#### Section 1 : Course Introduction, Success Tips and Key Learning Outcomes

 Lecture 1 Welcome Message copy 5:11 Lecture 2 INTRODUCTION TO BRAINMEASURES PROCTOR SYSTEM Pdf Lecture 3 Course Outline and Key Learning Outcomes 16:24 Lecture 4 Environment Setup & Course Materials Download 6:32 Lecture 5 Google Colab Walkthrough 8:54 Lecture 6 Python for Data Science Learning Path Pdf Lecture 7 Study Tips For Success Pdf

#### Section 2 : PART #1 PYTHON PROGRAMMING FUNDAMENTALS

 Lecture 8 Introduction to Part #1 Python Programming Fundamentals 1:24

#### Section 3 : Python 101 Variables Assignment, Math Operation, Precedence and PrintGet

 Lecture 9 Colab Notebooks - Variables Assignment, Math Ops, Precedence, and PrintGet Text Lecture 10 Variable assignment 14:31 Lecture 11 Math operations 14:36 Lecture 12 Precedence 11:50 Lecture 13 Print operation 11:50 Lecture 14 Get User Input 18:29

#### Section 4 : Python 101 Data Types

 Lecture 15 Colab Notebooks - Data Types Text Lecture 16 Booleans 8:26 Lecture 17 List 21:4 Lecture 18 Dictionaries 10:25 Lecture 19 Strings 15:14 Lecture 20 Tuples 7:33 Lecture 21 Sets 5:49

#### Section 5 : Python 101 Comparison Operators, Logical Operators, and Conditional Statements

 Lecture 22 Colab Notebooks - Comparison Operators, Logical Operators and If Statements Text Lecture 23 Comparison operators 10:53 Lecture 24 Logical operators 11:9 Lecture 25 Conditional statements - Part #1 17:31 Lecture 26 Conditional statements - Part #2 13:18

#### Section 6 : Python 101 Loops

 Lecture 27 Colab Notebooks - ForWhile Loops, Range, List Comprehension Text Lecture 28 For loops 15:38 Lecture 29 Range 11:39 Lecture 30 While Loops 14:4 Lecture 31 Break a loop 11:45 Lecture 32 Nested loops 11:31 Lecture 33 List comprehension 17:40

#### Section 7 : Python 101 Functions

 Lecture 34 Colab Notebooks - Functions Text Lecture 35 Functions built-in functions 7:58 Lecture 36 Custom functions 13:52 Lecture 37 Lambda expression 7:47 Lecture 38 Map 10:6 Lecture 39 Filter 9:57

#### Section 8 : Python 101 Files Operations

 Lecture 40 Colab Notebooks - Files Operations Text Lecture 41 Reading & Writing Text Files 21:11 Lecture 42 Reading & Writing CSV Files 13:32

#### Section 9 : Python 101 Data Science Python Libraries for Data Analysis (Numpy)

 Lecture 43 Colab Notebooks - Numpy Text Lecture 44 Numpy basics 8:49 Lecture 45 Built-in methods Lecture 46 Shape Length Type 13:21 Lecture 47 Math operations 6:16 Lecture 48 Slicing & indexing 16:38 Lecture 49 Elements Selection 8:16

#### Section 10 : Python 101 Data Science Python Libraries for Data Analysis (Pandas)

 Lecture 50 Colab Notebooks - Pandas Text Lecture 51 Pandas Introduction to Pandas and DataFrames 20:44 Lecture 52 Reading HTML data, and applying functions, and sorting 13:21 Lecture 53 DataFrame operations 7:48 Lecture 54 Pandas with functions 9:4 Lecture 55 Ordering and Sorting 5:17 Lecture 56 Mergingjoiningconcatenation 21:21

#### Section 11 : Python 101 Data Visualization with Matplotlib

 Lecture 57 Colab Notebooks - Data Visualization with Matplotlib Text Lecture 58 Line Plot 13:49 Lecture 59 Scatterplot 6:35 Lecture 60 Pie Chart 9:19 Lecture 61 Histograms 9:25 Lecture 62 Multiple Plots 5:4 Lecture 63 Subplots 8:47 Lecture 64 3D Plots 8:17 Lecture 65 BoxPlot 9:22

#### Section 12 : Python 101 Data Visualization with Seaborn

 Lecture 66 Colab Notebooks - Data Visualization with Seaborn Text Lecture 67 Data Visualization with Seaborn - Part #1 22:11 Lecture 68 Data Visualization with Seaborn - Part #2 13:57

#### Section 13 : PART #2 PYTHON FOR FINANCIAL ANALYSIS

 Lecture 69 Introduction to Part #2 Python for Financial Analysis 0:55

#### Section 14 : Stocks Data Analysis and Visualization in Python

 Lecture 70 Colab Notebooks - Stocks Data Analysis and Visualization in Python Text Lecture 71 Task 1 6:37 Lecture 72 Task 2 19:25 Lecture 73 Task 3 15:40 Lecture 74 Task 4 11:29 Lecture 75 Task 5 7:39 Lecture 76 Task 6 Lecture 77 Task 7 7:37 Lecture 78 Task 8 12:21

#### Section 15 : Asset Allocation and Statistical Data Analysis

 Lecture 79 Colab Notebooks - Asset Allocation and Statistical Data Analysis Text Lecture 80 Task 1 16:23 Lecture 81 Task 2 10:20 Lecture 82 Task 3 9:58 Lecture 83 Task 4 21:37 Lecture 84 Task 5 10:10 Lecture 85 Task 6 15:15 Lecture 86 Task 7 8:58 Lecture 87 Task 8 12:31

#### Section 16 : Capital Asset Pricing Model (CAPM)

 Lecture 88 Colab Notebooks - Capital Asset Pricing Model (CAPM) Text Lecture 89 Task 1 18:6 Lecture 90 Task 2 6:28 Lecture 91 Task 3 6:17 Lecture 92 Task 4 13:53 Lecture 93 Task 5 8:44 Lecture 94 Task 6 12:41 Lecture 95 Task 7 10:57

#### Section 17 : Monte Carlo Simulation, Portfolio Optimization, and Trading with Momentum

 Lecture 96 Monte Carlo Simulation, Portfolio Optimization, and Trading with Momentum Text

#### Section 18 : PART #3 MACHINE AND DEEP LEARNING IN FINANCE

 Lecture 97 Introduction to Part #3 Machine and Deep Learning in Finance 1:5

#### Section 20 : Perform Bank Market Segmentation Using Unsupervised Machine Learning Techniques

 Lecture 111 Colab Notebooks - Perform Bank Customers Segmentation Text Lecture 112 Problem statement and business case 10:42 Lecture 113 Import libraries and datasets 14:43 Lecture 114 Visualize data 19:55 Lecture 115 Understand K-means algorithm 15:19 Lecture 116 Obtain optimal K 8:10 Lecture 117 Apply K-means clustering 9:37 Lecture 118 Principal component analysis 10:6 Lecture 119 Intuition of autoencoders 7:50 Lecture 120 Train autoencoder 12:8 Lecture 121 Apply autoencoder 14:2

#### Section 21 : Perform Sentiment Analysis On Stocks Data Using Natural Language Processing

 Lecture 122 Colab Notebooks - Perform Sentiment Analysis on Stocks Data Text Lecture 123 Task 1 10:6 Lecture 124 Task 2 9:53 Lecture 125 Task 3 15:23 Lecture 126 Task 4 12:54 Lecture 127 Task 5 14:36 Lecture 128 Task 6 14:45 Lecture 129 Task 7 22:39 Lecture 130 Task 8 7:23 Lecture 131 Task 9 10:9 Lecture 132 Task 10 10:12