10 --- PART 2 STATISTICS AND HYPOTHESIS TESTING WITH PYTHON NUMPY AND SCIPY ---/100 Statistics - Overview Terms and Vocabulary.mp4 100.4 MB
24 Managing Time Series and Financial Data with Pandas/284 Creating a customized DatetimeIndex with pd.date_range().mp4 98.2 MB
22 Data Visualization with Pandas Matplotlib and Seaborn/249 Customization of Plots.mp4 88.2 MB
09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/094 Mortgage Loan Analysis - Interest Payments and Amortization Schedule.mp4 85.3 MB
07 How to create great graphs with Matplotlib - Plotting NPV and IRR/068 Customizing Plots (Part 2).mp4 84.3 MB
20 Pandas Basics - Starting from Zero/210 Slicing Rows and Columns with loc (label-based indexing).mp4 84.2 MB
31 Issues in Linear Regression Analysis and Logistic Regression/378 Detecting and Handling Serial Correlation (Autocorrelation).mp4 83.2 MB
24 Managing Time Series and Financial Data with Pandas/303 Importing Financial Data from Excel.mp4 81.6 MB
25 Creating analyzing and optimizing Financial Portfolios with Python/316 Coding Exercise 13 (Solution).mp4 81.5 MB
23 Pandas Advanced/267 Adding new Rows to a DataFrame.mp4 79.9 MB
08 The Numpy Package Working with numbers made easy/083 Coding Exercise 7.mp4 76.7 MB
14 How to perform Hypothesis Tests Z-Tests t-Tests Bootstrapping more/146 Two-tailed Z-Test with known Population Variance.mp4 55.3 MB
30 Case Study Multi-Factor Models (Fama-French)/364 Fama-French An Introduction.mp4 55.1 MB
18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/187 Monte Carlo Simulations for Value-at-Risk - Parametric (Part 3).mp4 53.5 MB
14 How to perform Hypothesis Tests Z-Tests t-Tests Bootstrapping more/145 Hypothesis Testing (Theory).mp4 53.4 MB
01 Getting Started/004 Jupyter Notebooks - let s get started.mp4 53.4 MB
26 --- PART 5 REGRESSION ANALYSIS (A MUST-HAVE FOR MACHINE LEARNING) ---/327 Introduction to Regression Analysis.mp4 53.1 MB
29 Multiple Regression Models/356 Movies Dataset - Preparing the Data.mp4 52.0 MB
14 How to perform Hypothesis Tests Z-Tests t-Tests Bootstrapping more/153 Testing for Normality of Financial Returns with scipy.stats.mp4 51.9 MB
30 Case Study Multi-Factor Models (Fama-French)/367 The Factors Size Value.mp4 51.5 MB
24 Managing Time Series and Financial Data with Pandas/281 Converting strings to datetime objects with pd.to_datetime().mp4 51.2 MB
28 OLS Regression ANOVA and Hypothesis Testing/344 OLS Regression with statsmodels - Intro.mp4 51.2 MB
21 Pandas Intermediate/231 Sorting DataFrames with sort_index() and sort_values().mp4 46.4 MB
29 Multiple Regression Models/362 Creating and working with Dummy Variables (Part 2).mp4 46.1 MB
11 How to perform Descriptive Statistics on Populations and Samples/103 Population vs. Sample.mp4 46.0 MB
20 Pandas Basics - Starting from Zero/201 Built-in Functions Attributes and Methods.mp4 46.0 MB
18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/186 Monte Carlo Simulations for Value-at-Risk - Parametric (Part 2).mp4 45.6 MB
23 Pandas Advanced/265 Creating DataFrames from Scratch with pd.DataFrame().mp4 45.5 MB
23 Pandas Advanced/273 Splitting with many Keys.mp4 44.3 MB
24 Managing Time Series and Financial Data with Pandas/291 Advanced Indexing with reindex().mp4 44.2 MB
18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/188 Monte Carlo Simulations for Value-at-Risk - Bootstrapping (Part 1).mp4 44.0 MB
18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/191 Dynamic path-dependent Simulations (Part 1).mp4 43.6 MB
24 Managing Time Series and Financial Data with Pandas/289 Downsampling Time Series with resample (Part 2).mp4 43.5 MB
23 Pandas Advanced/261 Removing Rows.mp4 43.4 MB
09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/097 Capital Budgeting - Mutually exclusive Projects (Part 2).mp4 43.0 MB
05 100 Python Objects Data Types Operators Functional Programming/049 Intro to Strings.mp4 42.8 MB
31 Issues in Linear Regression Analysis and Logistic Regression/381 Logistic Regression with statsmodels (Part 2).mp4 42.7 MB
07 How to create great graphs with Matplotlib - Plotting NPV and IRR/069 Plotting NPV IRR.mp4 42.7 MB
24 Managing Time Series and Financial Data with Pandas/283 Indexing and Slicing Time Series.mp4 42.6 MB
17 How to create your own user-defined Functions/171 What s the difference between Positional Arguments vs. Keyword Arguments.mp4 38.1 MB
24 Managing Time Series and Financial Data with Pandas/296 Initial Inspection and Visualization.mp4 38.1 MB
21 Pandas Intermediate/220 Analyzing non-numerical Series with unique() nunique() value_counts().mp4 37.9 MB
18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/189 Monte Carlo Simulations for Value-at-Risk - Bootstrapping (Part 2).mp4 37.9 MB
08 The Numpy Package Working with numbers made easy/072 Numpy Arrays.mp4 37.5 MB
22 Data Visualization with Pandas Matplotlib and Seaborn/256 Seaborn Heatmaps.mp4 37.4 MB
12 Common Probability Distributions and how to construct Confidence Intervals/119 Probability Distributions - Overview.mp4 37.4 MB
06 How to solve for IRR YTM with While Loops and Conditional Statements/058 While Loops.mp4 37.4 MB
05 100 Python Objects Data Types Operators Functional Programming/053 Comparison Logical and Membership Operators in Action.mp4 37.2 MB
17 How to create your own user-defined Functions/177 Scope - easily explained.mp4 37.0 MB
24 Managing Time Series and Financial Data with Pandas/300 Measuring Stock Performance with MEAN Returns and STD of Returns.mp4 36.6 MB
20 Pandas Basics - Starting from Zero/203 Explore your own Dataset Coding Exercise 1 (Solution).mp4 36.4 MB
05 100 Python Objects Data Types Operators Functional Programming/044 Mutable vs. immutable Objects (Part 1).mp4 36.2 MB
24 Managing Time Series and Financial Data with Pandas/280 Importing Time Series Data from csv-files.mp4 36.1 MB
13 How to estimate Population parameters with Samples - Sampling and Estimation/131 Sample Statistic Sampling Error and Sampling Distribution (Theory).mp4 35.6 MB
25 Creating analyzing and optimizing Financial Portfolios with Python/322 Beta and Alpha.mp4 35.2 MB
04 How to use Lists and For Loops for TVM Problems with many Cashflows/026 Calculate FV and PV for many Cashflows.mp4 35.2 MB
24 Managing Time Series and Financial Data with Pandas/290 The PeriodIndex object.mp4 35.1 MB
21 Pandas Intermediate/222 Sorting of Series and Introduction to the inplace - parameter.mp4 35.0 MB
04 How to use Lists and For Loops for TVM Problems with many Cashflows/027 The Net Present Value - NPV (Theory).mp4 34.9 MB
13 How to estimate Population parameters with Samples - Sampling and Estimation/142 Student s t-Distribution vs. Normal Distribution with scipy.stats.mp4 31.1 MB
24 Managing Time Series and Financial Data with Pandas/298 The shift() method.mp4 30.9 MB
22 Data Visualization with Pandas Matplotlib and Seaborn/252 Scatterplots.mp4 30.9 MB
18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/185 Monte Carlo Simulations for Value-at-Risk - Parametric (Part 1).mp4 30.9 MB
28 OLS Regression ANOVA and Hypothesis Testing/353 Case Study (Part 3) The Market Model (Single Factor Model).mp4 30.3 MB
24 Managing Time Series and Financial Data with Pandas/282 Initial Analysis Visualization of Time Series.mp4 30.3 MB
16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/159 How to slice 2-dim Numpy Arrays (Part 1).mp4 30.3 MB
22 Data Visualization with Pandas Matplotlib and Seaborn/251 Histogramms (Part 2).mp4 30.3 MB
17 How to create your own user-defined Functions/172 How to work with Default Arguments.mp4 29.9 MB
08 The Numpy Package Working with numbers made easy/080 Advanced Filtering Bitwise Operators.mp4 29.7 MB
12 Common Probability Distributions and how to construct Confidence Intervals/120 Discrete Uniform Distributions.mp4 29.6 MB
13 How to estimate Population parameters with Samples - Sampling and Estimation/143 Bootstrapping with Python an alternative method without Statistics.mp4 29.4 MB
21 Pandas Intermediate/228 Renaming Index Column Labels with rename().mp4 29.4 MB
11 How to perform Descriptive Statistics on Populations and Samples/110 Variability around the Central Tendency Dispersion (Theory).mp4 29.0 MB
27 Correlation and Regression/332 Covariance and Correlation Coefficient (Theory).mp4 28.9 MB
16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/165 Arithmetic Vectorized Operations with 2-dim Numpy Arrays.mp4 28.8 MB
11 How to perform Descriptive Statistics on Populations and Samples/115 How to calculate Skew and Kurtosis with scipy.stats.mp4 28.8 MB
17 How to create your own user-defined Functions/170 Defining your first user-defined Function.mp4 28.7 MB
23 Pandas Advanced/276 Hierarchical Indexing with Groupby.mp4 28.3 MB
12 Common Probability Distributions and how to construct Confidence Intervals/124 Normal Distribution - Probability Density Function (pdf) with scipy.stats.mp4 28.2 MB
17 How to create your own user-defined Functions/173 The Default Argument None.mp4 28.1 MB
21 Pandas Intermediate/232 nunique() and nlargest() nsmallest() with DataFrames.mp4 28.0 MB
13 How to estimate Population parameters with Samples - Sampling and Estimation/140 Unknown Population Variance - the Standard Case (Example 1).mp4 27.6 MB
27 Correlation and Regression/340 Case Study (Part 1) The Market Model (Single Factor Model).mp4 27.6 MB
13 How to estimate Population parameters with Samples - Sampling and Estimation/135 Central Limit Theorem (Coding Part 1).mp4 27.6 MB
17 How to create your own user-defined Functions/175 Sequences as arguments and args.mp4 27.5 MB
31 Issues in Linear Regression Analysis and Logistic Regression/372 Linear Regression - not that easy.mp4 25.4 MB
12 Common Probability Distributions and how to construct Confidence Intervals/123 Creating a normally distributed Random Variable.mp4 25.3 MB
27 Correlation and Regression/333 How to calculate Covariance and Correlation in Python.mp4 25.2 MB
06 How to solve for IRR YTM with While Loops and Conditional Statements/059 The Internal Rate of Return - IRR (Theory).mp4 25.1 MB
18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/183 How to use the Parametric Method to calculate Value-at-Risk (VaR).mp4 25.0 MB
13 How to estimate Population parameters with Samples - Sampling and Estimation/138 Point Estimates vs. Confidence Interval Estimates (known Population Variance).mp4 24.6 MB
07 How to create great graphs with Matplotlib - Plotting NPV and IRR/065 Line Plots.mp4 24.5 MB
25 Creating analyzing and optimizing Financial Portfolios with Python/314 Sharpe Ratio - visualized and explained.mp4 24.4 MB
09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/096 Capital Budgeting - Mutually exclusive Projects (Part 1).mp4 24.2 MB
19 --- PART 4 MANAGING (FINANCIAL) DATA WITH PANDAS BEYOND EXCEL ---/198 Tabular Data and Pandas DataFrames.mp4 24.1 MB
11 How to perform Descriptive Statistics on Populations and Samples/104 Visualizing Frequency Distributions with plt.hist().mp4 23.7 MB
31 Issues in Linear Regression Analysis and Logistic Regression/375 Non-Linear Relationships - Feature Transformation.mp4 23.7 MB
08 The Numpy Package Working with numbers made easy/081 Determining a Project s Payback Period with np.where().mp4 23.6 MB
16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/162 How to perform row-wise and column-wise Operations.mp4 23.6 MB
11 How to perform Descriptive Statistics on Populations and Samples/107 Coding Measures of Central Tendency - Mean and Median.mp4 23.4 MB
09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/084 Evaluating Investments with np.npv() and np.irr().mp4 23.3 MB
03 How to use Python as a Calculator for basic Time Value of Money Problems/016 More on Variables and Memory.mp4 23.3 MB
14 How to perform Hypothesis Tests Z-Tests t-Tests Bootstrapping more/148 Calculating and interpreting z-statistic and p-value with scipy.stats.mp4 23.3 MB
28 OLS Regression ANOVA and Hypothesis Testing/348 OLS Regression with statsmodels and DataFrames.mp4 23.1 MB
08 The Numpy Package Working with numbers made easy/077 Numpy Array Methods and Attributes.mp4 23.0 MB
06 How to solve for IRR YTM with While Loops and Conditional Statements/057 Calculate a Project s Payback Period.mp4 22.9 MB
05 100 Python Objects Data Types Operators Functional Programming/045 Mutable vs. immutable Objects (Part 2).mp4 22.9 MB
30 Case Study Multi-Factor Models (Fama-French)/369 The Factors Profitability and Investment.mp4 22.9 MB
09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/090 Frequency of compounding and the effective annual interest rate.mp4 22.9 MB
13 How to estimate Population parameters with Samples - Sampling and Estimation/133 Sampling Distribution.mp4 22.6 MB
31 Issues in Linear Regression Analysis and Logistic Regression/374 Detecting and Handling Outliers (Part 2).mp4 22.6 MB
21 Pandas Intermediate/234 Filtering DataFrames by many Conditions (AND).mp4 22.3 MB
10 --- PART 2 STATISTICS AND HYPOTHESIS TESTING WITH PYTHON NUMPY AND SCIPY ---/101 Coding Projects Part 2 - Overview.mp4 22.1 MB
24 Managing Time Series and Financial Data with Pandas/302 Financial Time Series - Covariance and Correlation.mp4 22.1 MB
28 OLS Regression ANOVA and Hypothesis Testing/352 Regression Analysis with statsmodels - the Summary Table.mp4 22.0 MB
05 100 Python Objects Data Types Operators Functional Programming/036 How to round Floats (and Integers) with round().mp4 21.9 MB
16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/166 The keepdims parameter.mp4 21.8 MB
21 Pandas Intermediate/221 The copy() method.mp4 21.8 MB
11 How to perform Descriptive Statistics on Populations and Samples/106 Measures of Central Tendency (Theory).mp4 21.7 MB
13 How to estimate Population parameters with Samples - Sampling and Estimation/132 Sampling with np.random.choice().mp4 21.6 MB
20 Pandas Basics - Starting from Zero/207 Slicing Rows and Columns with iloc (position-based indexing).mp4 21.6 MB
22 Data Visualization with Pandas Matplotlib and Seaborn/250 Histogramms (Part 1).mp4 21.5 MB
18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/181 What is the Value-at-Risk (VaR) (Theory).mp4 21.4 MB
29 Multiple Regression Models/360 How to test the Significance of the Model as a whole (F-Test).mp4 21.3 MB
13 How to estimate Population parameters with Samples - Sampling and Estimation/139 The Student s t-distribution What is it and whywhen do we use it.mp4 21.1 MB
12 Common Probability Distributions and how to construct Confidence Intervals/121 Continuous Uniform Distributions.mp4 21.1 MB
27 Correlation and Regression/334 Correlation and Scatterplots visual Interpretation.mp4 21.0 MB
18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/190 Conditional Value-at-Risk (CVaR).mp4 20.4 MB
08 The Numpy Package Working with numbers made easy/076 View vs. copy - potential Pitfalls when slicing Numpy Arrays.mp4 20.2 MB
03 How to use Python as a Calculator for basic Time Value of Money Problems/012 Calculate Interest Rates and Returns with Python.mp4 20.2 MB
15 -- PART 3 ADVANCED PYTHON MONTE CARLO SIMULATIONS AND VALUE AT RISK (VAR) ---/156 Coding Projects Part 3 - Overview.mp4 19.8 MB
21 Pandas Intermediate/244 The agg() method.mp4 19.8 MB
20 Pandas Basics - Starting from Zero/205 Selecting Rows with Square Brackets (not advisable).mp4 19.7 MB
08 The Numpy Package Working with numbers made easy/074 Vectorized Operations with Numpy Arrays.mp4 19.6 MB
16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/168 Merging and Concatenating Numpy Arrays.mp4 19.6 MB
09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/098 Capital Budgeting - Mutually exclusive Projects (Part 3).mp4 19.6 MB
17 How to create your own user-defined Functions/174 How to unpack Iterables.mp4 19.5 MB
12 Common Probability Distributions and how to construct Confidence Intervals/122 The Normal Distribution (Theory).mp4 19.3 MB
16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/157 How to work with nested Lists.mp4 19.1 MB
22 Data Visualization with Pandas Matplotlib and Seaborn/253 First Steps with Seaborn.mp4 19.1 MB
08 The Numpy Package Working with numbers made easy/079 Boolean Arrays and Conditional Filtering.mp4 19.0 MB
03 How to use Python as a Calculator for basic Time Value of Money Problems/013 Introduction to Variables.mp4 19.0 MB
11 How to perform Descriptive Statistics on Populations and Samples/114 Skew and Kurtosis (Theory).mp4 18.9 MB
28 OLS Regression ANOVA and Hypothesis Testing/346 OLS Regression with Statsmodels - ANOVA.mp4 18.7 MB
13 How to estimate Population parameters with Samples - Sampling and Estimation/141 Unknown Population Variance - the Standard Case (Example 2).mp4 18.7 MB
28 OLS Regression ANOVA and Hypothesis Testing/351 Hypothesis Testing of Regression Coefficients with statsmodels.mp4 18.6 MB
08 The Numpy Package Working with numbers made easy/078 Numpy Universal Functions.mp4 18.6 MB
18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/193 Dynamic path-dependent Simulations (Part 3).mp4 18.6 MB
05 100 Python Objects Data Types Operators Functional Programming/038 Lists and Element-wise Operations.mp4 18.4 MB
11 How to perform Descriptive Statistics on Populations and Samples/112 Percentiles with PythonNumpy.mp4 18.4 MB
03 How to use Python as a Calculator for basic Time Value of Money Problems/018 The print() Function.mp4 18.3 MB
12 Common Probability Distributions and how to construct Confidence Intervals/118 Reproducibility with np.random.seed().mp4 18.1 MB
25 Creating analyzing and optimizing Financial Portfolios with Python/307 Intro.mp4 18.1 MB
04 How to use Lists and For Loops for TVM Problems with many Cashflows/025 The range Object - another Iterable.mp4 17.9 MB
03 How to use Python as a Calculator for basic Time Value of Money Problems/017 Variables - Dos Don ts and Conventions.mp4 17.9 MB
23 Pandas Advanced/266 Adding new Rows (Hands-on).mp4 17.8 MB
13 How to estimate Population parameters with Samples - Sampling and Estimation/137 Central Limit Theorem (Theory).mp4 17.8 MB
16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/164 Creating 2-dim Numpy Arrays from Scratch.mp4 17.7 MB
25 Creating analyzing and optimizing Financial Portfolios with Python/311 What is the Sharpe Ratio and a Risk Free Asset.mp4 17.7 MB
27 Correlation and Regression/336 Testing for Correlation (t-Test).mp4 17.4 MB
11 How to perform Descriptive Statistics on Populations and Samples/108 Coding Measures of Central Tendency - Geometric Mean.mp4 17.4 MB
16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/161 Recap Changing Elements in a Numpy Array slice.mp4 17.3 MB
26 --- PART 5 REGRESSION ANALYSIS (A MUST-HAVE FOR MACHINE LEARNING) ---/328 Coding Projects Part 5 - Overview.mp4 17.3 MB
16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/167 Adding Removing Elements.mp4 17.3 MB
03 How to use Python as a Calculator for basic Time Value of Money Problems/008 Intro to the Time Value of Money (TVM) Concept (Theory).mp4 17.3 MB
11 How to perform Descriptive Statistics on Populations and Samples/113 Variance and Standard Deviation with PythonNumpy.mp4 17.1 MB
16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/158 2-dimensional Numpy Arrays.mp4 16.9 MB
25 Creating analyzing and optimizing Financial Portfolios with Python/318 Capital Market Line (CML) Two-Fund-Theorem.mp4 16.6 MB
09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/087 How to solve for annuity payments with np.pmt().mp4 16.5 MB
14 How to perform Hypothesis Tests Z-Tests t-Tests Bootstrapping more/151 One-tailed t-Test (unknown Population Variance).mp4 16.3 MB
28 OLS Regression ANOVA and Hypothesis Testing/350 Hypothesis Testing of Regression Coefficients (Theory).mp4 16.3 MB
12 Common Probability Distributions and how to construct Confidence Intervals/125 Normal Distribution - Cumulative Distribution Function (cdf) with scipy.stats.mp4 16.1 MB
02 ---- PART 1 PYTHON BASICS TIME VALUE OF MONEY AND CAPITAL BUDGETING ----/007 Coding Projects Part 1 - Overview.mp4 16.1 MB
24 Managing Time Series and Financial Data with Pandas/294 Getting Ready (Installing required library).mp4 16.1 MB
09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/089 How to calculate the required Contract Value with np.pv().mp4 16.0 MB
31 Issues in Linear Regression Analysis and Logistic Regression/379 Logistic Regression (Theory).mp4 15.8 MB
23 Pandas Advanced/262 Adding new Columns to a DataFrame.mp4 15.8 MB
29 Multiple Regression Models/358 Coefficient of Determination (Adjusted R squared).mp4 15.8 MB
12 Common Probability Distributions and how to construct Confidence Intervals/127 Properties of the Standard Normal Distribution (Theory).mp4 15.6 MB
07 How to create great graphs with Matplotlib - Plotting NPV and IRR/064 Intro.mp4 15.2 MB
04 How to use Lists and For Loops for TVM Problems with many Cashflows/028 Calculate an Investment Project s NPV.mp4 15.0 MB
21 Pandas Intermediate/237 any() and all().mp4 14.9 MB
03 How to use Python as a Calculator for basic Time Value of Money Problems/011 Interest Rates and Returns (Theory).mp4 14.9 MB
04 How to use Lists and For Loops for TVM Problems with many Cashflows/023 Indexing Lists.mp4 14.5 MB
08 The Numpy Package Working with numbers made easy/073 Indexing and Slicing Numpy Arrays.mp4 14.3 MB
18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/184 How to use the Historical Method to calculate Value-at-Risk (VaR).mp4 14.3 MB
17 How to create your own user-defined Functions/176 How to return many results.mp4 14.1 MB
05 100 Python Objects Data Types Operators Functional Programming/042 Sorting and Reversing Lists.mp4 13.8 MB
14 How to perform Hypothesis Tests Z-Tests t-Tests Bootstrapping more/147 What is the p-value (Theory).mp4 13.7 MB
03 How to use Python as a Calculator for basic Time Value of Money Problems/009 Calculate Future Values (FV) with Python Compounding.mp4 13.4 MB
09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/088 How to solve for the number of periodic payments with np.nper().mp4 13.3 MB
06 How to solve for IRR YTM with While Loops and Conditional Statements/062 Solving for a Bond s Yield to Maturity (YTM).mp4 13.1 MB
11 How to perform Descriptive Statistics on Populations and Samples/109 Excursus Why Log Returns are useful.mp4 13.0 MB
27 Correlation and Regression/339 How to interpret Intercept and Slope Coefficient.mp4 12.9 MB
11 How to perform Descriptive Statistics on Populations and Samples/111 Minimum Maximum and Range with PythonNumpy.mp4 12.9 MB
25 Creating analyzing and optimizing Financial Portfolios with Python/308 Getting the Data.mp4 12.8 MB
05 100 Python Objects Data Types Operators Functional Programming/031 The Data Type Hierarchy (Theory).mp4 11.3 MB
13 How to estimate Population parameters with Samples - Sampling and Estimation/134 Standard Error.mp4 11.2 MB
21 Pandas Intermediate/242 Exporting DataFrames to csv.mp4 11.1 MB
04 How to use Lists and For Loops for TVM Problems with many Cashflows/020 TVM Problems with many Cashflows.mp4 11.0 MB
27 Correlation and Regression/341 Case Study (Part 2) The Market Model (Single Factor Model).mp4 10.8 MB
09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/095 Calculate PV of equal installments with np.pv() - Valuation of Bonds.mp4 10.6 MB
05 100 Python Objects Data Types Operators Functional Programming/041 Changing Elements in Lists.mp4 10.6 MB
03 How to use Python as a Calculator for basic Time Value of Money Problems/010 Calculate Present Values (FV) with Python Discounting.mp4 10.5 MB
24 Managing Time Series and Financial Data with Pandas/285 More on pd.date_range().mp4 10.2 MB
25 Creating analyzing and optimizing Financial Portfolios with Python/320 Systematic vs. unsystematic Risk.en.srt 14.5 kB
17 How to create your own user-defined Functions/179 Putting it all together - Case Study.en.srt 14.3 kB
09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/094 Mortgage Loan Analysis - Interest Payments and Amortization Schedule.en.srt 14.2 kB
22 Data Visualization with Pandas Matplotlib and Seaborn/255 Seaborn Regression Plots.en.srt 14.2 kB
22 Data Visualization with Pandas Matplotlib and Seaborn/249 Customization of Plots.en.srt 14.2 kB
31 Issues in Linear Regression Analysis and Logistic Regression/378 Detecting and Handling Serial Correlation (Autocorrelation).en.srt 14.1 kB
25 Creating analyzing and optimizing Financial Portfolios with Python/310 Creating many random Portfolios with Python.en.srt 13.8 kB
08 The Numpy Package Working with numbers made easy/083 Coding Exercise 7.en.srt 13.7 kB
06 How to solve for IRR YTM with While Loops and Conditional Statements/060 Solving for a Project s IRR.en.srt 13.7 kB
05 100 Python Objects Data Types Operators Functional Programming/043 Adding and removing Elements fromto Lists.en.srt 11.9 kB
18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/194 Dynamic path-dependent Simulations (Part 4).en.srt 11.9 kB
20 Pandas Basics - Starting from Zero/212 Summary and Outlook.en.srt 11.8 kB
18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/187 Monte Carlo Simulations for Value-at-Risk - Parametric (Part 3).en.srt 11.7 kB
28 OLS Regression ANOVA and Hypothesis Testing/344 OLS Regression with statsmodels - Intro.en.srt 11.7 kB
14 How to perform Hypothesis Tests Z-Tests t-Tests Bootstrapping more/146 Two-tailed Z-Test with known Population Variance.en.srt 11.7 kB
06 How to solve for IRR YTM with While Loops and Conditional Statements/056 Keywords pass continue and break.en.srt 11.7 kB
03 How to use Python as a Calculator for basic Time Value of Money Problems/019 Coding Exercise 1.en.srt 11.7 kB
24 Managing Time Series and Financial Data with Pandas/281 Converting strings to datetime objects with pd.to_datetime().en.srt 11.4 kB
06 How to solve for IRR YTM with While Loops and Conditional Statements/055 Conditional Statements.en.srt 11.4 kB
30 Case Study Multi-Factor Models (Fama-French)/367 The Factors Size Value.en.srt 11.2 kB
01 Getting Started/004 Jupyter Notebooks - let s get started.en.srt 11.1 kB
22 Data Visualization with Pandas Matplotlib and Seaborn/248 Visualization with Matplotlib (Intro).en.srt 11.1 kB
21 Pandas Intermediate/231 Sorting DataFrames with sort_index() and sort_values().en.srt 11.0 kB
12 Common Probability Distributions and how to construct Confidence Intervals/119 Probability Distributions - Overview.en.srt 8.1 kB
11 How to perform Descriptive Statistics on Populations and Samples/103 Population vs. Sample.en.srt 8.1 kB
27 Correlation and Regression/338 A simple Linear Regression Model with numpy Scipy.en.srt 8.1 kB
18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/189 Monte Carlo Simulations for Value-at-Risk - Bootstrapping (Part 2).en.srt 8.1 kB
11 How to perform Descriptive Statistics on Populations and Samples/110 Variability around the Central Tendency Dispersion (Theory).en.srt 8.0 kB
18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/188 Monte Carlo Simulations for Value-at-Risk - Bootstrapping (Part 1).en.srt 7.9 kB
24 Managing Time Series and Financial Data with Pandas/297 Normalizing Time Series to a Base Value (100).en.srt 7.9 kB
17 How to create your own user-defined Functions/173 The Default Argument None.en.srt 7.8 kB
27 Correlation and Regression/330 Cleaning and preparing the Data - Movies Database (Part 1).en.srt 7.8 kB
31 Issues in Linear Regression Analysis and Logistic Regression/381 Logistic Regression with statsmodels (Part 2).en.srt 7.8 kB
30 Case Study Multi-Factor Models (Fama-French)/366 Single-Factor Models with the Fama-French Market Portfolio (Part 2).en.srt 7.7 kB
23 Pandas Advanced/276 Hierarchical Indexing with Groupby.en.srt 7.7 kB
18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/186 Monte Carlo Simulations for Value-at-Risk - Parametric (Part 2).en.srt 7.7 kB
03 How to use Python as a Calculator for basic Time Value of Money Problems/008 Intro to the Time Value of Money (TVM) Concept (Theory).en.srt 7.7 kB
25 Creating analyzing and optimizing Financial Portfolios with Python/324 Cyclical vs. non-cyclical Stocks - another Intuition on Beta.en.srt 7.6 kB
17 How to create your own user-defined Functions/170 Defining your first user-defined Function.en.srt 7.6 kB
14 How to perform Hypothesis Tests Z-Tests t-Tests Bootstrapping more/149 One-tailed Z-Test with known Population Variance.en.srt 7.5 kB
17 How to create your own user-defined Functions/171 What s the difference between Positional Arguments vs. Keyword Arguments.en.srt 7.5 kB
09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/090 Frequency of compounding and the effective annual interest rate.en.srt 7.3 kB
05 100 Python Objects Data Types Operators Functional Programming/030 Data Types in Action.en.srt 7.3 kB
09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/097 Capital Budgeting - Mutually exclusive Projects (Part 2).en.srt 7.3 kB
06 How to solve for IRR YTM with While Loops and Conditional Statements/059 The Internal Rate of Return - IRR (Theory).en.srt 7.3 kB
24 Managing Time Series and Financial Data with Pandas/290 The PeriodIndex object.en.srt 7.3 kB
27 Correlation and Regression/331 Cleaning and preparing the Data - Movies Database (Part 2).en.srt 7.2 kB
12 Common Probability Distributions and how to construct Confidence Intervals/120 Discrete Uniform Distributions.en.srt 7.2 kB
22 Data Visualization with Pandas Matplotlib and Seaborn/253 First Steps with Seaborn.en.srt 7.2 kB
08 The Numpy Package Working with numbers made easy/080 Advanced Filtering Bitwise Operators.en.srt 7.2 kB
11 How to perform Descriptive Statistics on Populations and Samples/115 How to calculate Skew and Kurtosis with scipy.stats.en.srt 7.0 kB
12 Common Probability Distributions and how to construct Confidence Intervals/122 The Normal Distribution (Theory).en.srt 7.0 kB
24 Managing Time Series and Financial Data with Pandas/282 Initial Analysis Visualization of Time Series.en.srt 7.0 kB
18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/181 What is the Value-at-Risk (VaR) (Theory).en.srt 7.0 kB
07 How to create great graphs with Matplotlib - Plotting NPV and IRR/067 Customizing Plots (Part 1).en.srt 7.0 kB
17 How to create your own user-defined Functions/172 How to work with Default Arguments.en.srt 6.9 kB
09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/086 Evaluating Annuities with np.fv() - Payout Phase.en.srt 6.8 kB
08 The Numpy Package Working with numbers made easy/075 Changing Elements in Numpy Arrays Mutability.en.srt 6.8 kB
16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/159 How to slice 2-dim Numpy Arrays (Part 1).en.srt 6.8 kB
21 Pandas Intermediate/225 First Steps with Pandas Index Objects.en.srt 6.7 kB
14 How to perform Hypothesis Tests Z-Tests t-Tests Bootstrapping more/152 Hypothesis Testing with Bootstrapping.en.srt 6.7 kB
01 Getting Started/001 Tips How to get the most out of this Course (don t skip).en.srt 6.7 kB
05 100 Python Objects Data Types Operators Functional Programming/036 How to round Floats (and Integers) with round().en.srt 6.7 kB
13 How to estimate Population parameters with Samples - Sampling and Estimation/143 Bootstrapping with Python an alternative method without Statistics.en.srt 6.7 kB
30 Case Study Multi-Factor Models (Fama-French)/370 How to create a Fama-French Five-Factor Model.en.srt 6.7 kB
20 Pandas Basics - Starting from Zero/209 Selecting Rows with loc (label-based indexing).en.srt 6.7 kB
12 Common Probability Distributions and how to construct Confidence Intervals/123 Creating a normally distributed Random Variable.en.srt 6.6 kB
11 How to perform Descriptive Statistics on Populations and Samples/106 Measures of Central Tendency (Theory).en.srt 6.6 kB
07 How to create great graphs with Matplotlib - Plotting NPV and IRR/065 Line Plots.en.srt 6.6 kB
13 How to estimate Population parameters with Samples - Sampling and Estimation/131 Sample Statistic Sampling Error and Sampling Distribution (Theory).en.srt 6.6 kB
17 How to create your own user-defined Functions/178 How to create Nested Functions.en.srt 6.6 kB
19 --- PART 4 MANAGING (FINANCIAL) DATA WITH PANDAS BEYOND EXCEL ---/198 Tabular Data and Pandas DataFrames.en.srt 6.5 kB
03 How to use Python as a Calculator for basic Time Value of Money Problems/013 Introduction to Variables.en.srt 6.5 kB
13 How to estimate Population parameters with Samples - Sampling and Estimation/142 Student s t-Distribution vs. Normal Distribution with scipy.stats.en.srt 6.5 kB
21 Pandas Intermediate/232 nunique() and nlargest() nsmallest() with DataFrames.en.srt 6.5 kB
13 How to estimate Population parameters with Samples - Sampling and Estimation/136 Central Limit Theorem (Coding Part 2).en.srt 6.5 kB
08 The Numpy Package Working with numbers made easy/082 Creating Numpy Arrays from Scratch.en.srt 6.5 kB
16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/165 Arithmetic Vectorized Operations with 2-dim Numpy Arrays.en.srt 6.4 kB
05 100 Python Objects Data Types Operators Functional Programming/037 More on Lists.en.srt 6.4 kB
27 Correlation and Regression/333 How to calculate Covariance and Correlation in Python.en.srt 6.4 kB
17 How to create your own user-defined Functions/175 Sequences as arguments and args.en.srt 6.4 kB
01 Getting Started/002 FAQ Your Questions answered.html 6.4 kB
24 Managing Time Series and Financial Data with Pandas/287 Coding Exercise 10 (Solution).en.srt 6.4 kB
02 ---- PART 1 PYTHON BASICS TIME VALUE OF MONEY AND CAPITAL BUDGETING ----/006 Overview Download of Course Materials for Part 1.en.srt 6.3 kB
20 Pandas Basics - Starting from Zero/207 Slicing Rows and Columns with iloc (position-based indexing).en.srt 6.3 kB
27 Correlation and Regression/334 Correlation and Scatterplots visual Interpretation.en.srt 6.3 kB
08 The Numpy Package Working with numbers made easy/081 Determining a Project s Payback Period with np.where().en.srt 6.3 kB
08 The Numpy Package Working with numbers made easy/077 Numpy Array Methods and Attributes.en.srt 6.3 kB
24 Managing Time Series and Financial Data with Pandas/293 Coding Exercise 11 (Solution).en.srt 6.2 kB
26 --- PART 5 REGRESSION ANALYSIS (A MUST-HAVE FOR MACHINE LEARNING) ---/327 Introduction to Regression Analysis.en.srt 6.2 kB
18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/185 Monte Carlo Simulations for Value-at-Risk - Parametric (Part 1).en.srt 6.2 kB
24 Managing Time Series and Financial Data with Pandas/296 Initial Inspection and Visualization.en.srt 6.2 kB
21 Pandas Intermediate/235 Filtering DataFrames by many Conditions (OR).en.srt 6.0 kB
24 Managing Time Series and Financial Data with Pandas/304 Merging Aligning Financial Time Series (hands-on).en.srt 6.0 kB
06 How to solve for IRR YTM with While Loops and Conditional Statements/057 Calculate a Project s Payback Period.en.srt 5.9 kB
31 Issues in Linear Regression Analysis and Logistic Regression/372 Linear Regression - not that easy.en.srt 5.9 kB
27 Correlation and Regression/340 Case Study (Part 1) The Market Model (Single Factor Model).en.srt 5.9 kB
18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/182 Analyzing the Data past Performance.en.srt 5.9 kB
20 Pandas Basics - Starting from Zero/203 Explore your own Dataset Coding Exercise 1 (Solution).en.srt 5.9 kB
05 100 Python Objects Data Types Operators Functional Programming/045 Mutable vs. immutable Objects (Part 2).en.srt 5.9 kB
31 Issues in Linear Regression Analysis and Logistic Regression/380 Logistic Regression with statsmodels (Part 1).en.srt 5.9 kB
13 How to estimate Population parameters with Samples - Sampling and Estimation/140 Unknown Population Variance - the Standard Case (Example 1).en.srt 5.8 kB
23 Pandas Advanced/268 Manipulating Elements in a DataFrame.en.srt 5.8 kB
04 How to use Lists and For Loops for TVM Problems with many Cashflows/025 The range Object - another Iterable.en.srt 5.8 kB
16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/163 Reshaping and Transposing 2-dim Numpy Arrays.en.srt 5.8 kB
09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/084 Evaluating Investments with np.npv() and np.irr().en.srt 5.8 kB
17 How to create your own user-defined Functions/174 How to unpack Iterables.en.srt 5.8 kB
13 How to estimate Population parameters with Samples - Sampling and Estimation/139 The Student s t-distribution What is it and whywhen do we use it.en.srt 5.8 kB
08 The Numpy Package Working with numbers made easy/076 View vs. copy - potential Pitfalls when slicing Numpy Arrays.en.srt 5.7 kB
24 Managing Time Series and Financial Data with Pandas/302 Financial Time Series - Covariance and Correlation.en.srt 5.7 kB
12 Common Probability Distributions and how to construct Confidence Intervals/117 How to generate Random Numbers with Numpy.en.srt 5.7 kB
08 The Numpy Package Working with numbers made easy/079 Boolean Arrays and Conditional Filtering.en.srt 5.6 kB
05 100 Python Objects Data Types Operators Functional Programming/038 Lists and Element-wise Operations.en.srt 5.6 kB
13 How to estimate Population parameters with Samples - Sampling and Estimation/138 Point Estimates vs. Confidence Interval Estimates (known Population Variance).en.srt 5.6 kB
25 Creating analyzing and optimizing Financial Portfolios with Python/311 What is the Sharpe Ratio and a Risk Free Asset.en.srt 5.6 kB
31 Issues in Linear Regression Analysis and Logistic Regression/375 Non-Linear Relationships - Feature Transformation.en.srt 5.6 kB
16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/162 How to perform row-wise and column-wise Operations.en.srt 5.6 kB
18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/183 How to use the Parametric Method to calculate Value-at-Risk (VaR).en.srt 5.5 kB
13 How to estimate Population parameters with Samples - Sampling and Estimation/133 Sampling Distribution.en.srt 5.0 kB
11 How to perform Descriptive Statistics on Populations and Samples/108 Coding Measures of Central Tendency - Geometric Mean.en.srt 5.0 kB
03 How to use Python as a Calculator for basic Time Value of Money Problems/017 Variables - Dos Don ts and Conventions.en.srt 4.9 kB
21 Pandas Intermediate/228 Renaming Index Column Labels with rename().en.srt 4.9 kB
25 Creating analyzing and optimizing Financial Portfolios with Python/307 Intro.en.srt 4.9 kB
03 How to use Python as a Calculator for basic Time Value of Money Problems/012 Calculate Interest Rates and Returns with Python.en.srt 4.8 kB
12 Common Probability Distributions and how to construct Confidence Intervals/121 Continuous Uniform Distributions.en.srt 4.8 kB
28 OLS Regression ANOVA and Hypothesis Testing/352 Regression Analysis with statsmodels - the Summary Table.en.srt 4.8 kB
08 The Numpy Package Working with numbers made easy/074 Vectorized Operations with Numpy Arrays.en.srt 4.8 kB
21 Pandas Intermediate/237 any() and all().en.srt 4.8 kB
14 How to perform Hypothesis Tests Z-Tests t-Tests Bootstrapping more/148 Calculating and interpreting z-statistic and p-value with scipy.stats.en.srt 4.7 kB
08 The Numpy Package Working with numbers made easy/078 Numpy Universal Functions.en.srt 4.7 kB
31 Issues in Linear Regression Analysis and Logistic Regression/379 Logistic Regression (Theory).en.srt 4.7 kB
28 OLS Regression ANOVA and Hypothesis Testing/350 Hypothesis Testing of Regression Coefficients (Theory).en.srt 4.7 kB
16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/158 2-dimensional Numpy Arrays.en.srt 4.7 kB
28 OLS Regression ANOVA and Hypothesis Testing/351 Hypothesis Testing of Regression Coefficients with statsmodels.en.srt 4.7 kB
16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/166 The keepdims parameter.en.srt 4.6 kB
20 Pandas Basics - Starting from Zero/205 Selecting Rows with Square Brackets (not advisable).en.srt 4.6 kB
11 How to perform Descriptive Statistics on Populations and Samples/104 Visualizing Frequency Distributions with plt.hist().en.srt 4.6 kB
16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/168 Merging and Concatenating Numpy Arrays.en.srt 4.6 kB
16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/164 Creating 2-dim Numpy Arrays from Scratch.en.srt 4.6 kB
16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/167 Adding Removing Elements.en.srt 4.6 kB
16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/161 Recap Changing Elements in a Numpy Array slice.en.srt 4.6 kB
12 Common Probability Distributions and how to construct Confidence Intervals/124 Normal Distribution - Probability Density Function (pdf) with scipy.stats.en.srt 4.6 kB
04 How to use Lists and For Loops for TVM Problems with many Cashflows/020 TVM Problems with many Cashflows.en.srt 4.6 kB
11 How to perform Descriptive Statistics on Populations and Samples/107 Coding Measures of Central Tendency - Mean and Median.en.srt 4.6 kB
13 How to estimate Population parameters with Samples - Sampling and Estimation/137 Central Limit Theorem (Theory).en.srt 4.5 kB
09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/098 Capital Budgeting - Mutually exclusive Projects (Part 3).en.srt 4.4 kB
05 100 Python Objects Data Types Operators Functional Programming/042 Sorting and Reversing Lists.en.srt 4.4 kB
05 100 Python Objects Data Types Operators Functional Programming/031 The Data Type Hierarchy (Theory).en.srt 4.4 kB
12 Common Probability Distributions and how to construct Confidence Intervals/118 Reproducibility with np.random.seed().en.srt 4.4 kB
14 How to perform Hypothesis Tests Z-Tests t-Tests Bootstrapping more/147 What is the p-value (Theory).en.srt 4.4 kB
03 How to use Python as a Calculator for basic Time Value of Money Problems/009 Calculate Future Values (FV) with Python Compounding.en.srt 4.3 kB
27 Correlation and Regression/336 Testing for Correlation (t-Test).en.srt 4.3 kB
21 Pandas Intermediate/244 The agg() method.en.srt 4.3 kB
09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/096 Capital Budgeting - Mutually exclusive Projects (Part 1).en.srt 4.3 kB
11 How to perform Descriptive Statistics on Populations and Samples/112 Percentiles with PythonNumpy.en.srt 4.2 kB
09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/087 How to solve for annuity payments with np.pmt().en.srt 4.2 kB
09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/089 How to calculate the required Contract Value with np.pv().en.srt 4.2 kB
11 How to perform Descriptive Statistics on Populations and Samples/113 Variance and Standard Deviation with PythonNumpy.en.srt 4.1 kB
04 How to use Lists and For Loops for TVM Problems with many Cashflows/023 Indexing Lists.en.srt 3.9 kB
23 Pandas Advanced/266 Adding new Rows (Hands-on).en.srt 3.8 kB
14 How to perform Hypothesis Tests Z-Tests t-Tests Bootstrapping more/151 One-tailed t-Test (unknown Population Variance).en.srt 3.8 kB
12 Common Probability Distributions and how to construct Confidence Intervals/127 Properties of the Standard Normal Distribution (Theory).en.srt 3.8 kB
13 How to estimate Population parameters with Samples - Sampling and Estimation/141 Unknown Population Variance - the Standard Case (Example 2).en.srt 3.7 kB
04 How to use Lists and For Loops for TVM Problems with many Cashflows/028 Calculate an Investment Project s NPV.en.srt 3.7 kB
03 How to use Python as a Calculator for basic Time Value of Money Problems/015 Excursus How to add inline comments.en.srt 3.7 kB
24 Managing Time Series and Financial Data with Pandas/285 More on pd.date_range().en.srt 3.6 kB
29 Multiple Regression Models/358 Coefficient of Determination (Adjusted R squared).en.srt 3.5 kB
09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/088 How to solve for the number of periodic payments with np.nper().en.srt 3.5 kB
05 100 Python Objects Data Types Operators Functional Programming/041 Changing Elements in Lists.en.srt 3.5 kB
15 -- PART 3 ADVANCED PYTHON MONTE CARLO SIMULATIONS AND VALUE AT RISK (VAR) ---/156 Coding Projects Part 3 - Overview.en.srt 3.5 kB
18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/184 How to use the Historical Method to calculate Value-at-Risk (VaR).en.srt 3.4 kB
11 How to perform Descriptive Statistics on Populations and Samples/109 Excursus Why Log Returns are useful.en.srt 3.4 kB
17 How to create your own user-defined Functions/176 How to return many results.en.srt 3.4 kB
06 How to solve for IRR YTM with While Loops and Conditional Statements/062 Solving for a Bond s Yield to Maturity (YTM).en.srt 3.4 kB
27 Correlation and Regression/339 How to interpret Intercept and Slope Coefficient.en.srt 3.4 kB
12 Common Probability Distributions and how to construct Confidence Intervals/125 Normal Distribution - Cumulative Distribution Function (cdf) with scipy.stats.en.srt 3.3 kB
08 The Numpy Package Working with numbers made easy/073 Indexing and Slicing Numpy Arrays.en.srt 3.3 kB
27 Correlation and Regression/337 What is Linear Regression (Theory).en.srt 3.3 kB
31 Issues in Linear Regression Analysis and Logistic Regression/374 Detecting and Handling Outliers (Part 2).en.srt 3.3 kB
32 What s next/382 Get your special BONUS here.html 3.3 kB
09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/095 Calculate PV of equal installments with np.pv() - Valuation of Bonds.en.srt 3.3 kB
04 How to use Lists and For Loops for TVM Problems with many Cashflows/022 Zero-based Indexing and negative Indexing in Python (Theory).en.srt 3.2 kB
13 How to estimate Population parameters with Samples - Sampling and Estimation/134 Standard Error.en.srt 3.2 kB
18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/193 Dynamic path-dependent Simulations (Part 3).en.srt 3.1 kB
03 How to use Python as a Calculator for basic Time Value of Money Problems/010 Calculate Present Values (FV) with Python Discounting.en.srt 3.1 kB
04 How to use Lists and For Loops for TVM Problems with many Cashflows/021 Intro to Python Lists.en.srt 3.0 kB
10 --- PART 2 STATISTICS AND HYPOTHESIS TESTING WITH PYTHON NUMPY AND SCIPY ---/101 Coding Projects Part 2 - Overview.en.srt 2.9 kB
27 Correlation and Regression/341 Case Study (Part 2) The Market Model (Single Factor Model).en.srt 2.9 kB
28 OLS Regression ANOVA and Hypothesis Testing/343 OLS (Ordinary Least Squares) Regression (Theory).en.srt 2.9 kB