Section 1 : Course Introduction, Success Tips and Key Learning Outcomes
Lecture 1 Welcome Message copy 00:05:11 Duration
Lecture 2 INTRODUCTION TO BRAINMEASURES PROCTOR SYSTEM
Lecture 3 Course Outline and Key Learning Outcomes 00:16:24 Duration
Lecture 4 Environment Setup & Course Materials Download 00:06:32 Duration
Lecture 5 Google Colab Walkthrough 00:08:54 Duration
Lecture 6 Python for Data Science Learning Path
Lecture 7 Study Tips For Success

Section 2 : PART #1 PYTHON PROGRAMMING FUNDAMENTALS
Lecture 1 Introduction to Part #1 Python Programming Fundamentals 00:01:24 Duration

Section 3 : Python 101 Variables Assignment, Math Operation, Precedence and PrintGet
Lecture 1 Colab Notebooks - Variables Assignment, Math Ops, Precedence, and PrintGet
Lecture 2 Variable assignment 00:14:31 Duration
Lecture 3 Math operations 00:14:36 Duration
Lecture 4 Precedence 00:11:50 Duration
Lecture 5 Print operation 00:11:50 Duration
Lecture 6 Get User Input 00:18:29 Duration

Section 4 : Python 101 Data Types
Lecture 1 Colab Notebooks - Data Types
Lecture 2 Booleans 00:08:26 Duration
Lecture 3 List 00:21:04 Duration
Lecture 4 Dictionaries 00:10:25 Duration
Lecture 5 Strings 00:15:14 Duration
Lecture 6 Tuples 00:07:33 Duration
Lecture 7 Sets 00:05:49 Duration

Section 5 : Python 101 Comparison Operators, Logical Operators, and Conditional Statements
Lecture 1 Colab Notebooks - Comparison Operators, Logical Operators and If Statements
Lecture 2 Comparison operators 00:10:53 Duration
Lecture 3 Logical operators 00:11:09 Duration
Lecture 4 Conditional statements - Part #1 00:17:31 Duration
Lecture 5 Conditional statements - Part #2 00:13:18 Duration

Section 6 : Python 101 Loops
Lecture 1 Colab Notebooks - ForWhile Loops, Range, List Comprehension
Lecture 2 For loops 00:15:38 Duration
Lecture 3 Range 00:11:39 Duration
Lecture 4 While Loops 00:14:04 Duration
Lecture 5 Break a loop 00:11:45 Duration
Lecture 6 Nested loops 00:11:31 Duration
Lecture 7 List comprehension 00:17:40 Duration

Section 7 : Python 101 Functions
Lecture 1 Colab Notebooks - Functions
Lecture 2 Functions built-in functions 00:07:58 Duration
Lecture 3 Custom functions 00:13:52 Duration
Lecture 4 Lambda expression 00:07:47 Duration
Lecture 5 Map 00:10:06 Duration
Lecture 6 Filter 00:09:57 Duration

Section 8 : Python 101 Files Operations
Lecture 1 Colab Notebooks - Files Operations
Lecture 2 Reading & Writing Text Files 00:21:11 Duration
Lecture 3 Reading & Writing CSV Files 00:13:32 Duration

Section 9 : Python 101 Data Science Python Libraries for Data Analysis (Numpy)
Lecture 1 Colab Notebooks - Numpy
Lecture 2 Numpy basics 00:08:49 Duration
Lecture 3 Built-in methods
Lecture 4 Shape Length Type 00:13:21 Duration
Lecture 5 Math operations 00:06:16 Duration
Lecture 6 Slicing & indexing 00:16:38 Duration
Lecture 7 Elements Selection 00:08:16 Duration

Section 10 : Python 101 Data Science Python Libraries for Data Analysis (Pandas)
Lecture 1 Colab Notebooks - Pandas
Lecture 2 Pandas Introduction to Pandas and DataFrames 00:20:44 Duration
Lecture 3 Reading HTML data, and applying functions, and sorting 00:13:21 Duration
Lecture 4 DataFrame operations 00:07:48 Duration
Lecture 5 Pandas with functions 00:09:04 Duration
Lecture 6 Ordering and Sorting 00:05:17 Duration
Lecture 7 Mergingjoiningconcatenation 00:21:21 Duration

Section 11 : Python 101 Data Visualization with Matplotlib
Lecture 1 Colab Notebooks - Data Visualization with Matplotlib
Lecture 2 Line Plot 00:13:49 Duration
Lecture 3 Scatterplot 00:06:35 Duration
Lecture 4 Pie Chart 00:09:19 Duration
Lecture 5 Histograms 00:09:25 Duration
Lecture 6 Multiple Plots 00:05:04 Duration
Lecture 7 Subplots 00:08:47 Duration
Lecture 8 3D Plots 00:08:17 Duration
Lecture 9 BoxPlot 00:09:22 Duration

Section 12 : Python 101 Data Visualization with Seaborn
Lecture 1 Colab Notebooks - Data Visualization with Seaborn
Lecture 2 Data Visualization with Seaborn - Part #1 00:22:11 Duration
Lecture 3 Data Visualization with Seaborn - Part #2 00:13:57 Duration

Section 13 : PART #2 PYTHON FOR FINANCIAL ANALYSIS
Lecture 1 Introduction to Part #2 Python for Financial Analysis 00:00:55 Duration

Section 14 : Stocks Data Analysis and Visualization in Python
Lecture 1 Colab Notebooks - Stocks Data Analysis and Visualization in Python
Lecture 2 Task 1 00:06:37 Duration
Lecture 3 Task 2 00:19:25 Duration
Lecture 4 Task 3 00:15:40 Duration
Lecture 5 Task 4 00:11:29 Duration
Lecture 6 Task 5 00:07:39 Duration
Lecture 7 Task 6
Lecture 8 Task 7 00:07:37 Duration
Lecture 9 Task 8 00:12:21 Duration

Section 15 : Asset Allocation and Statistical Data Analysis
Lecture 1 Colab Notebooks - Asset Allocation and Statistical Data Analysis
Lecture 2 Task 1 00:16:23 Duration
Lecture 3 Task 2 00:10:20 Duration
Lecture 4 Task 3 00:09:58 Duration
Lecture 5 Task 4 00:21:37 Duration
Lecture 6 Task 5 00:10:10 Duration
Lecture 7 Task 6 00:15:15 Duration
Lecture 8 Task 7 00:08:58 Duration
Lecture 9 Task 8 00:12:31 Duration

Section 16 : Capital Asset Pricing Model (CAPM)
Lecture 1 Colab Notebooks - Capital Asset Pricing Model (CAPM)
Lecture 2 Task 1 00:18:06 Duration
Lecture 3 Task 2 00:06:28 Duration
Lecture 4 Task 3 00:06:17 Duration
Lecture 5 Task 4 00:13:53 Duration
Lecture 6 Task 5 00:08:44 Duration
Lecture 7 Task 6 00:12:41 Duration
Lecture 8 Task 7 00:10:57 Duration

Section 17 : Monte Carlo Simulation, Portfolio Optimization, and Trading with Momentum
Lecture 1 Monte Carlo Simulation, Portfolio Optimization, and Trading with Momentum

Section 18 : PART #3 MACHINE AND DEEP LEARNING IN FINANCE
Lecture 1 Introduction to Part #3 Machine and Deep Learning in Finance 00:01:05 Duration

Section 19 : Predict Stocks Future Prices Using Machine and Deep Learning
Lecture 1 Colab Notebooks - Predict Future Stock Prices Using MachineDeep Learning
Lecture 2 Task 1 00:12:22 Duration
Lecture 3 Task 2 00:18:15 Duration
Lecture 4 Task 3
Lecture 5 Task 4 00:22:05 Duration
Lecture 6 Task 5 00:11:26 Duration
Lecture 7 Task 6 00:13:33 Duration
Lecture 8 Task 7 00:13:58 Duration
Lecture 9 Task 8 00:13:01 Duration
Lecture 10 Task 9
Lecture 11 Task 10 00:15:22 Duration
Lecture 12 Task 11 00:13:03 Duration
Lecture 13 Task 12

Section 20 : Perform Bank Market Segmentation Using Unsupervised Machine Learning Techniques
Lecture 1 Colab Notebooks - Perform Bank Customers Segmentation
Lecture 2 Problem statement and business case 00:10:42 Duration
Lecture 3 Import libraries and datasets 00:14:43 Duration
Lecture 4 Visualize data 00:19:55 Duration
Lecture 5 Understand K-means algorithm 00:15:19 Duration
Lecture 6 Obtain optimal K 00:08:10 Duration
Lecture 7 Apply K-means clustering 00:09:37 Duration
Lecture 8 Principal component analysis 00:10:06 Duration
Lecture 9 Intuition of autoencoders 00:07:50 Duration
Lecture 10 Train autoencoder 00:12:08 Duration
Lecture 11 Apply autoencoder 00:14:02 Duration

Section 21 : Perform Sentiment Analysis On Stocks Data Using Natural Language Processing
Lecture 1 Colab Notebooks - Perform Sentiment Analysis on Stocks Data
Lecture 2 Task 1 00:10:06 Duration
Lecture 3 Task 2 00:09:53 Duration
Lecture 4 Task 3 00:15:23 Duration
Lecture 5 Task 4 00:12:54 Duration
Lecture 6 Task 5 00:14:36 Duration
Lecture 7 Task 6 00:14:45 Duration
Lecture 8 Task 7 00:22:39 Duration
Lecture 9 Task 8 00:07:23 Duration
Lecture 10 Task 9 00:10:09 Duration
Lecture 11 Task 10 00:10:12 Duration