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 19 : Predict Stocks Future Prices Using Machine and Deep Learning

 		Lecture 98 Colab Notebooks - Predict Future Stock Prices Using MachineDeep Learning Text
Lecture 99 Task 1 12:22
Lecture 100 Task 2 18:15
Lecture 101 Task 3
Lecture 102 Task 4 22:5
Lecture 103 Task 5 11:26
Lecture 104 Task 6 13:33
Lecture 105 Task 7 13:58
Lecture 106 Task 8 13:1
Lecture 107 Task 9
Lecture 108 Task 10 15:22
Lecture 109 Task 11 13:3
Lecture 110 Task 12

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