Section 1 : Welcome To The Course

 		lecture 1 Installing Python (Windows & MAC) 8:55
lecture 2 BONUS Learning Paths Text
lecture 3 Get the materials Text
lecture 4 Some Additional Resources!! Text
lecture 5 FAQBot! Text
lecture 6 Your Shortcut To Becoming A Better Data Scienti Text

Section 2 : Core Programming Principles

 		lecture 7 About Proctor Testing Pdf
lecture 8 Types of variables 8:45
lecture 9 Using Variables 8:59
lecture 10 Boolean Variables and Operators 6:3
lecture 11 The While Loop 9:56
lecture 12 The For Loop 7:57
lecture 13 The If statement 12:30
lecture 14 Code indentation in Python 2:41
lecture 15 Section recap 3:8
lecture 16 HOMEWORK Law of Large Numbers 12:52

Section 3 : Fundamentals Of Python

 		lecture 17 What is a List 3:15
lecture 18 Let's create some lists
lecture 19 Using the [] brackets 6:29
lecture 20 Slicing 9:28
lecture 21 Tuples in Python 6:17
lecture 22 Functions in Python 5:37
lecture 23 Packages in Python 13:40
lecture 24 Numpy and Arrays in Python 7:9
lecture 25 Slicing Arrays 4:33
lecture 26 Section Recap 3:6
lecture 27 HOMEWORK Financial Statement Analysis 10:11

Section 4 : Matrices

 		lecture 28 Project Brief Basketball Trends 8:17
lecture 29 Matrices 3:32
lecture 30 Building Your First Matrix 16:50
lecture 31 Dictionaries in Python 14:20
lecture 32 Matrix Operations
lecture 33 Your first visualization 11:4
lecture 34 Expanded Visualization 9:37
lecture 35 Creating Your First Function 11:9
lecture 36 Advanced Function Design
lecture 37 Basketball Insights 11:17
lecture 38 Section Recap 4:8
lecture 39 HOMEWORK Basketball free throws

Section 5 : Data Frames

 		lecture 40 Importing data into Python 8:26
lecture 41 Exploring your dataset 10:51
lecture 42 Renaming Columns of a Dataframe 2:56
lecture 43 Subsetting dataframes in Pandas 16:32
lecture 44 Basic operations with a Data Frame 9:50
lecture 45 Filtering a Data Frame 18:52
lecture 46 Using .at() and .iat() (advanced tutorial) 9:1
lecture 47 Introduction to Seaborn 10:48
lecture 48 Visualizing With Seaborn Part 1 10:5
lecture 49 Keyword Arguments in Python (advanced tutorial 10:42
lecture 50 Section Recap 4:31
lecture 51 HOMEWORK World Trends 6:37

Section 6 : Advanced Visualization

 		lecture 52 What is a Category data type 10:29
lecture 53 Working with JointPlots 7:38
lecture 54 Histograms 7:52
lecture 55 Stacked histograms in Python 18:30
lecture 56 Creating a KDE Plot 8:0
lecture 57 Working with Subplots() 14:6
lecture 58 Violinplots vs Boxplots 8:55
lecture 59 Creating a Facet Grid 12:29
lecture 60 Coordinates and Diagonals 7:55
lecture 61 BONUS Building Dashboards in Python
lecture 62 BONUS Styling Tips 15:46
lecture 63 BONUS Finishing Touches 14:48
lecture 64 Section Recap 5:38
lecture 65 HOMEWORK Movie Domestic % Gross 7:32

Section 7 : Homework Solutions

 		lecture 66 Homework Solution Section 2 Law Of Large Numbe 8:57
lecture 67 Homework Solution Section 3 Financial Statemen 10:2
lecture 68 Homework Solution Section 3 Financial Statemen 13:40
lecture 69 Homework Solution Section 4 Basketball Free Th 17:23
lecture 70 Homework Solution Section 5 World Trends (Part1) 15:32
lecture 71 Homework Solution Section 5 World Trends (Part2) 14:35
lecture 72 Homework Solution Section 6 Movie Domestic % G 16:35
lecture 73 Homework Solution Section 6 Movie Domestic % 8:19