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| 001 Tips How to get the most out of this Course (don t skip).en.srt |
6.53Кб |
| 001 Tips How to get the most out of this Course (don t skip).mp4 |
37.57Мб |
| 002 FAQ Your Questions answered.html |
6.24Кб |
| 003 How to download and install Anaconda for Python coding.en.srt |
8.83Кб |
| 003 How to download and install Anaconda for Python coding.mp4 |
71.00Мб |
| 004 Jupyter Notebooks - let s get started.en.srt |
10.88Кб |
| 004 Jupyter Notebooks - let s get started.mp4 |
50.91Мб |
| 005 How to work with Jupyter Notebooks.en.srt |
16.94Кб |
| 005 How to work with Jupyter Notebooks.mp4 |
53.47Мб |
| 006 Course-Materials-Part1.zip |
252.26Кб |
| 006 Overview Download of Course Materials for Part 1.en.srt |
6.18Кб |
| 006 Overview Download of Course Materials for Part 1.mp4 |
30.37Мб |
| 007 Coding Projects Part 1 - Overview.en.srt |
2.18Кб |
| 007 Coding Projects Part 1 - Overview.mp4 |
15.36Мб |
| 007 Python-for-Finance-Projects-Part1.pdf |
512.83Кб |
| 008 Intro to the Time Value of Money (TVM) Concept (Theory).en.srt |
7.48Кб |
| 008 Intro to the Time Value of Money (TVM) Concept (Theory).mp4 |
16.49Мб |
| 008 TVM.pdf |
195.76Кб |
| 009 Calculate Future Values (FV) with Python Compounding.en.srt |
4.21Кб |
| 009 Calculate Future Values (FV) with Python Compounding.mp4 |
12.75Мб |
| 010 Calculate Present Values (FV) with Python Discounting.en.srt |
3.07Кб |
| 010 Calculate Present Values (FV) with Python Discounting.mp4 |
10.06Мб |
| 011 Interest-Rates.pdf |
187.82Кб |
| 011 Interest Rates and Returns (Theory).en.srt |
5.94Кб |
| 011 Interest Rates and Returns (Theory).mp4 |
14.19Мб |
| 012 Calculate Interest Rates and Returns with Python.en.srt |
4.71Кб |
| 012 Calculate Interest Rates and Returns with Python.mp4 |
19.27Мб |
| 013 Introduction to Variables.en.srt |
6.30Кб |
| 013 Introduction to Variables.mp4 |
18.13Мб |
| 014 Variables.pdf |
142.98Кб |
| 014 Variables and Memory (Theory).en.srt |
2.38Кб |
| 014 Variables and Memory (Theory).mp4 |
5.48Мб |
| 015 Excursus How to add inline comments.en.srt |
3.57Кб |
| 015 Excursus How to add inline comments.mp4 |
11.25Мб |
| 016 More on Variables and Memory.en.srt |
8.11Кб |
| 016 More on Variables and Memory.mp4 |
22.22Мб |
| 017 keywords.pdf |
69.44Кб |
| 017 Variables - Dos Don ts and Conventions.en.srt |
4.79Кб |
| 017 Variables - Dos Don ts and Conventions.mp4 |
17.06Мб |
| 018 The print() Function.en.srt |
5.14Кб |
| 018 The print() Function.mp4 |
17.41Мб |
| 019 Coding Exercise 1.en.srt |
11.39Кб |
| 019 Coding Exercise 1.mp4 |
46.86Мб |
| 020 FV-many.pdf |
175.95Кб |
| 020 TVM Problems with many Cashflows.en.srt |
4.46Кб |
| 020 TVM Problems with many Cashflows.mp4 |
10.49Мб |
| 021 Intro to Python Lists.en.srt |
2.88Кб |
| 021 Intro to Python Lists.mp4 |
7.76Мб |
| 022 Indexing.pdf |
122.88Кб |
| 022 Zero-based Indexing and negative Indexing in Python (Theory).en.srt |
3.14Кб |
| 022 Zero-based Indexing and negative Indexing in Python (Theory).mp4 |
7.44Мб |
| 023 Indexing Lists.en.srt |
3.78Кб |
| 023 Indexing Lists.mp4 |
13.86Мб |
| 024 For Loops - Iterating over Lists.en.srt |
9.64Кб |
| 024 For Loops - Iterating over Lists.mp4 |
29.91Мб |
| 025 The range Object - another Iterable.en.srt |
5.67Кб |
| 025 The range Object - another Iterable.mp4 |
17.09Мб |
| 026 Calculate FV and PV for many Cashflows.en.srt |
9.04Кб |
| 026 Calculate FV and PV for many Cashflows.mp4 |
33.53Мб |
| 026 PV-FV-many.pdf |
194.55Кб |
| 027 NPV.pdf |
245.66Кб |
| 027 The Net Present Value - NPV (Theory).en.srt |
9.52Кб |
| 027 The Net Present Value - NPV (Theory).mp4 |
33.29Мб |
| 028 Calculate an Investment Project s NPV.en.srt |
3.61Кб |
| 028 Calculate an Investment Project s NPV.mp4 |
14.34Мб |
| 029 Coding Exercise 2.en.srt |
10.17Кб |
| 029 Coding Exercise 2.mp4 |
37.98Мб |
| 030 Data Types in Action.en.srt |
7.16Кб |
| 030 Data Types in Action.mp4 |
24.34Мб |
| 031 The Data Type Hierarchy (Theory).en.srt |
4.29Кб |
| 031 The Data Type Hierarchy (Theory).mp4 |
10.78Мб |
| 031 Type-Hierarchy.pdf |
162.43Кб |
| 032 Excursus Dynamic Typing in Python.en.srt |
1.97Кб |
| 032 Excursus Dynamic Typing in Python.mp4 |
5.19Мб |
| 033 Build-in Functions.en.srt |
7.42Кб |
| 033 Build-in Functions.mp4 |
25.37Мб |
| 033 Built-in-func.pdf |
92.61Кб |
| 034 Integers.en.srt |
3.83Кб |
| 034 Integers.mp4 |
10.98Мб |
| 035 Floats.en.srt |
7.09Кб |
| 035 Floats.mp4 |
24.33Мб |
| 036 How to round Floats (and Integers) with round().en.srt |
6.53Кб |
| 036 How to round Floats (and Integers) with round().mp4 |
20.91Мб |
| 037 More on Lists.en.srt |
6.28Кб |
| 037 More on Lists.mp4 |
24.60Мб |
| 038 Lists and Element-wise Operations.en.srt |
5.50Кб |
| 038 Lists and Element-wise Operations.mp4 |
17.59Мб |
| 039 Slicing Lists.en.srt |
5.12Кб |
| 039 Slicing Lists.mp4 |
20.12Мб |
| 040 Slicing Cheat Sheet.html |
968б |
| 040 Slicing-cheatsheet.pdf |
105.28Кб |
| 041 Changing Elements in Lists.en.srt |
3.39Кб |
| 041 Changing Elements in Lists.mp4 |
10.11Мб |
| 042 Sorting and Reversing Lists.en.srt |
4.30Кб |
| 042 Sorting and Reversing Lists.mp4 |
13.19Мб |
| 043 Adding and removing Elements fromto Lists.en.srt |
11.67Кб |
| 043 Adding and removing Elements fromto Lists.mp4 |
38.54Мб |
| 044 Mutable vs. immutable Objects (Part 1).en.srt |
10.34Кб |
| 044 Mutable vs. immutable Objects (Part 1).mp4 |
34.49Мб |
| 045 Mutability.pdf |
166.46Кб |
| 045 Mutable vs. immutable Objects (Part 2).en.srt |
5.72Кб |
| 045 Mutable vs. immutable Objects (Part 2).mp4 |
21.85Мб |
| 046 Coding Exercise 3.en.srt |
13.33Кб |
| 046 Coding Exercise 3.mp4 |
53.78Мб |
| 047 Tuples.en.srt |
8.12Кб |
| 047 Tuples.mp4 |
29.78Мб |
| 048 Dictionaries.en.srt |
7.92Кб |
| 048 Dictionaries.mp4 |
31.01Мб |
| 049 Intro to Strings.en.srt |
10.10Кб |
| 049 Intro to Strings.mp4 |
40.84Мб |
| 050 String Replacement.en.srt |
4.93Кб |
| 050 String Replacement.mp4 |
17.30Мб |
| 051 Booleans.en.srt |
2.82Кб |
| 051 Booleans.mp4 |
8.87Мб |
| 052 Operators.pdf |
145.62Кб |
| 052 Operators (Theory).en.srt |
5.34Кб |
| 052 Operators (Theory).mp4 |
11.71Мб |
| 053 Comparison Logical and Membership Operators in Action.en.srt |
9.26Кб |
| 053 Comparison Logical and Membership Operators in Action.mp4 |
35.52Мб |
| 054 Coding Exercise 4.en.srt |
10.63Кб |
| 054 Coding Exercise 4.mp4 |
42.30Мб |
| 055 Conditional Statements.en.srt |
11.11Кб |
| 055 Conditional Statements.mp4 |
38.63Мб |
| 056 Keywords pass continue and break.en.srt |
11.40Кб |
| 056 Keywords pass continue and break.mp4 |
39.40Мб |
| 057 Calculate a Project s Payback Period.en.srt |
5.81Кб |
| 057 Calculate a Project s Payback Period.mp4 |
21.87Мб |
| 058 While Loops.en.srt |
8.75Кб |
| 058 While Loops.mp4 |
35.63Мб |
| 059 IRR.pdf |
243.01Кб |
| 059 The Internal Rate of Return - IRR (Theory).en.srt |
7.10Кб |
| 059 The Internal Rate of Return - IRR (Theory).mp4 |
23.91Мб |
| 060 Solving for a Project s IRR.en.srt |
13.37Кб |
| 060 Solving for a Project s IRR.mp4 |
60.77Мб |
| 061 Bonds and the Yield to Maturity - YTM (Theory).en.srt |
11.82Кб |
| 061 Bonds and the Yield to Maturity - YTM (Theory).mp4 |
36.99Мб |
| 061 Bonds-YTM.pdf |
178.61Кб |
| 062 Solving for a Bond s Yield to Maturity (YTM).en.srt |
3.30Кб |
| 062 Solving for a Bond s Yield to Maturity (YTM).mp4 |
12.53Мб |
| 063 Coding Exercise 5.en.srt |
12.33Кб |
| 063 Coding Exercise 5.mp4 |
55.81Мб |
| 064 Intro.en.srt |
1.70Кб |
| 064 Intro.mp4 |
14.48Мб |
| 065 Line Plots.en.srt |
6.46Кб |
| 065 Line Plots.mp4 |
23.34Мб |
| 066 Scatter Plots.en.srt |
2.39Кб |
| 066 Scatter Plots.mp4 |
7.22Мб |
| 067 Customizing Plots (Part 1).en.srt |
6.79Кб |
| 067 Customizing Plots (Part 1).mp4 |
24.42Мб |
| 068 Customizing Plots (Part 2).en.srt |
12.94Кб |
| 068 Customizing Plots (Part 2).mp4 |
80.42Мб |
| 069 Plotting NPV IRR.en.srt |
10.12Кб |
| 069 Plotting NPV IRR.mp4 |
40.68Мб |
| 070 Coding Exercise 6.html |
1016б |
| 071 Modules Packages and Libraries - No need to reinvent the Wheel.en.srt |
8.89Кб |
| 071 Modules Packages and Libraries - No need to reinvent the Wheel.mp4 |
32.03Мб |
| 072 Numpy Arrays.en.srt |
9.46Кб |
| 072 Numpy Arrays.mp4 |
35.72Мб |
| 073 Indexing and Slicing Numpy Arrays.en.srt |
3.25Кб |
| 073 Indexing and Slicing Numpy Arrays.mp4 |
13.67Мб |
| 074 Vectorized Operations with Numpy Arrays.en.srt |
4.67Кб |
| 074 Vectorized Operations with Numpy Arrays.mp4 |
18.73Мб |
| 075 Changing Elements in Numpy Arrays Mutability.en.srt |
6.61Кб |
| 075 Changing Elements in Numpy Arrays Mutability.mp4 |
24.52Мб |
| 075 Mutability-arrays.pdf |
121.74Кб |
| 076 Slicing-arrays.pdf |
122.52Кб |
| 076 View vs. copy - potential Pitfalls when slicing Numpy Arrays.en.srt |
5.61Кб |
| 076 View vs. copy - potential Pitfalls when slicing Numpy Arrays.mp4 |
19.27Мб |
| 077 Numpy Array Methods and Attributes.en.srt |
6.11Кб |
| 077 Numpy Array Methods and Attributes.mp4 |
21.97Мб |
| 078 Numpy Universal Functions.en.srt |
4.61Кб |
| 078 Numpy Universal Functions.mp4 |
17.77Мб |
| 079 Boolean Arrays and Conditional Filtering.en.srt |
5.51Кб |
| 079 Boolean Arrays and Conditional Filtering.mp4 |
18.14Мб |
| 080 Advanced Filtering Bitwise Operators.en.srt |
7.00Кб |
| 080 Advanced Filtering Bitwise Operators.mp4 |
28.31Мб |
| 081 Determining a Project s Payback Period with np.where().en.srt |
6.14Кб |
| 081 Determining a Project s Payback Period with np.where().mp4 |
22.53Мб |
| 082 Creating Numpy Arrays from Scratch.en.srt |
6.30Кб |
| 082 Creating Numpy Arrays from Scratch.mp4 |
37.86Мб |
| 083 Coding Exercise 7.en.srt |
13.40Кб |
| 083 Coding Exercise 7.mp4 |
73.13Мб |
| 084 Evaluating Investments with np.npv() and np.irr().en.srt |
5.65Кб |
| 084 Evaluating Investments with np.npv() and np.irr().mp4 |
22.24Мб |
| 085 Annuity.pdf |
187.00Кб |
| 085 Evaluating Annuities with np.fv() - Funding Phase.en.srt |
8.84Кб |
| 085 Evaluating Annuities with np.fv() - Funding Phase.mp4 |
32.80Мб |
| 086 Evaluating Annuities with np.fv() - Payout Phase.en.srt |
6.66Кб |
| 086 Evaluating Annuities with np.fv() - Payout Phase.mp4 |
24.40Мб |
| 087 How to solve for annuity payments with np.pmt().en.srt |
4.11Кб |
| 087 How to solve for annuity payments with np.pmt().mp4 |
15.78Мб |
| 088 How to solve for the number of periodic payments with np.nper().en.srt |
3.45Кб |
| 088 How to solve for the number of periodic payments with np.nper().mp4 |
12.70Мб |
| 089 How to calculate the required Contract Value with np.pv().en.srt |
4.08Кб |
| 089 How to calculate the required Contract Value with np.pv().mp4 |
15.27Мб |
| 090 Frequency of compounding and the effective annual interest rate.en.srt |
7.17Кб |
| 090 Frequency of compounding and the effective annual interest rate.mp4 |
21.81Мб |
| 091 How to evaluate a Retirement Plan A-Z.en.srt |
8.79Кб |
| 091 How to evaluate a Retirement Plan A-Z.mp4 |
31.97Мб |
| 092 Retirement Plan Sensitivity Analysis.en.srt |
8.10Кб |
| 092 Retirement Plan Sensitivity Analysis.mp4 |
30.76Мб |
| 093 Mortgage.pdf |
152.86Кб |
| 093 Mortgage Loan Analysis - Debt Sizing.en.srt |
9.30Кб |
| 093 Mortgage Loan Analysis - Debt Sizing.mp4 |
39.07Мб |
| 094 Mortgage Loan Analysis - Interest Payments and Amortization Schedule.en.srt |
13.89Кб |
| 094 Mortgage Loan Analysis - Interest Payments and Amortization Schedule.mp4 |
81.35Мб |
| 095 Calculate PV of equal installments with np.pv() - Valuation of Bonds.en.srt |
3.20Кб |
| 095 Calculate PV of equal installments with np.pv() - Valuation of Bonds.mp4 |
10.15Мб |
| 096 Capital Budgeting - Mutually exclusive Projects (Part 1).en.srt |
4.15Кб |
| 096 Capital Budgeting - Mutually exclusive Projects (Part 1).mp4 |
23.06Мб |
| 097 Capital Budgeting - Mutually exclusive Projects (Part 2).en.srt |
7.11Кб |
| 097 Capital Budgeting - Mutually exclusive Projects (Part 2).mp4 |
40.99Мб |
| 098 Capital-budgeting.pdf |
222.85Кб |
| 098 Capital Budgeting - Mutually exclusive Projects (Part 3).en.srt |
4.31Кб |
| 098 Capital Budgeting - Mutually exclusive Projects (Part 3).mp4 |
18.67Мб |
| 099 Coding Exercise 8.html |
1016б |
| 100 Overview.pdf |
1022.89Кб |
| 100 Statistics - Overview Terms and Vocabulary.en.srt |
15.05Кб |
| 100 Statistics - Overview Terms and Vocabulary.mp4 |
95.73Мб |
| 101 Coding Projects Part 2 - Overview.en.srt |
2.88Кб |
| 101 Coding Projects Part 2 - Overview.mp4 |
21.07Мб |
| 101 Python-for-Finance-Projects-Part2.pdf |
462.83Кб |
| 102 Course-Materials-Part2.zip |
69.13Кб |
| 102 Download of Part 2 Course Materials.en.srt |
5.20Кб |
| 102 Download of Part 2 Course Materials.mp4 |
30.19Мб |
| 103 Population vs. Sample.en.srt |
7.90Кб |
| 103 Population vs. Sample.mp4 |
43.91Мб |
| 104 Visualizing Frequency Distributions with plt.hist().en.srt |
4.50Кб |
| 104 Visualizing Frequency Distributions with plt.hist().mp4 |
22.65Мб |
| 105 Relative and Cumulative Frequencies with plt.hist().en.srt |
5.93Кб |
| 105 Relative and Cumulative Frequencies with plt.hist().mp4 |
36.43Мб |
| 106 Central-tend.pdf |
299.27Кб |
| 106 Measures of Central Tendency (Theory).en.srt |
6.47Кб |
| 106 Measures of Central Tendency (Theory).mp4 |
20.74Мб |
| 107 Coding Measures of Central Tendency - Mean and Median.en.srt |
4.45Кб |
| 107 Coding Measures of Central Tendency - Mean and Median.mp4 |
22.33Мб |
| 108 Coding Measures of Central Tendency - Geometric Mean.en.srt |
4.87Кб |
| 108 Coding Measures of Central Tendency - Geometric Mean.mp4 |
16.56Мб |
| 109 Excursus Why Log Returns are useful.en.srt |
3.32Кб |
| 109 Excursus Why Log Returns are useful.mp4 |
12.40Мб |
| 110 Dispersion.pdf |
298.92Кб |
| 110 Variability around the Central Tendency Dispersion (Theory).en.srt |
7.83Кб |
| 110 Variability around the Central Tendency Dispersion (Theory).mp4 |
27.68Мб |
| 111 Minimum Maximum and Range with PythonNumpy.en.srt |
2.48Кб |
| 111 Minimum Maximum and Range with PythonNumpy.mp4 |
12.30Мб |
| 112 Percentiles with PythonNumpy.en.srt |
4.11Кб |
| 112 Percentiles with PythonNumpy.mp4 |
17.57Мб |
| 113 Variance and Standard Deviation with PythonNumpy.en.srt |
4.00Кб |
| 113 Variance and Standard Deviation with PythonNumpy.mp4 |
16.35Мб |
| 114 Skew and Kurtosis (Theory).en.srt |
5.24Кб |
| 114 Skew and Kurtosis (Theory).mp4 |
18.03Мб |
| 114 skew-kurtosis.pdf |
425.14Кб |
| 115 How to calculate Skew and Kurtosis with scipy.stats.en.srt |
6.86Кб |
| 115 How to calculate Skew and Kurtosis with scipy.stats.mp4 |
27.45Мб |
| 116 Coding Exercise 1.html |
1016б |
| 117 How to generate Random Numbers with Numpy.en.srt |
5.52Кб |
| 117 How to generate Random Numbers with Numpy.mp4 |
25.19Мб |
| 118 Reproducibility with np.random.seed().en.srt |
4.28Кб |
| 118 Reproducibility with np.random.seed().mp4 |
17.25Мб |
| 119 Probability Distributions - Overview.en.srt |
7.91Кб |
| 119 Probability Distributions - Overview.mp4 |
35.68Мб |
| 119 Prob-distr.pdf |
477.98Кб |
| 120 Discrete Uniform Distributions.en.srt |
7.06Кб |
| 120 Discrete Uniform Distributions.mp4 |
28.20Мб |
| 121 Continuous Uniform Distributions.en.srt |
4.70Кб |
| 121 Continuous Uniform Distributions.mp4 |
20.11Мб |
| 122 Normal.pdf |
412.36Кб |
| 122 The Normal Distribution (Theory).en.srt |
6.83Кб |
| 122 The Normal Distribution (Theory).mp4 |
18.43Мб |
| 123 Creating a normally distributed Random Variable.en.srt |
6.48Кб |
| 123 Creating a normally distributed Random Variable.mp4 |
24.11Мб |
| 124 Normal Distribution - Probability Density Function (pdf) with scipy.stats.en.srt |
4.46Кб |
| 124 Normal Distribution - Probability Density Function (pdf) with scipy.stats.mp4 |
26.92Мб |
| 125 Normal Distribution - Cumulative Distribution Function (cdf) with scipy.stats.en.srt |
3.25Кб |
| 125 Normal Distribution - Cumulative Distribution Function (cdf) with scipy.stats.mp4 |
15.38Мб |
| 126 The Standard Normal Distribution and Z-Values.en.srt |
7.41Кб |
| 126 The Standard Normal Distribution and Z-Values.mp4 |
38.63Мб |
| 127 Properties of the Standard Normal Distribution (Theory).en.srt |
3.70Кб |
| 127 Properties of the Standard Normal Distribution (Theory).mp4 |
14.84Мб |
| 127 standard-normal.pdf |
393.93Кб |
| 128 Probabilities and Z-Values with scipy.stats.en.srt |
12.74Кб |
| 128 Probabilities and Z-Values with scipy.stats.mp4 |
59.27Мб |
| 129 Confidence Intervals with scipy.stats.en.srt |
8.46Кб |
| 129 Confidence Intervals with scipy.stats.mp4 |
48.12Мб |
| 130 Coding Exercise 2.html |
1016б |
| 131 Sample Statistic Sampling Error and Sampling Distribution (Theory).en.srt |
6.45Кб |
| 131 Sample Statistic Sampling Error and Sampling Distribution (Theory).mp4 |
33.91Мб |
| 131 Sampling.pdf |
773.80Кб |
| 132 Sampling with np.random.choice().en.srt |
5.06Кб |
| 132 Sampling with np.random.choice().mp4 |
20.64Мб |
| 133 Sampling Distribution.en.srt |
4.90Кб |
| 133 Sampling Distribution.mp4 |
21.58Мб |
| 134 Standard Error.en.srt |
3.08Кб |
| 134 Standard Error.mp4 |
10.65Мб |
| 135 Central Limit Theorem (Coding Part 1).en.srt |
4.99Кб |
| 135 Central Limit Theorem (Coding Part 1).mp4 |
26.30Мб |
| 136 Central Limit Theorem (Coding Part 2).en.srt |
6.30Кб |
| 136 Central Limit Theorem (Coding Part 2).mp4 |
30.34Мб |
| 137 central-limit-th.pdf |
341.14Кб |
| 137 Central Limit Theorem (Theory).en.srt |
4.42Кб |
| 137 Central Limit Theorem (Theory).mp4 |
16.98Мб |
| 138 Point Estimates vs. Confidence Interval Estimates (known Population Variance).en.srt |
5.48Кб |
| 138 Point Estimates vs. Confidence Interval Estimates (known Population Variance).mp4 |
23.42Мб |
| 139 studentsT.pdf |
569.17Кб |
| 139 The Student s t-distribution What is it and whywhen do we use it.en.srt |
5.63Кб |
| 139 The Student s t-distribution What is it and whywhen do we use it.mp4 |
20.14Мб |
| 140 Unknown Population Variance - the Standard Case (Example 1).en.srt |
5.67Кб |
| 140 Unknown Population Variance - the Standard Case (Example 1).mp4 |
26.34Мб |
| 141 Unknown Population Variance - the Standard Case (Example 2).en.srt |
3.63Кб |
| 141 Unknown Population Variance - the Standard Case (Example 2).mp4 |
17.80Мб |
| 142 Student s t-Distribution vs. Normal Distribution with scipy.stats.en.srt |
6.30Кб |
| 142 Student s t-Distribution vs. Normal Distribution with scipy.stats.mp4 |
29.63Мб |
| 143 Bootstrapping with Python an alternative method without Statistics.en.srt |
6.53Кб |
| 143 Bootstrapping with Python an alternative method without Statistics.mp4 |
28.05Мб |
| 144 Coding Exercise 3.html |
1016б |
| 145 Hypothesis.pdf |
507.37Кб |
| 145 Hypothesis Testing (Theory).en.srt |
12.59Кб |
| 145 Hypothesis Testing (Theory).mp4 |
50.95Мб |
| 146 Two-tailed Z-Test with known Population Variance.en.srt |
11.40Кб |
| 146 Two-tailed Z-Test with known Population Variance.mp4 |
52.74Мб |
| 147 p-value.pdf |
345.54Кб |
| 147 What is the p-value (Theory).en.srt |
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| 147 What is the p-value (Theory).mp4 |
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| 148 Calculating and interpreting z-statistic and p-value with scipy.stats.en.srt |
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| 148 Calculating and interpreting z-statistic and p-value with scipy.stats.mp4 |
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| 149 One-tailed Z-Test with known Population Variance.en.srt |
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| 149 One-tailed Z-Test with known Population Variance.mp4 |
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| 150 Two-tailed t-Test (unknown Population Variance).en.srt |
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| 150 Two-tailed t-Test (unknown Population Variance).mp4 |
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| 151 One-tailed t-Test (unknown Population Variance).en.srt |
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| 151 One-tailed t-Test (unknown Population Variance).mp4 |
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| 152 Hypothesis Testing with Bootstrapping.en.srt |
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| 152 Hypothesis Testing with Bootstrapping.mp4 |
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| 153 Testing for Normality of Financial Returns with scipy.stats.en.srt |
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| 153 Testing for Normality of Financial Returns with scipy.stats.mp4 |
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| 154 Coding Exercise 4.html |
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| 155 Course-Materials-Part3.zip |
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| 155 Overview Download of Course Materials for Part 3.en.srt |
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| 155 Overview Download of Course Materials for Part 3.mp4 |
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| 156 Coding-Projects-Part3.pdf |
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| 156 Coding Projects Part 3 - Overview.en.srt |
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| 156 Coding Projects Part 3 - Overview.mp4 |
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| 157 How to work with nested Lists.en.srt |
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| 157 How to work with nested Lists.mp4 |
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| 158 2-dimensional Numpy Arrays.en.srt |
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| 158 2-dimensional Numpy Arrays.mp4 |
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| 159 How to slice 2-dim Numpy Arrays (Part 1).en.srt |
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| 159 How to slice 2-dim Numpy Arrays (Part 1).mp4 |
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| 160 How to slice 2-dim Numpy Arrays (Part 2).en.srt |
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| 160 How to slice 2-dim Numpy Arrays (Part 2).mp4 |
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| 161 Recap Changing Elements in a Numpy Array slice.en.srt |
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| 161 Recap Changing Elements in a Numpy Array slice.mp4 |
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| 162 How to perform row-wise and column-wise Operations.en.srt |
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| 162 How to perform row-wise and column-wise Operations.mp4 |
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| 163 Reshaping and Transposing 2-dim Numpy Arrays.en.srt |
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| 163 Reshaping and Transposing 2-dim Numpy Arrays.mp4 |
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| 164 Creating 2-dim Numpy Arrays from Scratch.en.srt |
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| 164 Creating 2-dim Numpy Arrays from Scratch.mp4 |
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| 165 Arithmetic Vectorized Operations with 2-dim Numpy Arrays.en.srt |
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| 165 Arithmetic Vectorized Operations with 2-dim Numpy Arrays.mp4 |
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| 166 The keepdims parameter.en.srt |
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| 166 The keepdims parameter.mp4 |
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| 167 Adding Removing Elements.en.srt |
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| 167 Adding Removing Elements.mp4 |
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| 168 Merging and Concatenating Numpy Arrays.en.srt |
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| 168 Merging and Concatenating Numpy Arrays.mp4 |
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| 169 Coding Exercise 1.html |
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| 170 Defining your first user-defined Function.en.srt |
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| 170 Defining your first user-defined Function.mp4 |
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| 171 What s the difference between Positional Arguments vs. Keyword Arguments.en.srt |
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| 171 What s the difference between Positional Arguments vs. Keyword Arguments.mp4 |
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| 172 How to work with Default Arguments.en.srt |
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| 172 How to work with Default Arguments.mp4 |
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| 173 The Default Argument None.en.srt |
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| 173 The Default Argument None.mp4 |
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| 174 How to unpack Iterables.en.srt |
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| 174 How to unpack Iterables.mp4 |
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| 175 Sequences as arguments and args.en.srt |
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| 175 Sequences as arguments and args.mp4 |
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| 176 How to return many results.en.srt |
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| 176 How to return many results.mp4 |
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| 177 Scope - easily explained.en.srt |
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| 177 Scope - easily explained.mp4 |
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| 178 How to create Nested Functions.en.srt |
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| 178 How to create Nested Functions.mp4 |
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| 179 Putting it all together - Case Study.en.srt |
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| 179 Putting it all together - Case Study.mp4 |
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| 180 Coding Exercise 2.html |
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| 181 Value-at-Risk.pdf |
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| 181 What is the Value-at-Risk (VaR) (Theory).en.srt |
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| 181 What is the Value-at-Risk (VaR) (Theory).mp4 |
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| 182 Analyzing the Data past Performance.en.srt |
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| 182 Analyzing the Data past Performance.mp4 |
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| 183 How to use the Parametric Method to calculate Value-at-Risk (VaR).en.srt |
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| 183 How to use the Parametric Method to calculate Value-at-Risk (VaR).mp4 |
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| 184 How to use the Historical Method to calculate Value-at-Risk (VaR).en.srt |
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| 184 How to use the Historical Method to calculate Value-at-Risk (VaR).mp4 |
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| 185 Monte Carlo Simulations for Value-at-Risk - Parametric (Part 1).en.srt |
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| 185 Monte Carlo Simulations for Value-at-Risk - Parametric (Part 1).mp4 |
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| 186 Monte Carlo Simulations for Value-at-Risk - Parametric (Part 2).en.srt |
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| 186 Monte Carlo Simulations for Value-at-Risk - Parametric (Part 2).mp4 |
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| 187 Monte Carlo Simulations for Value-at-Risk - Parametric (Part 3).en.srt |
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| 187 Monte Carlo Simulations for Value-at-Risk - Parametric (Part 3).mp4 |
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| 188 Monte Carlo Simulations for Value-at-Risk - Bootstrapping (Part 1).en.srt |
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| 188 Monte Carlo Simulations for Value-at-Risk - Bootstrapping (Part 1).mp4 |
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| 189 Monte Carlo Simulations for Value-at-Risk - Bootstrapping (Part 2).en.srt |
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| 189 Monte Carlo Simulations for Value-at-Risk - Bootstrapping (Part 2).mp4 |
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| 190 Conditional Value-at-Risk (CVaR).en.srt |
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| 190 Conditional Value-at-Risk (CVaR).mp4 |
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| 190 CVaR.pdf |
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| 191 Dynamic path-dependent Simulations (Part 1).en.srt |
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| 191 Dynamic path-dependent Simulations (Part 1).mp4 |
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| 192 Dynamic path-dependent Simulations (Part 2).en.srt |
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| 192 Dynamic path-dependent Simulations (Part 2).mp4 |
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| 193 Dynamic path-dependent Simulations (Part 3).en.srt |
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| 193 Dynamic path-dependent Simulations (Part 3).mp4 |
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| 194 Dynamic path-dependent Simulations (Part 4).en.srt |
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| 194 Dynamic path-dependent Simulations (Part 4).mp4 |
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| 195 Coding Exercise 3.html |
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| 196 Introduction.en.srt |
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| 196 Introduction.mp4 |
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| 197 Course-Materials-Part4.zip |
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| 197 Download of Part 4 Course Materials.en.srt |
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| 197 Download of Part 4 Course Materials.mp4 |
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| 198 Tabular Data and Pandas DataFrames.en.srt |
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| 198 Tabular Data and Pandas DataFrames.mp4 |
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| 199 First Steps (Inspection of Data Part 1).en.srt |
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| 199 First Steps (Inspection of Data Part 1).mp4 |
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| 200 First Steps (Inspection of Data Part 2).en.srt |
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| 200 First Steps (Inspection of Data Part 2).mp4 |
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| 201 Built-in Functions Attributes and Methods.en.srt |
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| 201 Built-in Functions Attributes and Methods.mp4 |
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| 202 Explore your own Dataset Coding Exercise 1 (Intro).html |
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| 203 Explore your own Dataset Coding Exercise 1 (Solution).en.srt |
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| 203 Explore your own Dataset Coding Exercise 1 (Solution).mp4 |
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| 204 Selecting Columns.en.srt |
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| 204 Selecting Columns.mp4 |
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| 205 Selecting Rows with Square Brackets (not advisable).en.srt |
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| 205 Selecting Rows with Square Brackets (not advisable).mp4 |
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| 206 Selecting Rows with iloc (position-based indexing).en.srt |
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| 206 Selecting Rows with iloc (position-based indexing).mp4 |
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| 207 Slicing Rows and Columns with iloc (position-based indexing).en.srt |
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| 207 Slicing Rows and Columns with iloc (position-based indexing).mp4 |
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| 208 pandas-iloc.pdf |
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| 208 Position-based Indexing Cheat Sheets.html |
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| 209 Selecting Rows with loc (label-based indexing).en.srt |
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| 209 Selecting Rows with loc (label-based indexing).mp4 |
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| 210 Slicing Rows and Columns with loc (label-based indexing).en.srt |
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| 210 Slicing Rows and Columns with loc (label-based indexing).mp4 |
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| 211 Label-based Indexing Cheat Sheets.html |
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| 211 Pandas-loc.pdf |
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| 212 Summary and Outlook.en.srt |
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| 212 Summary and Outlook.mp4 |
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| 213 Coding Exercise 2 (Intro).html |
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| 214 Coding Exercise 2 (Solution).en.srt |
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| 214 Coding Exercise 2 (Solution).mp4 |
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| 215 Intro.html |
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| 216 First Steps with Pandas Series.en.srt |
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| 216 First Steps with Pandas Series.mp4 |
30.45Мб |
| 217 Analyzing Numerical Series with unique() nunique() and value_counts().en.srt |
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| 217 Analyzing Numerical Series with unique() nunique() and value_counts().mp4 |
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| 218 UPDATE Pandas Version 0.24.0 (Jan E9).html |
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| 219 EXCURSUS Updating Pandas Anaconda.en.srt |
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| 219 EXCURSUS Updating Pandas Anaconda.mp4 |
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| 220 Analyzing non-numerical Series with unique() nunique() value_counts().en.srt |
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| 220 Analyzing non-numerical Series with unique() nunique() value_counts().mp4 |
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| 221 The copy() method.en.srt |
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| 221 The copy() method.mp4 |
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| 222 Sorting of Series and Introduction to the inplace - parameter.en.srt |
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| 222 Sorting of Series and Introduction to the inplace - parameter.mp4 |
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| 223 Coding Exercise 3 (Intro).html |
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| 224 Coding Exercise 3 (Solution).en.srt |
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| 224 Coding Exercise 3 (Solution).mp4 |
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| 225 First Steps with Pandas Index Objects.en.srt |
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| 225 First Steps with Pandas Index Objects.mp4 |
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| 226 Changing Row Index with set_index() and reset_index().en.srt |
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| 226 Changing Row Index with set_index() and reset_index().mp4 |
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| 227 Changing Column Labels.en.srt |
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| 227 Changing Column Labels.mp4 |
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| 228 Renaming Index Column Labels with rename().en.srt |
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| 228 Renaming Index Column Labels with rename().mp4 |
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| 229 Coding Exercise 4 (Intro).html |
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| 230 Coding Exercise 4 (Solution).en.srt |
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| 230 Coding Exercise 4 (Solution).mp4 |
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| 231 Sorting DataFrames with sort_index() and sort_values().en.srt |
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| 231 Sorting DataFrames with sort_index() and sort_values().mp4 |
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| 232 nunique() and nlargest() nsmallest() with DataFrames.en.srt |
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| 232 nunique() and nlargest() nsmallest() with DataFrames.mp4 |
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| 233 Filtering DataFrames (one Condition).en.srt |
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| 233 Filtering DataFrames (one Condition).mp4 |
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| 234 Filtering DataFrames by many Conditions (AND).en.srt |
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| 234 Filtering DataFrames by many Conditions (AND).mp4 |
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| 235 Filtering DataFrames by many Conditions (OR).en.srt |
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| 235 Filtering DataFrames by many Conditions (OR).mp4 |
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| 236 Advanced Filtering with between() isin() and ~.en.srt |
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| 236 Advanced Filtering with between() isin() and ~.mp4 |
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| 237 any() and all().en.srt |
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| 237 any() and all().mp4 |
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| 238 Coding Exercise 5 (Intro).html |
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| 239 Coding Exercise 5 (Solution).en.srt |
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| 239 Coding Exercise 5 (Solution).mp4 |
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| 240 Intro to NA Values missing Values.en.srt |
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| 240 Intro to NA Values missing Values.mp4 |
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| 241 Handling NA Values missing Values.en.srt |
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| 241 Handling NA Values missing Values.mp4 |
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| 242 Exporting DataFrames to csv.en.srt |
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| 242 Exporting DataFrames to csv.mp4 |
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| 243 Summary Statistics and Accumulations.en.srt |
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| 243 Summary Statistics and Accumulations.mp4 |
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| 244 The agg() method.en.srt |
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| 244 The agg() method.mp4 |
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| 245 Coding Exercise 6 (Intro).html |
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| 246 Coding Exercise 6 (Solution).en.srt |
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| 246 Coding Exercise 6 (Solution).mp4 |
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| 247 Intro.html |
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| 248 Visualization with Matplotlib (Intro).en.srt |
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| 248 Visualization with Matplotlib (Intro).mp4 |
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| 249 Customization of Plots.en.srt |
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| 249 Customization of Plots.mp4 |
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| 250 Histogramms (Part 1).en.srt |
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| 250 Histogramms (Part 1).mp4 |
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| 251 Histogramms (Part 2).en.srt |
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| 251 Histogramms (Part 2).mp4 |
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| 252 Scatterplots.en.srt |
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| 252 Scatterplots.mp4 |
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| 253 First Steps with Seaborn.en.srt |
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| 253 First Steps with Seaborn.mp4 |
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| 254 Categorical Seaborn Plots.en.srt |
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| 254 Categorical Seaborn Plots.mp4 |
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| 255 Seaborn Regression Plots.en.srt |
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| 255 Seaborn Regression Plots.mp4 |
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| 256 Seaborn Heatmaps.en.srt |
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| 256 Seaborn Heatmaps.mp4 |
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| 257 Coding Exercise 7 (Intro).html |
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| 258 Coding Exercise 7 (Solution).en.srt |
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| 258 Coding Exercise 7 (Solution).mp4 |
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| 259 Intro.html |
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| 260 Removing Columns.en.srt |
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| 260 Removing Columns.mp4 |
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| 261 Removing Rows.en.srt |
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| 261 Removing Rows.mp4 |
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| 262 Adding new Columns to a DataFrame.en.srt |
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| 262 Adding new Columns to a DataFrame.mp4 |
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| 263 Arithmetic Operations (Part 1).en.srt |
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| 263 Arithmetic Operations (Part 1).mp4 |
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| 264 Arithmetic Operations (Part 2).en.srt |
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| 264 Arithmetic Operations (Part 2).mp4 |
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| 265 Creating DataFrames from Scratch with pd.DataFrame().en.srt |
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| 265 Creating DataFrames from Scratch with pd.DataFrame().mp4 |
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| 266 Adding new Rows (Hands-on).en.srt |
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| 266 Adding new Rows (Hands-on).mp4 |
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| 267 Adding new Rows to a DataFrame.en.srt |
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| 267 Adding new Rows to a DataFrame.mp4 |
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| 268 Manipulating Elements in a DataFrame.en.srt |
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| 268 Manipulating Elements in a DataFrame.mp4 |
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| 269 Coding Exercise 8 (Intro).html |
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| 270 Coding Exercise 8 (Solution).en.srt |
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| 270 Coding Exercise 8 (Solution).mp4 |
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| 271 Introduction to GroupBy Operations.en.srt |
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| 271 Introduction to GroupBy Operations.mp4 |
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| 272 Understanding the GroupBy Object.en.srt |
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| 272 Understanding the GroupBy Object.mp4 |
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| 273 Splitting with many Keys.en.srt |
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| 273 Splitting with many Keys.mp4 |
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| 274 split-apply-combine.en.srt |
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| 274 split-apply-combine.mp4 |
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| 275 split-apply-combine applied.en.srt |
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| 275 split-apply-combine applied.mp4 |
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| 276 Hierarchical Indexing with Groupby.en.srt |
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| 276 Hierarchical Indexing with Groupby.mp4 |
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| 277 stack() and unstack().en.srt |
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| 277 stack() and unstack().mp4 |
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| 278 Coding Exercise 9 (Intro).html |
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| 279 Coding Exercise 9 (Solution).en.srt |
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| 279 Coding Exercise 9 (Solution).mp4 |
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| 280 Importing Time Series Data from csv-files.en.srt |
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| 280 Importing Time Series Data from csv-files.mp4 |
34.41Мб |
| 281 Converting strings to datetime objects with pd.to_datetime().en.srt |
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| 281 Converting strings to datetime objects with pd.to_datetime().mp4 |
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| 282 Initial Analysis Visualization of Time Series.en.srt |
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| 282 Initial Analysis Visualization of Time Series.mp4 |
28.93Мб |
| 283 Indexing and Slicing Time Series.en.srt |
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| 283 Indexing and Slicing Time Series.mp4 |
40.63Мб |
| 284 Creating a customized DatetimeIndex with pd.date_range().en.srt |
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| 284 Creating a customized DatetimeIndex with pd.date_range().mp4 |
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| 285 More on pd.date_range().en.srt |
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| 285 More on pd.date_range().mp4 |
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| 286 Coding Exercise 10 (intro).html |
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| 287 Coding Exercise 10 (Solution).en.srt |
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| 287 Coding Exercise 10 (Solution).mp4 |
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| 288 Downsampling Time Series with resample() (Part 1).en.srt |
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| 288 Downsampling Time Series with resample() (Part 1).mp4 |
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| 289 Downsampling Time Series with resample (Part 2).en.srt |
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| 289 Downsampling Time Series with resample (Part 2).mp4 |
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| 290 The PeriodIndex object.en.srt |
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| 290 The PeriodIndex object.mp4 |
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| 291 Advanced Indexing with reindex().en.srt |
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| 291 Advanced Indexing with reindex().mp4 |
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| 292 Coding Exercise 11 (intro).html |
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| 293 Coding Exercise 11 (Solution).en.srt |
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| 293 Coding Exercise 11 (Solution).mp4 |
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| 294 Getting Ready (Installing required library).en.srt |
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| 294 Getting Ready (Installing required library).mp4 |
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| 295 Importing Stock Price Data from Yahoo Finance (it still works).en.srt |
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| 295 Importing Stock Price Data from Yahoo Finance (it still works).mp4 |
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| 296 Initial Inspection and Visualization.en.srt |
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| 296 Initial Inspection and Visualization.mp4 |
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| 297 Normalizing Time Series to a Base Value (100).en.srt |
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| 297 Normalizing Time Series to a Base Value (100).mp4 |
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| 298 The shift() method.en.srt |
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| 298 The shift() method.mp4 |
29.49Мб |
| 299 The methods diff() and pct_change().en.srt |
8.38Кб |
| 299 The methods diff() and pct_change().mp4 |
32.72Мб |
| 300 Measuring Stock Performance with MEAN Returns and STD of Returns.en.srt |
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| 300 Measuring Stock Performance with MEAN Returns and STD of Returns.mp4 |
34.87Мб |
| 301 Financial Time Series - Return and Risk.en.srt |
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| 301 Financial Time Series - Return and Risk.mp4 |
44.90Мб |
| 302 Financial Time Series - Covariance and Correlation.en.srt |
5.55Кб |
| 302 Financial Time Series - Covariance and Correlation.mp4 |
21.04Мб |
| 303 Importing Financial Data from Excel.en.srt |
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| 303 Importing Financial Data from Excel.mp4 |
77.87Мб |
| 304 Merging Aligning Financial Time Series (hands-on).en.srt |
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| 304 Merging Aligning Financial Time Series (hands-on).mp4 |
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| 305 Coding Exercise 12 (intro).html |
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| 306 Coding Exercise 12 (Solution).en.srt |
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| 306 Coding Exercise 12 (Solution).mp4 |
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| 307 Intro.en.srt |
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| 307 Intro.mp4 |
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| 308 Getting the Data.en.srt |
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| 308 Getting the Data.mp4 |
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| 309 Creating the equally-weighted Portfolio.en.srt |
9.87Кб |
| 309 Creating the equally-weighted Portfolio.mp4 |
45.78Мб |
| 310 Creating many random Portfolios with Python.en.srt |
13.51Кб |
| 310 Creating many random Portfolios with Python.mp4 |
72.48Мб |
| 311 What is the Sharpe Ratio and a Risk Free Asset.en.srt |
5.43Кб |
| 311 What is the Sharpe Ratio and a Risk Free Asset.mp4 |
16.87Мб |
| 312 Portfolio Analysis and the Sharpe Ratio with Python.en.srt |
8.25Кб |
| 312 Portfolio Analysis and the Sharpe Ratio with Python.mp4 |
44.86Мб |
| 313 Finding the Optimal Portfolio.en.srt |
8.37Кб |
| 313 Finding the Optimal Portfolio.mp4 |
39.05Мб |
| 314 Sharpe Ratio - visualized and explained.en.srt |
6.00Кб |
| 314 Sharpe Ratio - visualized and explained.mp4 |
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| 315 Coding Exercise 13 (Intro).html |
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| 316 Coding Exercise 13 (Solution).en.srt |
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| 316 Coding Exercise 13 (Solution).mp4 |
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| 317 Intro CAPM.en.srt |
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| 317 Intro CAPM.mp4 |
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| 318 Capital Market Line (CML) Two-Fund-Theorem.en.srt |
3.95Кб |
| 318 Capital Market Line (CML) Two-Fund-Theorem.mp4 |
15.81Мб |
| 319 The Portfolio Diversification Effect.en.srt |
15.09Кб |
| 319 The Portfolio Diversification Effect.mp4 |
70.99Мб |
| 320 Systematic vs. unsystematic Risk.en.srt |
14.18Кб |
| 320 Systematic vs. unsystematic Risk.mp4 |
59.51Мб |
| 321 Capital Asset Pricing Model (CAPM) Security Market Line (SLM).en.srt |
8.68Кб |
| 321 Capital Asset Pricing Model (CAPM) Security Market Line (SLM).mp4 |
39.19Мб |
| 322 Beta and Alpha.en.srt |
8.75Кб |
| 322 Beta and Alpha.mp4 |
33.60Мб |
| 323 Redefining the Market Portfolio.en.srt |
8.59Кб |
| 323 Redefining the Market Portfolio.mp4 |
36.67Мб |
| 324 Cyclical vs. non-cyclical Stocks - another Intuition on Beta.en.srt |
7.47Кб |
| 324 Cyclical vs. non-cyclical Stocks - another Intuition on Beta.mp4 |
32.71Мб |
| 325 Coding Exercise 14 (Intro).html |
1.00Кб |
| 326 Coding Exercise 14 (Solution).en.srt |
10.26Кб |
| 326 Coding Exercise 14 (Solution).mp4 |
59.21Мб |
| 327 Introduction to Regression Analysis.en.srt |
6.06Кб |
| 327 Introduction to Regression Analysis.mp4 |
50.63Мб |
| 328 Coding-Projects-Part5.pdf |
636.64Кб |
| 328 Coding Projects Part 5 - Overview.en.srt |
2.79Кб |
| 328 Coding Projects Part 5 - Overview.mp4 |
16.49Мб |
| 329 Course-Materials-Part5.zip |
25.69Мб |
| 329 Download of Part 5 Course Materials.html |
995б |
| 330 Cleaning and preparing the Data - Movies Database (Part 1).en.srt |
7.59Кб |
| 330 Cleaning and preparing the Data - Movies Database (Part 1).mp4 |
47.03Мб |
| 331 Cleaning and preparing the Data - Movies Database (Part 2).en.srt |
7.07Кб |
| 331 Cleaning and preparing the Data - Movies Database (Part 2).mp4 |
31.12Мб |
| 332 Covariance and Correlation Coefficient (Theory).en.srt |
8.79Кб |
| 332 Covariance and Correlation Coefficient (Theory).mp4 |
27.58Мб |
| 332 Cov-Corr.pdf |
228.13Кб |
| 333 How to calculate Covariance and Correlation in Python.en.srt |
6.28Кб |
| 333 How to calculate Covariance and Correlation in Python.mp4 |
23.98Мб |
| 334 Correlation and Scatterplots visual Interpretation.en.srt |
6.15Кб |
| 334 Correlation and Scatterplots visual Interpretation.mp4 |
20.00Мб |
| 334 Visual.pdf |
118.59Кб |
| 335 Creating a Confidence Interval for the Correlation Coefficient (Bootstrapping).en.srt |
9.05Кб |
| 335 Creating a Confidence Interval for the Correlation Coefficient (Bootstrapping).mp4 |
38.94Мб |
| 336 Testing for Correlation (t-Test).en.srt |
4.17Кб |
| 336 Testing for Correlation (t-Test).mp4 |
16.57Мб |
| 337 Regression.pdf |
150.15Кб |
| 337 What is Linear Regression (Theory).en.srt |
3.25Кб |
| 337 What is Linear Regression (Theory).mp4 |
11.64Мб |
| 338 A simple Linear Regression Model with numpy Scipy.en.srt |
7.90Кб |
| 338 A simple Linear Regression Model with numpy Scipy.mp4 |
39.72Мб |
| 339 Coeff.pdf |
177.70Кб |
| 339 How to interpret Intercept and Slope Coefficient.en.srt |
3.29Кб |
| 339 How to interpret Intercept and Slope Coefficient.mp4 |
12.33Мб |
| 340 Case Study (Part 1) The Market Model (Single Factor Model).en.srt |
5.77Кб |
| 340 Case Study (Part 1) The Market Model (Single Factor Model).mp4 |
26.32Мб |
| 341 Case Study (Part 2) The Market Model (Single Factor Model).en.srt |
2.87Кб |
| 341 Case Study (Part 2) The Market Model (Single Factor Model).mp4 |
10.31Мб |
| 342 Coding Exercise 1.html |
1016б |
| 343 OLS.pdf |
147.82Кб |
| 343 OLS (Ordinary Least Squares) Regression (Theory).en.srt |
2.85Кб |
| 343 OLS (Ordinary Least Squares) Regression (Theory).mp4 |
7.26Мб |
| 344 OLS Regression with statsmodels - Intro.en.srt |
11.45Кб |
| 344 OLS Regression with statsmodels - Intro.mp4 |
48.78Мб |
| 345 ANOVA.pdf |
267.08Кб |
| 345 OLS Regression - ANOVA (Theory).en.srt |
10.71Кб |
| 345 OLS Regression - ANOVA (Theory).mp4 |
36.35Мб |
| 346 OLS Regression with Statsmodels - ANOVA.en.srt |
3.87Кб |
| 346 OLS Regression with Statsmodels - ANOVA.mp4 |
17.82Мб |
| 347 Coefficient of Determination (R squared).en.srt |
2.28Кб |
| 347 Coefficient of Determination (R squared).mp4 |
6.88Мб |
| 348 OLS Regression with statsmodels and DataFrames.en.srt |
5.06Кб |
| 348 OLS Regression with statsmodels and DataFrames.mp4 |
22.04Мб |
| 349 Confidence Intervals for Regression Coefficients - Bootstrapping.en.srt |
12.20Кб |
| 349 Confidence Intervals for Regression Coefficients - Bootstrapping.mp4 |
53.48Мб |
| 350 Hypothesis Testing of Regression Coefficients (Theory).en.srt |
4.58Кб |
| 350 Hypothesis Testing of Regression Coefficients (Theory).mp4 |
15.51Мб |
| 350 Testing.pdf |
222.57Кб |
| 351 Hypothesis Testing of Regression Coefficients with statsmodels.en.srt |
4.56Кб |
| 351 Hypothesis Testing of Regression Coefficients with statsmodels.mp4 |
17.77Мб |
| 352 Regression Analysis with statsmodels - the Summary Table.en.srt |
4.69Кб |
| 352 Regression Analysis with statsmodels - the Summary Table.mp4 |
20.94Мб |
| 353 Case Study (Part 3) The Market Model (Single Factor Model).en.srt |
5.89Кб |
| 353 Case Study (Part 3) The Market Model (Single Factor Model).mp4 |
28.93Мб |
| 354 Coding Exercise 2.html |
1016б |
| 355 Multiple-Reg.pdf |
163.99Кб |
| 355 Multiple Regression (Theory).en.srt |
7.62Кб |
| 355 Multiple Regression (Theory).mp4 |
25.94Мб |
| 356 Movies Dataset - Preparing the Data.en.srt |
8.77Кб |
| 356 Movies Dataset - Preparing the Data.mp4 |
49.60Мб |
| 357 Multiple Regression Analysis with statsmodels.en.srt |
6.11Кб |
| 357 Multiple Regression Analysis with statsmodels.mp4 |
31.27Мб |
| 358 Coefficient of Determination (Adjusted R squared).en.srt |
3.46Кб |
| 358 Coefficient of Determination (Adjusted R squared).mp4 |
15.02Мб |
| 358 Rsquared-adjusted.pdf |
132.04Кб |
| 359 Regression Coefficients Hypothesis Testing Model Specification.en.srt |
10.13Кб |
| 359 Regression Coefficients Hypothesis Testing Model Specification.mp4 |
53.61Мб |
| 360 F-Test.pdf |
155.68Кб |
| 360 How to test the Significance of the Model as a whole (F-Test).en.srt |
5.96Кб |
| 360 How to test the Significance of the Model as a whole (F-Test).mp4 |
20.33Мб |
| 361 Creating and working with Dummy Variables (Part 1).en.srt |
9.93Кб |
| 361 Creating and working with Dummy Variables (Part 1).mp4 |
54.41Мб |
| 362 Creating and working with Dummy Variables (Part 2).en.srt |
8.38Кб |
| 362 Creating and working with Dummy Variables (Part 2).mp4 |
43.97Мб |
| 363 Coding Exercise 3.html |
1016б |
| 364 Fama-French.pdf |
322.15Кб |
| 364 Fama-French An Introduction.en.srt |
16.11Кб |
| 364 Fama-French An Introduction.mp4 |
52.56Мб |
| 365 Single-Factor Models with the Fama-French Market Portfolio (Part 1).en.srt |
9.57Кб |
| 365 Single-Factor Models with the Fama-French Market Portfolio (Part 1).mp4 |
63.57Мб |
| 366 Single-Factor Models with the Fama-French Market Portfolio (Part 2).en.srt |
7.52Кб |
| 366 Single-Factor Models with the Fama-French Market Portfolio (Part 2).mp4 |
39.08Мб |
| 367 Size-Value.pdf |
188.85Кб |
| 367 The Factors Size Value.en.srt |
10.95Кб |
| 367 The Factors Size Value.mp4 |
49.08Мб |
| 368 How to create a Fama-French Three-Factor Model.en.srt |
8.83Кб |
| 368 How to create a Fama-French Three-Factor Model.mp4 |
55.42Мб |
| 369 Profitability-Investment.pdf |
190.15Кб |
| 369 The Factors Profitability and Investment.en.srt |
5.91Кб |
| 369 The Factors Profitability and Investment.mp4 |
21.81Мб |
| 370 How to create a Fama-French Five-Factor Model.en.srt |
6.52Кб |
| 370 How to create a Fama-French Five-Factor Model.mp4 |
46.58Мб |
| 371 Coding Exercise 4.html |
1016б |
| 372 Linear Regression - not that easy.en.srt |
5.79Кб |
| 372 Linear Regression - not that easy.mp4 |
24.27Мб |
| 373 Detecting and Handling Outliers (Part 1).en.srt |
10.60Кб |
| 373 Detecting and Handling Outliers (Part 1).mp4 |
67.97Мб |
| 374 Detecting and Handling Outliers (Part 2).en.srt |
3.23Кб |
| 374 Detecting and Handling Outliers (Part 2).mp4 |
21.54Мб |
| 375 Non-Linear Relationships - Feature Transformation.en.srt |
5.42Кб |
| 375 Non-Linear Relationships - Feature Transformation.mp4 |
22.64Мб |
| 376 Detecting and Handling Multicollinearity.en.srt |
8.88Кб |
| 376 Detecting and Handling Multicollinearity.mp4 |
48.52Мб |
| 377 Detecting and Correcting Heteroskedasticity.en.srt |
10.53Кб |
| 377 Detecting and Correcting Heteroskedasticity.mp4 |
61.30Мб |
| 378 Detecting and Handling Serial Correlation (Autocorrelation).en.srt |
13.79Кб |
| 378 Detecting and Handling Serial Correlation (Autocorrelation).mp4 |
79.35Мб |
| 379 Logistic-Regression.pdf |
239.82Кб |
| 379 Logistic Regression (Theory).en.srt |
4.59Кб |
| 379 Logistic Regression (Theory).mp4 |
15.05Мб |
| 380 Logistic Regression with statsmodels (Part 1).en.srt |
5.72Кб |
| 380 Logistic Regression with statsmodels (Part 1).mp4 |
31.14Мб |
| 381 Logistic Regression with statsmodels (Part 2).en.srt |
7.57Кб |
| 381 Logistic Regression with statsmodels (Part 2).mp4 |
40.77Мб |
| 382 Get your special BONUS here.html |
3.23Кб |
| Download Paid Udemy Courses For Free.url |
116б |
| GetFreeCourses.Co.url |
116б |
| GetFreeCourses.Co.url |
116б |
| GetFreeCourses.Co.url |
116б |
| GetFreeCourses.Co.url |
116б |