#### Section 1 : Welcome! Course Introduction

 Lecture 1 What Does the Course Cover 5:10 Lecture 2 About Proctor Testing Pdf

#### Section 2 : Introduction to programming with Python

 Lecture 3 Programming Explained in 5 Minutes 5:4 Lecture 4 Why Python 5:11 Lecture 5 Why Jupyter 3:29 Lecture 6 Installing Python and Jupyter 7:12 Lecture 7 Jupyter’s Interface – the Dashboard 3:16 Lecture 8 Jupyter’s Interface – Prerequisites for Coding 6:15 Lecture 9 Python 2 vs Python 3 What's the Difference 2:57

#### Section 3 : Python Variables and Data Types

 Lecture 10 Variables Lecture 11 Numbers and Boolean Values 3:6 Lecture 12 Strings 12:18

#### Section 4 : Basic Python Syntax

 Lecture 13 Arithmetic Operators 3:24 Lecture 14 The Double Equality Sign 1:34 Lecture 15 Reassign Values 1:9 Lecture 16 Add Comments 3:20 Lecture 17 Line Continuation 0:50 Lecture 18 Indexing Elements 1:18 Lecture 19 Structure Your Code with Indentation 3:42

#### Section 5 : Python Operators Continued

 Lecture 20 Comparison Operators 2:11 Lecture 21 Logical and Identity Operators 5:36

#### Section 6 : Conditional Statements

 Lecture 22 Introduction to the IF statement 6:14 Lecture 23 Add an ELSE statement 5:38 Lecture 24 Else if, for Brief – ELIF 11:16 Lecture 25 A Note on Boolean values 4:39

#### Section 7 : Python Functions

 Lecture 26 Defining a Function in Python 4:20 Lecture 27 Creating a Function with a Parameter 7:58 Lecture 28 Another Way to Define a Function 5:29 Lecture 29 Using a Function in another Function Lecture 30 Combining Conditional Statements and Functions 3:7 Lecture 31 Creating Functions Containing a Few Arguments 2:48 Lecture 32 Notable Built-in Functions in Python 3:56

#### Section 8 : Python Sequences

 Lecture 33 Lists 8:18 Lecture 34 Using Methods 6:54 Lecture 35 List Slicing 4:31 Lecture 36 Tuples 6:40 Lecture 37 Dictionaries 8:27

#### Section 9 : Using Iterations in Python

 Lecture 38 For Loops 5:40 Lecture 39 While Loops and Incrementing 5:11 Lecture 40 Create Lists with the range() Function 6:22 Lecture 41 Use Conditional Statements and Loops Together 6:30 Lecture 42 All In – Conditional Statements, Functions, and Loops 2:27 Lecture 43 Iterating over Dictionaries 6:22

#### Section 10 : Advanced Python tools

 Lecture 44 Object Oriented Programming 5:0 Lecture 45 Modules and Packages 1:6 Lecture 46 The Standard Library 2:47 Lecture 47 Importing Modules 4:10 Lecture 48 Must-have packages for Finance and Data Science 4:54 Lecture 49 Working with arrays 6:2 Lecture 50 Generating Random Numbers 2:52 Lecture 51 A Note on Using Financial Data in Python 2:42 Lecture 52 Sources of Financial Data Lecture 53 Accessing the Notebook Files 2:35 Lecture 54 Importing and Organizing Data in Python – part I 3:44 Lecture 55 Importing and Organizing Data in Python – part II 7:2 Lecture 56 Importing and Organizing Data in Python – part II 4:38 Lecture 57 Importing and Organizing Data in Python – part III 4:19 Lecture 58 Changing the Index of Your Time-Series Data 3:17 Lecture 59 Restarting the Jupyter Kernel 2:17

#### Section 11 : PART II FINANCE Calculating and Comparing Rates of Return in Python

 Lecture 60 Considering both risk and return 2:33 Lecture 61 What are we going to see next 2:35 Lecture 62 Calculating a security's rate of return 5:31 Lecture 63 Calculating a Security’s Rate of Return in Python – Simple Returns – Part I 5:24 Lecture 64 Calculating a Security’s Rate of Return in Python – Simple Returns – Part II Lecture 65 Calculating a Security’s Return in Python – Logarithmic Returns 3:40 Lecture 66 What is a portfolio of securities and how to calculate its rate of return 2:39 Lecture 67 Calculating a Portfolio of Securities' Rate of Return 8:35 Lecture 68 Popular stock indices that can help us understand financial markets 3:24 Lecture 69 Calculating the Indices' Rate of Return 5:3

#### Section 12 : PART II Finance Measuring Investment Risk

 Lecture 70 How do we measure a security's risk 6:6 Lecture 71 Calculating a Security’s Risk in Python 5:56 Lecture 72 The benefits of portfolio diversification 3:28 Lecture 73 Calculating the covariance between securities 3:35 Lecture 74 Measuring the correlation between stocks 3:59 Lecture 75 Calculating Covariance and Correlation 5:0 Lecture 76 Considering the risk of multiple securities in a portfolio 3:20 Lecture 77 Calculating Portfolio Risk 2:39 Lecture 78 Understanding Systematic vs 2:59 Lecture 79 Calculating Diversifiable and Non-Diversifiable Risk of a Portfolio 4:28

#### Section 13 : PART II Finance - Using Regressions for Financial Analysis

 Lecture 80 The fundamentals of simple regression analysis 3:55 Lecture 81 Running a Regression in Python 6:35 Lecture 82 Are all regressions created equal Learning how to distinguish good regressions 4:55 Lecture 83 mp4 6:14

#### Section 14 : PART II Finance - Markowitz Portfolio Optimization

 Lecture 84 Markowitz Portfolio Theory - One of the main pillars of modern Finance 6:34 Lecture 85 Obtaining the Efficient Frontier in Python – Part I 5:36 Lecture 86 Obtaining the Efficient Frontier in Python – Part II Lecture 87 Obtaining the Efficient Frontier in Python – Part III 2:8

#### Section 15 : Part II Finance - The Capital Asset Pricing Model

 Lecture 88 The intuition behind the Capital Asset Pricing Model (CAPM) 4:45 Lecture 89 Understanding and calculating a security's Beta 4:15 Lecture 90 Calculating the Beta of a Stock 3:38 Lecture 91 The CAPM formula 4:20 Lecture 92 Calculating the Expected Return of a Stock (CAPM) 2:16 Lecture 93 Introducing the Sharpe ratio and how to put it into practice 2:21 Lecture 94 Obtaining the Sharpe ratio in Python 1:23 Lecture 95 Measuring alpha and verifying how good (or bad) a portfolio manager is doing 4:13

#### Section 16 : Part II Finance Multivariate regression analysis

 Lecture 96 Multivariate regression analysis - a valuable tool for finance practitioners 5:42 Lecture 97 Running a multivariate regression in Python 6:21

#### Section 17 : PART II Finance - Monte Carlo simulations as a decision-making tool

 Lecture 98 The essence of Monte Carlo simulations 2:32 Lecture 99 Monte Carlo applied in a Corporate Finance context 2:31 Lecture 100 Monte Carlo Predicting Gross Profit – Part I 6:3 Lecture 101 Monte Carlo Predicting Gross Profit – Part II 2:57 Lecture 102 Forecasting Stock Prices with a Monte Carlo Simulation 4:28 Lecture 103 Monte Carlo Forecasting Stock Prices - Part I 3:39 Lecture 104 Monte Carlo Forecasting Stock Prices - Part II 4:39 Lecture 105 Monte Carlo Forecasting Stock Prices - Part III 4:18 Lecture 106 An Introduction to Derivative Contracts 6:33 Lecture 107 The Black Scholes Formula for Option Pricing 4:52 Lecture 108 Monte Carlo Black-Scholes-Merton 6:1 Lecture 109 Monte Carlo Euler Discretization - Part I 6:22 Lecture 110 Monte Carlo Euler Discretization - Part II 2:10