Complete 2-in-1 Python for Business and Finance Bootcamp

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Complete 2-in-1 Python for Business and Finance Bootcamp

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Complete 2-in-1 Python for Business and Finance Bootcamp
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01 Getting Started
001 Tips How to get the most out of this Course (don t skip).en.srt
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001 Tips How to get the most out of this Course (don t skip).mp4
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37.57 MB
002 FAQ Your Questions answered.html
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003 How to download and install Anaconda for Python coding.en.srt
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003 How to download and install Anaconda for Python coding.mp4
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004 Jupyter Notebooks - let s get started.en.srt
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004 Jupyter Notebooks - let s get started.mp4
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005 How to work with Jupyter Notebooks.en.srt
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005 How to work with Jupyter Notebooks.mp4
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02 ---- PART 1 PYTHON BASICS TIME VALUE OF MONEY AND CAPITAL BUDGETING ----
006 Course-Materials-Part1.zip
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006 Overview Download of Course Materials for Part 1.en.srt
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006 Overview Download of Course Materials for Part 1.mp4
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007 Coding Projects Part 1 - Overview.en.srt
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007 Coding Projects Part 1 - Overview.mp4
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007 Python-for-Finance-Projects-Part1.pdf
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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
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008 Intro to the Time Value of Money (TVM) Concept (Theory).mp4
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008 TVM.pdf
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009 Calculate Future Values (FV) with Python Compounding.en.srt
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009 Calculate Future Values (FV) with Python Compounding.mp4
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010 Calculate Present Values (FV) with Python Discounting.en.srt
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010 Calculate Present Values (FV) with Python Discounting.mp4
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011 Interest Rates and Returns (Theory).en.srt
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011 Interest Rates and Returns (Theory).mp4
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011 Interest-Rates.pdf
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012 Calculate Interest Rates and Returns with Python.en.srt
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012 Calculate Interest Rates and Returns with Python.mp4
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013 Introduction to Variables.en.srt
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013 Introduction to Variables.mp4
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014 Variables and Memory (Theory).en.srt
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014 Variables and Memory (Theory).mp4
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014 Variables.pdf
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015 Excursus How to add inline comments.en.srt
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015 Excursus How to add inline comments.mp4
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016 More on Variables and Memory.en.srt
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016 More on Variables and Memory.mp4
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017 Variables - Dos Don ts and Conventions.en.srt
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017 Variables - Dos Don ts and Conventions.mp4
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017 keywords.pdf
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018 The print() Function.en.srt
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018 The print() Function.mp4
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019 Coding Exercise 1.en.srt
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019 Coding Exercise 1.mp4
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04 How to use Lists and For Loops for TVM Problems with many Cashflows
020 FV-many.pdf
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020 TVM Problems with many Cashflows.en.srt
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020 TVM Problems with many Cashflows.mp4
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021 Intro to Python Lists.en.srt
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021 Intro to Python Lists.mp4
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022 Indexing.pdf
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022 Zero-based Indexing and negative Indexing in Python (Theory).en.srt
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022 Zero-based Indexing and negative Indexing in Python (Theory).mp4
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023 Indexing Lists.en.srt
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023 Indexing Lists.mp4
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024 For Loops - Iterating over Lists.en.srt
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024 For Loops - Iterating over Lists.mp4
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025 The range Object - another Iterable.en.srt
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025 The range Object - another Iterable.mp4
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026 Calculate FV and PV for many Cashflows.en.srt
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026 Calculate FV and PV for many Cashflows.mp4
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026 PV-FV-many.pdf
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027 NPV.pdf
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027 The Net Present Value - NPV (Theory).en.srt
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027 The Net Present Value - NPV (Theory).mp4
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028 Calculate an Investment Project s NPV.en.srt
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028 Calculate an Investment Project s NPV.mp4
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029 Coding Exercise 2.en.srt
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029 Coding Exercise 2.mp4
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05 100 Python Objects Data Types Operators Functional Programming
030 Data Types in Action.en.srt
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030 Data Types in Action.mp4
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031 The Data Type Hierarchy (Theory).en.srt
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031 The Data Type Hierarchy (Theory).mp4
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031 Type-Hierarchy.pdf
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032 Excursus Dynamic Typing in Python.en.srt
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032 Excursus Dynamic Typing in Python.mp4
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033 Build-in Functions.en.srt
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033 Build-in Functions.mp4
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033 Built-in-func.pdf
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034 Integers.en.srt
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034 Integers.mp4
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035 Floats.en.srt
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035 Floats.mp4
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036 How to round Floats (and Integers) with round().en.srt
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036 How to round Floats (and Integers) with round().mp4
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037 More on Lists.en.srt
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037 More on Lists.mp4
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038 Lists and Element-wise Operations.en.srt
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038 Lists and Element-wise Operations.mp4
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039 Slicing Lists.en.srt
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039 Slicing Lists.mp4
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040 Slicing Cheat Sheet.html
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040 Slicing-cheatsheet.pdf
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041 Changing Elements in Lists.en.srt
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041 Changing Elements in Lists.mp4
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042 Sorting and Reversing Lists.en.srt
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042 Sorting and Reversing Lists.mp4
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043 Adding and removing Elements fromto Lists.en.srt
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043 Adding and removing Elements fromto Lists.mp4
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044 Mutable vs. immutable Objects (Part 1).en.srt
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044 Mutable vs. immutable Objects (Part 1).mp4
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045 Mutability.pdf
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045 Mutable vs. immutable Objects (Part 2).en.srt
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045 Mutable vs. immutable Objects (Part 2).mp4
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046 Coding Exercise 3.en.srt
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046 Coding Exercise 3.mp4
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047 Tuples.en.srt
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047 Tuples.mp4
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048 Dictionaries.en.srt
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048 Dictionaries.mp4
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049 Intro to Strings.en.srt
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049 Intro to Strings.mp4
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050 String Replacement.en.srt
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050 String Replacement.mp4
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051 Booleans.en.srt
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051 Booleans.mp4
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052 Operators (Theory).en.srt
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052 Operators (Theory).mp4
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052 Operators.pdf
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053 Comparison Logical and Membership Operators in Action.en.srt
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053 Comparison Logical and Membership Operators in Action.mp4
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054 Coding Exercise 4.en.srt
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054 Coding Exercise 4.mp4
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06 How to solve for IRR YTM with While Loops and Conditional Statements
055 Conditional Statements.en.srt
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055 Conditional Statements.mp4
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056 Keywords pass continue and break.en.srt
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056 Keywords pass continue and break.mp4
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057 Calculate a Project s Payback Period.en.srt
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057 Calculate a Project s Payback Period.mp4
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058 While Loops.en.srt
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058 While Loops.mp4
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059 IRR.pdf
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059 The Internal Rate of Return - IRR (Theory).en.srt
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059 The Internal Rate of Return - IRR (Theory).mp4
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060 Solving for a Project s IRR.en.srt
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060 Solving for a Project s IRR.mp4
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061 Bonds and the Yield to Maturity - YTM (Theory).en.srt
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061 Bonds and the Yield to Maturity - YTM (Theory).mp4
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061 Bonds-YTM.pdf
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062 Solving for a Bond s Yield to Maturity (YTM).en.srt
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062 Solving for a Bond s Yield to Maturity (YTM).mp4
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063 Coding Exercise 5.en.srt
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063 Coding Exercise 5.mp4
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GetFreeCourses.Co.url
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116 B
07 How to create great graphs with Matplotlib - Plotting NPV and IRR
064 Intro.en.srt
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064 Intro.mp4
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065 Line Plots.en.srt
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065 Line Plots.mp4
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066 Scatter Plots.en.srt
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066 Scatter Plots.mp4
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067 Customizing Plots (Part 1).en.srt
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067 Customizing Plots (Part 1).mp4
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068 Customizing Plots (Part 2).en.srt
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068 Customizing Plots (Part 2).mp4
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069 Plotting NPV IRR.en.srt
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069 Plotting NPV IRR.mp4
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070 Coding Exercise 6.html
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08 The Numpy Package Working with numbers made easy
071 Modules Packages and Libraries - No need to reinvent the Wheel.en.srt
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071 Modules Packages and Libraries - No need to reinvent the Wheel.mp4
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072 Numpy Arrays.en.srt
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072 Numpy Arrays.mp4
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073 Indexing and Slicing Numpy Arrays.en.srt
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073 Indexing and Slicing Numpy Arrays.mp4
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074 Vectorized Operations with Numpy Arrays.en.srt
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074 Vectorized Operations with Numpy Arrays.mp4
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075 Changing Elements in Numpy Arrays Mutability.en.srt
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075 Changing Elements in Numpy Arrays Mutability.mp4
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075 Mutability-arrays.pdf
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076 Slicing-arrays.pdf
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076 View vs. copy - potential Pitfalls when slicing Numpy Arrays.en.srt
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076 View vs. copy - potential Pitfalls when slicing Numpy Arrays.mp4
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077 Numpy Array Methods and Attributes.en.srt
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077 Numpy Array Methods and Attributes.mp4
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078 Numpy Universal Functions.en.srt
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078 Numpy Universal Functions.mp4
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079 Boolean Arrays and Conditional Filtering.en.srt
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079 Boolean Arrays and Conditional Filtering.mp4
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080 Advanced Filtering Bitwise Operators.en.srt
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080 Advanced Filtering Bitwise Operators.mp4
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081 Determining a Project s Payback Period with np.where().en.srt
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081 Determining a Project s Payback Period with np.where().mp4
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082 Creating Numpy Arrays from Scratch.en.srt
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082 Creating Numpy Arrays from Scratch.mp4
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083 Coding Exercise 7.en.srt
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083 Coding Exercise 7.mp4
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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
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084 Evaluating Investments with np.npv() and np.irr().mp4
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085 Annuity.pdf
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085 Evaluating Annuities with np.fv() - Funding Phase.en.srt
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085 Evaluating Annuities with np.fv() - Funding Phase.mp4
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086 Evaluating Annuities with np.fv() - Payout Phase.en.srt
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086 Evaluating Annuities with np.fv() - Payout Phase.mp4
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087 How to solve for annuity payments with np.pmt().en.srt
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087 How to solve for annuity payments with np.pmt().mp4
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088 How to solve for the number of periodic payments with np.nper().en.srt
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088 How to solve for the number of periodic payments with np.nper().mp4
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089 How to calculate the required Contract Value with np.pv().en.srt
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089 How to calculate the required Contract Value with np.pv().mp4
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090 Frequency of compounding and the effective annual interest rate.en.srt
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090 Frequency of compounding and the effective annual interest rate.mp4
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091 How to evaluate a Retirement Plan A-Z.en.srt
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091 How to evaluate a Retirement Plan A-Z.mp4
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092 Retirement Plan Sensitivity Analysis.en.srt
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092 Retirement Plan Sensitivity Analysis.mp4
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093 Mortgage Loan Analysis - Debt Sizing.en.srt
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093 Mortgage Loan Analysis - Debt Sizing.mp4
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093 Mortgage.pdf
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094 Mortgage Loan Analysis - Interest Payments and Amortization Schedule.en.srt
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094 Mortgage Loan Analysis - Interest Payments and Amortization Schedule.mp4
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095 Calculate PV of equal installments with np.pv() - Valuation of Bonds.en.srt
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095 Calculate PV of equal installments with np.pv() - Valuation of Bonds.mp4
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096 Capital Budgeting - Mutually exclusive Projects (Part 1).en.srt
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096 Capital Budgeting - Mutually exclusive Projects (Part 1).mp4
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097 Capital Budgeting - Mutually exclusive Projects (Part 2).en.srt
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097 Capital Budgeting - Mutually exclusive Projects (Part 2).mp4
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098 Capital Budgeting - Mutually exclusive Projects (Part 3).en.srt
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098 Capital Budgeting - Mutually exclusive Projects (Part 3).mp4
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098 Capital-budgeting.pdf
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099 Coding Exercise 8.html
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10 --- PART 2 STATISTICS AND HYPOTHESIS TESTING WITH PYTHON NUMPY AND SCIPY ---
100 Overview.pdf
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100 Statistics - Overview Terms and Vocabulary.en.srt
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100 Statistics - Overview Terms and Vocabulary.mp4
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101 Coding Projects Part 2 - Overview.en.srt
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101 Coding Projects Part 2 - Overview.mp4
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101 Python-for-Finance-Projects-Part2.pdf
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102 Course-Materials-Part2.zip
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102 Download of Part 2 Course Materials.en.srt
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102 Download of Part 2 Course Materials.mp4
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11 How to perform Descriptive Statistics on Populations and Samples
103 Population vs. Sample.en.srt
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103 Population vs. Sample.mp4
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104 Visualizing Frequency Distributions with plt.hist().en.srt
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104 Visualizing Frequency Distributions with plt.hist().mp4
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105 Relative and Cumulative Frequencies with plt.hist().en.srt
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105 Relative and Cumulative Frequencies with plt.hist().mp4
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106 Central-tend.pdf
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106 Measures of Central Tendency (Theory).en.srt
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106 Measures of Central Tendency (Theory).mp4
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107 Coding Measures of Central Tendency - Mean and Median.en.srt
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107 Coding Measures of Central Tendency - Mean and Median.mp4
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108 Coding Measures of Central Tendency - Geometric Mean.en.srt
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108 Coding Measures of Central Tendency - Geometric Mean.mp4
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109 Excursus Why Log Returns are useful.en.srt
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109 Excursus Why Log Returns are useful.mp4
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110 Dispersion.pdf
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110 Variability around the Central Tendency Dispersion (Theory).en.srt
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110 Variability around the Central Tendency Dispersion (Theory).mp4
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111 Minimum Maximum and Range with PythonNumpy.en.srt
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111 Minimum Maximum and Range with PythonNumpy.mp4
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112 Percentiles with PythonNumpy.en.srt
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112 Percentiles with PythonNumpy.mp4
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113 Variance and Standard Deviation with PythonNumpy.en.srt
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113 Variance and Standard Deviation with PythonNumpy.mp4
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114 Skew and Kurtosis (Theory).en.srt
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114 Skew and Kurtosis (Theory).mp4
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114 skew-kurtosis.pdf
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115 How to calculate Skew and Kurtosis with scipy.stats.en.srt
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115 How to calculate Skew and Kurtosis with scipy.stats.mp4
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116 Coding Exercise 1.html
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12 Common Probability Distributions and how to construct Confidence Intervals
117 How to generate Random Numbers with Numpy.en.srt
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117 How to generate Random Numbers with Numpy.mp4
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118 Reproducibility with np.random.seed().en.srt
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118 Reproducibility with np.random.seed().mp4
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119 Prob-distr.pdf
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119 Probability Distributions - Overview.en.srt
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119 Probability Distributions - Overview.mp4
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120 Discrete Uniform Distributions.en.srt
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120 Discrete Uniform Distributions.mp4
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121 Continuous Uniform Distributions.en.srt
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121 Continuous Uniform Distributions.mp4
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122 Normal.pdf
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122 The Normal Distribution (Theory).en.srt
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122 The Normal Distribution (Theory).mp4
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123 Creating a normally distributed Random Variable.en.srt
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123 Creating a normally distributed Random Variable.mp4
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124 Normal Distribution - Probability Density Function (pdf) with scipy.stats.en.srt
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124 Normal Distribution - Probability Density Function (pdf) with scipy.stats.mp4
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125 Normal Distribution - Cumulative Distribution Function (cdf) with scipy.stats.en.srt
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125 Normal Distribution - Cumulative Distribution Function (cdf) with scipy.stats.mp4
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126 The Standard Normal Distribution and Z-Values.en.srt
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126 The Standard Normal Distribution and Z-Values.mp4
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127 Properties of the Standard Normal Distribution (Theory).en.srt
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127 Properties of the Standard Normal Distribution (Theory).mp4
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127 standard-normal.pdf
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128 Probabilities and Z-Values with scipy.stats.en.srt
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128 Probabilities and Z-Values with scipy.stats.mp4
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129 Confidence Intervals with scipy.stats.en.srt
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129 Confidence Intervals with scipy.stats.mp4
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130 Coding Exercise 2.html
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13 How to estimate Population parameters with Samples - Sampling and Estimation
131 Sample Statistic Sampling Error and Sampling Distribution (Theory).en.srt
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131 Sample Statistic Sampling Error and Sampling Distribution (Theory).mp4
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131 Sampling.pdf
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132 Sampling with np.random.choice().en.srt
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132 Sampling with np.random.choice().mp4
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133 Sampling Distribution.en.srt
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133 Sampling Distribution.mp4
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134 Standard Error.en.srt
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134 Standard Error.mp4
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135 Central Limit Theorem (Coding Part 1).en.srt
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135 Central Limit Theorem (Coding Part 1).mp4
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136 Central Limit Theorem (Coding Part 2).en.srt
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136 Central Limit Theorem (Coding Part 2).mp4
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137 Central Limit Theorem (Theory).en.srt
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137 Central Limit Theorem (Theory).mp4
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137 central-limit-th.pdf
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138 Point Estimates vs. Confidence Interval Estimates (known Population Variance).en.srt
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138 Point Estimates vs. Confidence Interval Estimates (known Population Variance).mp4
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139 The Student s t-distribution What is it and whywhen do we use it.en.srt
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139 The Student s t-distribution What is it and whywhen do we use it.mp4
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139 studentsT.pdf
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140 Unknown Population Variance - the Standard Case (Example 1).en.srt
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140 Unknown Population Variance - the Standard Case (Example 1).mp4
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141 Unknown Population Variance - the Standard Case (Example 2).en.srt
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141 Unknown Population Variance - the Standard Case (Example 2).mp4
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142 Student s t-Distribution vs. Normal Distribution with scipy.stats.en.srt
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142 Student s t-Distribution vs. Normal Distribution with scipy.stats.mp4
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143 Bootstrapping with Python an alternative method without Statistics.en.srt
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143 Bootstrapping with Python an alternative method without Statistics.mp4
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144 Coding Exercise 3.html
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14 How to perform Hypothesis Tests Z-Tests t-Tests Bootstrapping more
145 Hypothesis Testing (Theory).en.srt
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145 Hypothesis Testing (Theory).mp4
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145 Hypothesis.pdf
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146 Two-tailed Z-Test with known Population Variance.en.srt
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146 Two-tailed Z-Test with known Population Variance.mp4
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147 p-value.pdf
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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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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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15 -- PART 3 ADVANCED PYTHON MONTE CARLO SIMULATIONS AND VALUE AT RISK (VAR) ---
155 Course-Materials-Part3.zip
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155 Overview Download of Course Materials for Part 3.en.srt
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156 Coding Projects Part 3 - Overview.en.srt
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156 Coding-Projects-Part3.pdf
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16 n-dimensional Numpy Arrays How to work with numerical Tabular Data
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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17 How to create your own user-defined Functions
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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18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy
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 CVaR.pdf
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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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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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19 --- PART 4 MANAGING (FINANCIAL) DATA WITH PANDAS BEYOND EXCEL ---
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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20 Pandas Basics - Starting from Zero
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 Position-based Indexing Cheat Sheets.html
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208 pandas-iloc.pdf
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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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21 Pandas Intermediate
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
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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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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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22 Data Visualization with Pandas Matplotlib and Seaborn
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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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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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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256 Seaborn Heatmaps.en.srt
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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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23 Pandas Advanced
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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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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274 split-apply-combine.en.srt
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275 split-apply-combine applied.en.srt
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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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24 Managing Time Series and Financial Data with Pandas
280 Importing Time Series Data from csv-files.en.srt
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280 Importing Time Series Data from csv-files.mp4
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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
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283 Indexing and Slicing Time Series.en.srt
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283 Indexing and Slicing Time Series.mp4
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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
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299 The methods diff() and pct_change().en.srt
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299 The methods diff() and pct_change().mp4
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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
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301 Financial Time Series - Return and Risk.en.srt
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301 Financial Time Series - Return and Risk.mp4
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302 Financial Time Series - Covariance and Correlation.en.srt
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302 Financial Time Series - Covariance and Correlation.mp4
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303 Importing Financial Data from Excel.en.srt
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303 Importing Financial Data from Excel.mp4
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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).mp4
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25 Creating analyzing and optimizing Financial Portfolios with Python
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
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309 Creating the equally-weighted Portfolio.mp4
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310 Creating many random Portfolios with Python.en.srt
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310 Creating many random Portfolios with Python.mp4
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311 What is the Sharpe Ratio and a Risk Free Asset.en.srt
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311 What is the Sharpe Ratio and a Risk Free Asset.mp4
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312 Portfolio Analysis and the Sharpe Ratio with Python.en.srt
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312 Portfolio Analysis and the Sharpe Ratio with Python.mp4
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313 Finding the Optimal Portfolio.en.srt
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313 Finding the Optimal Portfolio.mp4
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39.05 MB
314 Sharpe Ratio - visualized and explained.en.srt
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314 Sharpe Ratio - visualized and explained.mp4
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23.23 MB
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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7.99 MB
318 Capital Market Line (CML) Two-Fund-Theorem.en.srt
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318 Capital Market Line (CML) Two-Fund-Theorem.mp4
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15.81 MB
319 The Portfolio Diversification Effect.en.srt
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319 The Portfolio Diversification Effect.mp4
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70.99 MB
320 Systematic vs. unsystematic Risk.en.srt
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320 Systematic vs. unsystematic Risk.mp4
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59.51 MB
321 Capital Asset Pricing Model (CAPM) Security Market Line (SLM).en.srt
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321 Capital Asset Pricing Model (CAPM) Security Market Line (SLM).mp4
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322 Beta and Alpha.en.srt
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322 Beta and Alpha.mp4
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323 Redefining the Market Portfolio.en.srt
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323 Redefining the Market Portfolio.mp4
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324 Cyclical vs. non-cyclical Stocks - another Intuition on Beta.en.srt
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324 Cyclical vs. non-cyclical Stocks - another Intuition on Beta.mp4
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32.71 MB
325 Coding Exercise 14 (Intro).html
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326 Coding Exercise 14 (Solution).en.srt
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326 Coding Exercise 14 (Solution).mp4
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26 --- PART 5 REGRESSION ANALYSIS (A MUST-HAVE FOR MACHINE LEARNING) ---
327 Introduction to Regression Analysis.en.srt
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327 Introduction to Regression Analysis.mp4
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50.63 MB
328 Coding Projects Part 5 - Overview.en.srt
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2.79 KB
328 Coding Projects Part 5 - Overview.mp4
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16.49 MB
328 Coding-Projects-Part5.pdf
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636.64 KB
329 Course-Materials-Part5.zip
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25.69 MB
329 Download of Part 5 Course Materials.html
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995 B
27 Correlation and Regression
330 Cleaning and preparing the Data - Movies Database (Part 1).en.srt
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330 Cleaning and preparing the Data - Movies Database (Part 1).mp4
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47.03 MB
331 Cleaning and preparing the Data - Movies Database (Part 2).en.srt
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7.07 KB
331 Cleaning and preparing the Data - Movies Database (Part 2).mp4
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31.12 MB
332 Cov-Corr.pdf
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228.13 KB
332 Covariance and Correlation Coefficient (Theory).en.srt
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332 Covariance and Correlation Coefficient (Theory).mp4
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27.58 MB
333 How to calculate Covariance and Correlation in Python.en.srt
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6.28 KB
333 How to calculate Covariance and Correlation in Python.mp4
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23.98 MB
334 Correlation and Scatterplots visual Interpretation.en.srt
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334 Correlation and Scatterplots visual Interpretation.mp4
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20 MB
334 Visual.pdf
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335 Creating a Confidence Interval for the Correlation Coefficient (Bootstrapping).en.srt
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335 Creating a Confidence Interval for the Correlation Coefficient (Bootstrapping).mp4
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38.94 MB
336 Testing for Correlation (t-Test).en.srt
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336 Testing for Correlation (t-Test).mp4
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16.57 MB
337 Regression.pdf
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150.15 KB
337 What is Linear Regression (Theory).en.srt
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337 What is Linear Regression (Theory).mp4
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11.64 MB
338 A simple Linear Regression Model with numpy Scipy.en.srt
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7.9 KB
338 A simple Linear Regression Model with numpy Scipy.mp4
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39.72 MB
339 Coeff.pdf
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177.7 KB
339 How to interpret Intercept and Slope Coefficient.en.srt
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3.29 KB
339 How to interpret Intercept and Slope Coefficient.mp4
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12.33 MB
340 Case Study (Part 1) The Market Model (Single Factor Model).en.srt
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5.77 KB
340 Case Study (Part 1) The Market Model (Single Factor Model).mp4
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26.32 MB
341 Case Study (Part 2) The Market Model (Single Factor Model).en.srt
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341 Case Study (Part 2) The Market Model (Single Factor Model).mp4
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10.31 MB
342 Coding Exercise 1.html
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28 OLS Regression ANOVA and Hypothesis Testing
343 OLS (Ordinary Least Squares) Regression (Theory).en.srt
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343 OLS (Ordinary Least Squares) Regression (Theory).mp4
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343 OLS.pdf
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147.82 KB
344 OLS Regression with statsmodels - Intro.en.srt
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344 OLS Regression with statsmodels - Intro.mp4
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345 ANOVA.pdf
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345 OLS Regression - ANOVA (Theory).en.srt
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345 OLS Regression - ANOVA (Theory).mp4
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36.35 MB
346 OLS Regression with Statsmodels - ANOVA.en.srt
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346 OLS Regression with Statsmodels - ANOVA.mp4
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17.82 MB
347 Coefficient of Determination (R squared).en.srt
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347 Coefficient of Determination (R squared).mp4
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6.88 MB
348 OLS Regression with statsmodels and DataFrames.en.srt
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348 OLS Regression with statsmodels and DataFrames.mp4
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22.04 MB
349 Confidence Intervals for Regression Coefficients - Bootstrapping.en.srt
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349 Confidence Intervals for Regression Coefficients - Bootstrapping.mp4
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350 Hypothesis Testing of Regression Coefficients (Theory).en.srt
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350 Hypothesis Testing of Regression Coefficients (Theory).mp4
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350 Testing.pdf
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351 Hypothesis Testing of Regression Coefficients with statsmodels.en.srt
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351 Hypothesis Testing of Regression Coefficients with statsmodels.mp4
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352 Regression Analysis with statsmodels - the Summary Table.en.srt
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352 Regression Analysis with statsmodels - the Summary Table.mp4
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20.94 MB
353 Case Study (Part 3) The Market Model (Single Factor Model).en.srt
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353 Case Study (Part 3) The Market Model (Single Factor Model).mp4
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354 Coding Exercise 2.html
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29 Multiple Regression Models
355 Multiple Regression (Theory).en.srt
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355 Multiple Regression (Theory).mp4
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355 Multiple-Reg.pdf
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163.99 KB
356 Movies Dataset - Preparing the Data.en.srt
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356 Movies Dataset - Preparing the Data.mp4
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49.6 MB
357 Multiple Regression Analysis with statsmodels.en.srt
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357 Multiple Regression Analysis with statsmodels.mp4
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31.27 MB
358 Coefficient of Determination (Adjusted R squared).en.srt
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358 Coefficient of Determination (Adjusted R squared).mp4
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15.02 MB
358 Rsquared-adjusted.pdf
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132.04 KB
359 Regression Coefficients Hypothesis Testing Model Specification.en.srt
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359 Regression Coefficients Hypothesis Testing Model Specification.mp4
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53.61 MB
360 F-Test.pdf
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155.68 KB
360 How to test the Significance of the Model as a whole (F-Test).en.srt
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5.96 KB
360 How to test the Significance of the Model as a whole (F-Test).mp4
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20.33 MB
361 Creating and working with Dummy Variables (Part 1).en.srt
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361 Creating and working with Dummy Variables (Part 1).mp4
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54.41 MB
362 Creating and working with Dummy Variables (Part 2).en.srt
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362 Creating and working with Dummy Variables (Part 2).mp4
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363 Coding Exercise 3.html
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30 Case Study Multi-Factor Models (Fama-French)
364 Fama-French An Introduction.en.srt
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364 Fama-French An Introduction.mp4
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364 Fama-French.pdf
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365 Single-Factor Models with the Fama-French Market Portfolio (Part 1).en.srt
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365 Single-Factor Models with the Fama-French Market Portfolio (Part 1).mp4
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63.57 MB
366 Single-Factor Models with the Fama-French Market Portfolio (Part 2).en.srt
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366 Single-Factor Models with the Fama-French Market Portfolio (Part 2).mp4
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367 Size-Value.pdf
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367 The Factors Size Value.en.srt
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367 The Factors Size Value.mp4
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368 How to create a Fama-French Three-Factor Model.en.srt
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368 How to create a Fama-French Three-Factor Model.mp4
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369 Profitability-Investment.pdf
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190.15 KB
369 The Factors Profitability and Investment.en.srt
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369 The Factors Profitability and Investment.mp4
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370 How to create a Fama-French Five-Factor Model.en.srt
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370 How to create a Fama-French Five-Factor Model.mp4
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371 Coding Exercise 4.html
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GetFreeCourses.Co.url
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116 B
31 Issues in Linear Regression Analysis and Logistic Regression
372 Linear Regression - not that easy.en.srt
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372 Linear Regression - not that easy.mp4
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24.27 MB
373 Detecting and Handling Outliers (Part 1).en.srt
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373 Detecting and Handling Outliers (Part 1).mp4
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67.97 MB
374 Detecting and Handling Outliers (Part 2).en.srt
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374 Detecting and Handling Outliers (Part 2).mp4
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375 Non-Linear Relationships - Feature Transformation.en.srt
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375 Non-Linear Relationships - Feature Transformation.mp4
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22.64 MB
376 Detecting and Handling Multicollinearity.en.srt
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376 Detecting and Handling Multicollinearity.mp4
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48.52 MB
377 Detecting and Correcting Heteroskedasticity.en.srt
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377 Detecting and Correcting Heteroskedasticity.mp4
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61.3 MB
378 Detecting and Handling Serial Correlation (Autocorrelation).en.srt
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378 Detecting and Handling Serial Correlation (Autocorrelation).mp4
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79.35 MB
379 Logistic Regression (Theory).en.srt
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379 Logistic Regression (Theory).mp4
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379 Logistic-Regression.pdf
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239.82 KB
380 Logistic Regression with statsmodels (Part 1).en.srt
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380 Logistic Regression with statsmodels (Part 1).mp4
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31.14 MB
381 Logistic Regression with statsmodels (Part 2).en.srt
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381 Logistic Regression with statsmodels (Part 2).mp4
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32 What s next
382 Get your special BONUS here.html
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Download Paid Udemy Courses For Free.url
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