Section 1 : Course Introduction
Lecture 1 Introduction to the Course 00:03:03 Duration
Lecture 2 Course Help and Welcome 00:00:36 Duration
Lecture 3 INTRODUCTION TO BRAINMEASURES PROCTOR SYSTEM

Section 2 : Environment Set-Up
Lecture 1 Python Environment Setup 00:09:52 Duration

Section 3 : Jupyter Overview
Lecture 1 Updates to Notebook
Lecture 2 Jupyter Notebooks 00:13:13 Duration
Lecture 3 Optional Virtual Environments 00:09:51 Duration

Section 4 : Python Crash Course
Lecture 1 Welcome to the Python Crash Course Section! 00:00:17 Duration
Lecture 2 Introduction to Python Crash Course 00:01:18 Duration
Lecture 3 Python Crash Course - Part 1 00:19:19 Duration
Lecture 4 Python Crash Course - Part 2 00:15:08 Duration
Lecture 5 Python Crash Course - Part 3 00:15:43 Duration
Lecture 6 Python Crash Course - Part 4 00:15:24 Duration
Lecture 7 Python Crash Course Exercises - Overview
Lecture 8 Python Crash Course Exercises - Solutions 00:11:51 Duration

Section 5 : Python for Data Analysis - NumPy
Lecture 1 Welcome to the NumPy Section!. 00:00:11 Duration
Lecture 2 Introduction to Numpy
Lecture 3 Numpy Arrays 00:16:44 Duration
Lecture 4 Quick Note on Array Indexing
Lecture 5 Numpy Array Indexing 00:18:17 Duration
Lecture 6 Numpy Operations 00:06:58 Duration
Lecture 7 Numpy Exercises Overview 00:02:38 Duration
Lecture 8 Numpy Exercises Solutions 00:15:26 Duration

Section 6 : Python for Data Analysis - Pandas
Lecture 1 Welcome to the Pandas Section! 00:00:14 Duration
Lecture 2 Introduction to Pandas 00:01:37 Duration
Lecture 3 Series 00:10:34 Duration
Lecture 4 DataFrames - Part 1 00:15:25 Duration
Lecture 5 DataFrames - Part 2 00:17:04 Duration
Lecture 6 DataFrames - Part 3 00:09:06 Duration
Lecture 7 Missing Data 00:06:14 Duration
Lecture 8 Groupby 00:06:44 Duration
Lecture 9 Merging Joining and Concatenating 00:08:50 Duration
Lecture 10 Operations 00:11:59 Duration
Lecture 11 Data Input and Output 00:13:54 Duration

Section 7 : Python for Data Analysis - Pandas Exercises
Lecture 1 Note on SF Salary Exercise
Lecture 2 SF Salaries Exercise Overview 00:01:44 Duration
Lecture 3 SF Salaries Solutions 00:15:20 Duration
Lecture 4 Ecommerce Purchases Exercise Overview 00:02:05 Duration
Lecture 5 Ecommerce Purchases Exercise Solutions 00:15:07 Duration

Section 8 : Python for Data Visualization - Matplotlib
Lecture 1 Welcome to the Data Visualization Section! 00:00:22 Duration
Lecture 2 Introduction to Matplotlib 00:02:55 Duration
Lecture 3 Matplotlib Part 1 00:16:33 Duration
Lecture 4 Matplotlib Part 2 00:15:45 Duration
Lecture 5 Matplotlib Part 3 00:11:46 Duration
Lecture 6 Matplotlib Exercises Overview 00:01:40 Duration
Lecture 7 Matplotlib Exercises - Solutions 00:10:14 Duration

Section 9 : Python for Data Visualization - Seaborn
Lecture 1 Introduction to Seaborn 00:02:53 Duration
Lecture 2 Distribution Plots 00:18:14 Duration
Lecture 3 Categorical Plots 00:17:12 Duration
Lecture 4 Matrix Plots 00:10:09 Duration
Lecture 5 Grids 00:08:25 Duration
Lecture 6 Regression Plots 00:07:08 Duration
Lecture 7 Style and Color 00:08:16 Duration
Lecture 8 Seaborn Exercise Overview 00:01:47 Duration
Lecture 9 Seaborn Exercise Solutions 00:07:03 Duration

Section 10 : Python for Data Visualization - Pandas Built-in Data Visuali
Lecture 1 Pandas Built-in Data Visualization 00:13:22 Duration
Lecture 2 Pandas Data Visualization Exercise 00:01:15 Duration
Lecture 3 Pandas Data Visualization Exercise- Solutions 00:08:52 Duration

Section 11 : Python for Data Visualization - Plotly and Cufflinks
Lecture 1 Introduction to Plotly and Cufflinks 00:03:17 Duration
Lecture 2 READ ME FIRST BEFORE PLOTLY PLEASE!
Lecture 3 Plotly and Cufflinks 00:18:33 Duration

Section 12 : Python for Data Visualization - Geographical Plotting
Lecture 1 Introduction to Geographical Plotting 00:00:49 Duration
Lecture 2 Choropleth Maps - Part 1 - USA 00:19:21 Duration
Lecture 3 Choropleth Maps - Part 2 - World 00:06:48 Duration
Lecture 4 Choropleth Exercises 00:03:06 Duration
Lecture 5 Choropleth Exercises - Solutions 00:09:56 Duration

Section 13 : Data Capstone Project
Lecture 1 Welcome to the Data Capstone Projects! 00:00:17 Duration
Lecture 2 911 Calls Project Overview 00:02:01 Duration
Lecture 3 911 Calls Solutions - Part 1 00:14:23 Duration
Lecture 4 911 Calls Solutions - Part 2 00:17:32 Duration
Lecture 5 Bank Data
Lecture 6 Finance Data Project Overview 00:02:41 Duration
Lecture 7 Finance Project - Solutions Part 1 00:16:07 Duration
Lecture 8 Finance Project - Solutions Part 2 00:18:04 Duration
Lecture 9 Finance Project - Solutions Part 3 00:06:18 Duration

Section 14 : Introduction to Machine Learning
Lecture 1 About Certification
Lecture 2 Welcome to the Machine Learning Section! 00:00:31 Duration
Lecture 3 Supervised Learning Overview 00:08:13 Duration
Lecture 4 Evaluating Performance - Classification Error 00:16:30 Duration
Lecture 5 Evaluating Performance - Regression Error Met 00:05:29 Duration
Lecture 6 Machine Learning with Python 00:09:21 Duration

Section 15 : Linear Regression
Lecture 1 Linear Regression Theory 00:04:28 Duration
Lecture 2 model_selection Updates for SciKit Learn 0.18
Lecture 3 Linear Regression with Python - Part 1 00:18:11 Duration
Lecture 4 Linear Regression with Python - Part 2 00:06:58 Duration
Lecture 5 Linear Regression Project Overview 00:02:26 Duration
Lecture 6 Linear Regression Project Solution 00:18:31 Duration

Section 16 : Cross Validation and Bias-Variance Trade-Off
Lecture 1 Bias Variance Trade-Off 00:06:20 Duration

Section 17 : Logistic Regression
Lecture 1 Logistic Regression Theory 00:11:47 Duration
Lecture 2 Logistic Regression with Python - Part 1 00:17:37 Duration
Lecture 3 Logistic Regression with Python - Part 2 00:16:50 Duration
Lecture 4 Logistic Regression with Python - Part 3 00:08:09 Duration
Lecture 5 Logistic Regression Project Overview 00:01:30 Duration
Lecture 6 Logistic Regression Project Solutions 00:11:00 Duration

Section 18 : K Nearest Neighbors
Lecture 1 KNN Theory 00:05:33 Duration
Lecture 2 KNN with Python 00:19:34 Duration
Lecture 3 KNN Project Overview 00:01:07 Duration
Lecture 4 KNN Project Solutions 00:14:09 Duration

Section 19 : Decision Trees and Random Forests
Lecture 1 Introduction to Tree Methods 00:06:48 Duration
Lecture 2 Decision Trees and Random Forest with Python 00:13:52 Duration
Lecture 3 Decision Trees and Random Forest Project Over 00:03:04 Duration
Lecture 4 Decision Trees and Random Forest Solutions 00:11:53 Duration
Lecture 5 Decision Trees and Random Forest Solutions 00:08:39 Duration

Section 20 : Support Vector Machines
Lecture 1 SVM Theory 00:04:31 Duration
Lecture 2 Support Vector Machines with Python 00:17:47 Duration
Lecture 3 SVM Project Overview 00:02:14 Duration
Lecture 4 SVM Project Solutions 00:10:04 Duration

Section 21 : K Means Clustering
Lecture 1 K Means Algorithm Theory 00:05:09 Duration
Lecture 2 K Means with Python 00:12:30 Duration
Lecture 3 K Means Project Overview 00:02:46 Duration
Lecture 4 K Means Project Solutions 00:16:32 Duration

Section 22 : Principal Component Analysis
Lecture 1 Principal Component Analysis 00:03:20 Duration
Lecture 2 PCA with Python 00:16:19 Duration

Section 23 : Recommender Systems
Lecture 1 Recommender Systems 00:04:07 Duration
Lecture 2 Recommender Systems with Python - Part 1 00:13:31 Duration
Lecture 3 Recommender Systems with Python - Part 2 00:13:16 Duration

Section 24 : Natural Language Processing
Lecture 1 Natural Language Processing Theory 00:05:00 Duration
Lecture 2 NLP with Python - Part 1 00:15:57 Duration
Lecture 3 NLP with Python - Part 2
Lecture 4 NLP with Python - Part 3 00:17:24 Duration
Lecture 5 NLP Project Overview 00:01:59 Duration
Lecture 6 NLP Project Solutions 00:19:20 Duration

Section 25 : Neural Nets and Deep Learning
Lecture 1 About Proctor Testing
Lecture 2 Welcome to the Deep Learning Section!
Lecture 3 Introduction to Artificial Neural Networks 00:02:02 Duration
Lecture 4 Installing Tensorflow
Lecture 5 Perceptron Model
Lecture 6 Neural Networks 00:07:13 Duration
Lecture 7 Activation Functions 00:10:33 Duration
Lecture 8 Multi-Class Classification Considerations 00:10:27 Duration
Lecture 9 Cost Functions and Gradient Descent 00:18:06 Duration
Lecture 10 Backpropagation 00:14:42 Duration
Lecture 11 TensorFlow vs Keras 00:02:07 Duration
Lecture 12 TF Syntax Basics - Part One - Preparing the 00:10:43 Duration
Lecture 13 TF Syntax Basics - Part Two - Creating and 00:13:54 Duration
Lecture 14 TF Syntax Basics - Part Three - Model Evaluat 00:12:51 Duration
Lecture 15 TF Regression Code Along - Exploratory Data 00:18:43 Duration
Lecture 16 TF Regression Code Along - Exploratory Data 00:13:11 Duration
Lecture 17 TF Regression Code Along - Data Preprocessing 00:08:23 Duration
Lecture 18 TF Regression Code Along - Model Evaluation 00:11:18 Duration
Lecture 19 TF Classification Code Along - EDA and Prepro 00:07:59 Duration
Lecture 20 TF Classification - Dealing with Overfitting 00:16:43 Duration
Lecture 21 TensorFlow 2.0 Project Options Overview 00:01:33 Duration
Lecture 22 TensorFlow 2.0 Project Notebook Overview 00:07:36 Duration
Lecture 23 Keras Project Solutions - Dealing with Missin 00:20:29 Duration
Lecture 24 Keras Project Solutions - Dealing with Missin 00:14:40 Duration
Lecture 25 Keras Project Solutions - Categorical Data 00:11:56 Duration
Lecture 26 Keras Project Solutions - Data PreProcessing 00:17:16 Duration
Lecture 27 Keras Project Solutions - Data PreProcessing 00:03:40 Duration
Lecture 28 Keras Project Solutions - Creating and Training 00:03:51 Duration
Lecture 29 Keras Project Solutions - Model Evaluation 00:09:36 Duration
Lecture 30 Tensorboard 00:18:17 Duration

Section 26 : Big Data and Spark with Python
Lecture 1 Welcome to the Big Data Section! 00:00:23 Duration
Lecture 2 Big Data Overview 00:05:26 Duration
Lecture 3 Spark Overview 00:08:54 Duration
Lecture 4 Local Spark Set-Up
Lecture 5 AWS Account Set-Up 00:04:06 Duration
Lecture 6 Quick Note on AWS Security
Lecture 7 EC2 Instance Set-Up 00:16:03 Duration
Lecture 8 SSH with Mac or Linux 00:04:48 Duration
Lecture 9 PySpark Setup 00:23:43 Duration
Lecture 10 Lambda Expressions Review 00:05:21 Duration
Lecture 11 Introduction to Spark and Python 00:08:16 Duration
Lecture 12 RDD Transformations and Actions 00:23:07 Duration