:52 Duration

Section 6 : Working with Data Part 2
Lecture 1 Merge 00:20:31 Duration
Lecture 2 Merge on Index 00:12:36 Duration
Lecture 3 Concatenate 00:09:19 Duration
Lecture 4 Combining DataFrames 00:10:18 Duration
Lecture 5 Reshaping 00:07:51 Duration
Lecture 6 Pivoting 00:05:31 Duration
Lecture 7 Duplicates in DataFrames 00:05:54 Duration
Lecture 8 Mapping 00:04:12 Duration
Lecture 9 Replace 00:03:16 Duration
Lecture 10 Rename Index 00:05:53 Duration
Lecture 11 Binning 00:06:16 Duration
Lecture 12 Outliers 00:06:52 Duration
Lecture 13 Permutation 00:05:22 Duration

Section 7 : Working with Data Part 3
Lecture 1 GroupBy on DataFrames 00:17:42 Duration
Lecture 2 GroupBy on Dict and Series 00:13:21 Duration
Lecture 3 Aggregation 00:12:41 Duration
Lecture 4 Splitting Applying and Combining 00:10:02 Duration
Lecture 5 Cross Tabulation 00:05:06 Duration

Section 8 : Data Visualization
Lecture 1 Installing Seaborn 00:01:44 Duration
Lecture 2 Histograms 00:09:19 Duration
Lecture 3 Kernel Density Estimate Plots 00:25:58 Duration
Lecture 4 Combining Plot Styles 00:06:14 Duration
Lecture 5 Box and Violin Plots 00:08:51 Duration
Lecture 6 Regression Plots 00:18:39 Duration
Lecture 7 Heatmaps and Clustered Matrices 00:16:46 Duration

Section 9 : Example Projects
Lecture 1 Data Projects Preview 00:03:02 Duration
Lecture 2 Intro to Data Projects 00:04:33 Duration
Lecture 3 Titanic Project - Part 1 00:17:07 Duration
Lecture 4 Titanic Project - Part 2 00:16:07 Duration
Lecture 5 Titanic Project - Part 3 00:15:47 Duration
Lecture 6 Titanic Project - Part 4 00:02:01 Duration
Lecture 7 Intro to Data Project - Stock Market Analysis 00:03:09 Duration
Lecture 8 Data Project - Stock Market Analysis Part 1 00:11:20 Duration
Lecture 9 Data Project - Stock Market Analysis Part 2 00:18:06 Duration
Lecture 10 Data Project - Stock Market Analysis Part 3 00:10:24 Duration
Lecture 11 Data Project - Stock Market Analysis Part 4 00:06:57 Duration
Lecture 12 Data Project - Stock Market Analysis Part 5 00:27:40 Duration
Lecture 13 Data Project - Intro to Election Analysis 00:02:21 Duration
Lecture 14 Data Project - Election Analysis Part 1 00:18:00 Duration
Lecture 15 Data Project - Election Analysis Part 2 00:20:34 Duration
Lecture 16 Data Project - Election Analysis Part 3 00:15:05 Duration
Lecture 17 Data Project - Election Analysis Part 4 00:25:57 Duration

Section 10 : Machine Learning
Lecture 1 Introduction to Machine Learning with SciKit Learn 00:12:51 Duration
Lecture 2 Linear Regression Part 1 00:17:40 Duration
Lecture 3 Linear Regression Part 2
Lecture 4 Linear Regression Part 3 00:18:45 Duration
Lecture 5 Linear Regression Part 4 00:22:08 Duration
Lecture 6 Logistic Regression Part 1 00:14:19 Duration
Lecture 7 Logistic Regression Part 2 00:14:26 Duration
Lecture 8 Logistic Regression Part 3 00:12:20 Duration
Lecture 9 Logistic Regression Part 4 00:22:22 Duration
Lecture 10 Multi Class Classification Part 1 - Logistic Regression 00:18:33 Duration
Lecture 11 Multi Class Classification Part 2 - k Nearest Neighbor 00:23:05 Duration
Lecture 12 Support Vector Machines Part 1 00:12:53 Duration
Lecture 13 Support Vector Machines - Part 2 00:29:07 Duration
Lecture 14 Naive Bayes Part 1 00:10:04 Duration
Lecture 15 Naive Bayes Part 2 00:12:26 Duration
Lecture 16 Decision Trees and Random Forests 00:31:48 Duration
Lecture 17 Natural Language Processing Part 1 00:07:20 Duration
Lecture 18 Natural Language Processing Part 2 00:15:39 Duration
Lecture 19 Natural Language Processing Part 3
Lecture 20 Natural Language Processing Part 4 00:16:17 Duration

Section 11 : Appendix Statistics Overview
Lecture 1 Intro to Appendix B 00:02:39 Duration
Lecture 2 Discrete Uniform Distribution 00:06:05 Duration
Lecture 3 Continuous Uniform Distribution 00:06:56 Duration
Lecture 4 Binomial Distribution 00:12:31 Duration
Lecture 5 Poisson Distribution 00:10:39 Duration
Lecture 6 Normal Distribution 00:06:25 Duration
Lecture 7 Sampling Techniques 00:04:51 Duration
Lecture 8 T-Distribution 00:05:07 Duration
Lecture 9 Hypothesis Testing and Confidence Intervals 00:20:08 Duration
Lecture 10 Chi Square Test and Distribution 00:02:53 Duration
Lecture 11 Bayes Theorem 00:10:03 Duration

Section 12 : Appendix SQL and Python
Lecture 1 Introduction to SQL with Python 00:09:59 Duration
Lecture 2 SQL - SELECT,DISTINCT,WHERE,AND & OR 00:09:59 Duration
Lecture 3 SQL WILDCARDS, ORDER BY, GROUP BY and Aggregate Functions 00:08:25 Duration

Section 13 : Appendix Web Scraping with Python
Lecture 1 Web Scraping Part 1 00:12:14 Duration
Lecture 2 Web Scraping Part 2 00:12:14 Duration

Section 14 : Appendix Python Special Offers
Lecture 1 Python Overview Part 1
Lecture 2 Python Overview Part 2 00:12:19 Duration
Lecture 3 Python Overview Part 3 00:10:09 Duration