Udemy Python for Finance Investment Fundamentals Data Analytics


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Udemy Python for Finance Investment Fundamentals Data Analytics
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     [GigaCourse.Com].url -
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     001 What Does the Course Cover.mp4 -
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     001 What Does the Course Cover_en.srt -
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     002 Course-Resources.url -
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     002 Download Useful Resources - Exercises and Solutions.mp4 -
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     002 Python-for-Finance-FAQ.pdf -
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     001 Programming Explained in 5 Minutes.mp4 -
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     002 Why Python.mp4 -
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     001 Comparison Operators.mp4 -
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     002 Logical and Identity Operators.mp4 -
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     006 Iterating over Dictionaries.mp4 -
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     001 Object Oriented Programming.mp4 -
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     002 Modules and Packages.mp4 -
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     003 The Standard Library.mp4 -
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     004 Importing Modules.mp4 -
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     005 47-Packages-Exercise.pdf -
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     005 Must-have packages for Finance and Data Science.mp4 -
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     007 Generating Random Numbers.mp4 -
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     008 A Note on Using Financial Data in Python.mp4 -
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     009 Sources of Financial Data.mp4 -
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     010 Accessing the Notebook Files.mp4 -
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     011 Importing and Organizing Data in Python – part I.mp4 -
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     015 Changing the Index of Your Time-Series Data.mp4 -
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     016 Restarting the Jupyter Kernel.mp4 -
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     001 Considering both risk and return.mp4 -
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     002 What are we going to see next.mp4 -
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     003 Calculating a security's rate of return.mp4 -
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     005 Calculating a Security’s Rate of Return in Python – Simple Returns – Part II.mp4 -
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     006 Calculating a Security’s Return in Python – Logarithmic Returns.mp4 -
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     009 Popular stock indices that can help us understand financial markets.mp4 -
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     010 Calculating the Indices' Rate of Return.mp4 -
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     001 How do we measure a security's risk.mp4 -
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     002 Calculating a Security’s Risk in Python.mp4 -
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     003 The benefits of portfolio diversification.mp4 -
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     004 Calculating the covariance between securities.mp4 -
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     005 Measuring the correlation between stocks.mp4 -
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     006 Calculating Covariance and Correlation.mp4 -
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     009 Understanding Systematic vs. Idiosyncratic risk.mp4 -
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     010 Calculating Diversifiable and Non-Diversifiable Risk of a Portfolio.mp4 -
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     001 Housing-Data.xlsx -
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     001 The fundamentals of simple regression analysis.mp4 -
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     002 Housing.xlsx -
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     002 Running a Regression in Python.mp4 -
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     004 Computing Alpha, Beta, and R Squared in Python.mp4 -
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     001 14.Markowitz-Efficient-frontier.xlsx -
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     001 Markowitz Portfolio Theory - One of the main pillars of modern Finance.mp4 -
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     002 Obtaining the Efficient Frontier in Python – Part I.mp4 -
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     001 The intuition behind the Capital Asset Pricing Model (CAPM).mp4 -
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     002 Understanding and calculating a security's Beta.mp4 -
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     003 Calculating the Beta of a Stock.mp4 -
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     004 The CAPM formula.mp4 -
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     005 Calculating the Expected Return of a Stock (CAPM).mp4 -
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     006 Introducing the Sharpe ratio and how to put it into practice.mp4 -
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     008 Measuring alpha and verifying how good (or bad) a portfolio manager is doing.mp4 -
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     001 Multivariate regression analysis - a valuable tool for finance practitioners.mp4 -
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     002 Housing.xlsx -
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     002 Running a multivariate regression in Python.mp4 -
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     001 The essence of Monte Carlo simulations.mp4 -
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     002 Monte Carlo applied in a Corporate Finance context.mp4 -
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     003 Monte Carlo Predicting Gross Profit – Part I.mp4 -
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     005 Forecasting Stock Prices with a Monte Carlo Simulation.mp4 -
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     006 Monte Carlo Forecasting Stock Prices - Part I.mp4 -
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     007 Monte Carlo Forecasting Stock Prices - Part II.mp4 -
17.4 MB



     007 Monte Carlo Forecasting Stock Prices - Part II_en.srt -
5.6 KB



     007 Predicting-Stock-Prices-Part-II-Resources.url -
97 bytes



     008 Monte Carlo Forecasting Stock Prices - Part III.mp4 -
20.8 MB



     008 Monte Carlo Forecasting Stock Prices - Part III_en.srt -
5.4 KB



     008 Predicting-Stock-Prices-Part-III-Resources.url -
97 bytes



     009 An Introduction to Derivative Contracts.mp4 -
11.4 MB



     009 An Introduction to Derivative Contracts_en.srt -
8.2 KB



     009 Python-for-Finance-Course-Notes-Part-II.pdf -
1.0 MB



     010 Python-for-Finance-Course-Notes-Part-II.pdf -
1.0 MB



     010 The Black Scholes Formula for Option Pricing.mp4 -
8.8 MB



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     011 Monte Carlo Black-Scholes-Merton.mp4 -
29.0 MB



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7.8 KB



     011 Monte-Carlo-Black-Scholes-Merton-Resources.url -
97 bytes



     012 Monte Carlo Euler Discretization - Part I.mp4 -
30.4 MB



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8.4 KB



     012 Monte-Carlo-Euler-Discretization-Part-I-Resources.url -
97 bytes



     013 Monte Carlo Euler Discretization - Part II.mp4 -
8.7 MB



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3.0 KB



     013 Monte-Carlo-Euler-Discretization-Part-II-Resources.url -
97 bytes



     external-links.txt -
1.1 KB



     001 pandas Series - Introduction.mp4 -
21.8 MB



     001 pandas Series - Introduction_en.srt -
10.8 KB



     001 pandas-DataFrames-Introduction-Exercise.ipynb -
3.8 KB



     001 pandas-DataFrames-Introduction-Lecture.ipynb -
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     001 pandas-DataFrames-Introduction-Solution.ipynb -
16.9 KB



     002 pandas - Working with Methods - Part I.mp4 -
19.4 MB



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7.0 KB



     002 pandas-Working-with-Methods-Part-I-Lecture.ipynb -
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     003 pandas - Working with Methods - Part II.mp4 -
8.9 MB



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     004 Using-Parameters-and-Arguments-Exercise.ipynb -
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2.8 KB



     004 pandas - Using Parameters and Arguments.mp4 -
15.3 MB



     004 pandas - Using Parameters and Arguments_en.srt -
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     005 Location.csv -
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     005 Region.csv -
10.2 KB



     005 pandas Series - .unique() and .nunique().mp4 -
26.1 MB



     005 pandas Series - .unique() and .nunique()_en.srt -
5.5 KB



     005 pandas-Series.unique-and.nunique-Exercise.ipynb -
2.7 KB



     005 pandas-Series.unique-and.nunique-Lecture.ipynb -
2.5 KB



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     006 Location.csv -
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     006 Region.csv -
10.2 KB



     006 pandas Series - .sort_values().mp4 -
13.0 MB



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     006 pandas-Series.sort-values-Exercise.ipynb -
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     006 pandas-Series.sort-values-Lecture.ipynb -
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     006 pandas-Series.sort-values-Solution.ipynb -
4.6 KB



     007 pandas DataFrames - Introduction - Part I.mp4 -
10.6 MB



     007 pandas DataFrames - Introduction - Part I_en.srt -
7.1 KB



     008 Lending-company.csv -
112.4 KB



     008 Sales-products.csv -
152.3 KB



     008 pandas DataFrames - Introduction - Part II.mp4 -
20.4 MB



     008 pandas DataFrames - Introduction - Part II_en.srt -
7.6 KB



     008 pandas-Series-Introduction-Exercise.ipynb -
5.2 KB



     008 pandas-Series-Introduction-Lecture.ipynb -
3.1 KB



     008 pandas-Series-Introduction-Solution.ipynb -
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     009 Lending-company.csv -
112.4 KB



     009 Sales-products.csv -
152.3 KB



     009 pandas DataFrames - Common Attributes.mp4 -
25.5 MB



     009 pandas DataFrames - Common Attributes_en.srt -
6.3 KB



     009 pandas-DataFrames-Common-Attributes-Exercise.ipynb -
7.2 KB



     009 pandas-DataFrames-Common-Attributes-Lecture.ipynb -
2.9 KB



     009 pandas-DataFrames-Common-Attributes-Solution.ipynb -
23.2 KB



     010 Lending-company.csv -
112.4 KB



     010 Sales-products.csv -
152.3 KB



     010 pandas DataFrames - Data Selection.mp4 -
46.8 MB



     010 pandas DataFrames - Data Selection_en.srt -
10.2 KB



     010 pandas-DataFrames-Data-Selection-Exercise.ipynb -
4.9 KB



     010 pandas-DataFrames-Data-Selection-Lecture.ipynb -
3.0 KB



     010 pandas-DataFrames-Data-Selection-Solution.ipynb -
17.3 KB



     011 Lending-company.csv -
112.4 KB



     011 Sales-products.csv -
152.3 KB



     011 pandas DataFrames - Data Selection with .iloc[].mp4 -
32.1 MB



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8.2 KB



     011 pandas-DataFrames-Data-Selection.iloc-Exercise.ipynb -
5.4 KB



     011 pandas-DataFrames-Data-Selection.iloc-Lecture.ipynb -
3.0 KB



     011 pandas-DataFrames-Data-Selection.iloc-Solution.ipynb -
19.0 KB



     012 Lending-company.csv -
112.4 KB



     012 Sales-products.csv -
152.3 KB



     012 pandas DataFrames - Data Selection with .loc[].mp4 -
20.7 MB



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     012 pandas-DataFrames-Data-Selection.loc-Exercise.ipynb -
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     012 pandas-DataFrames-Data-Selection.loc-Lecture.ipynb -
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     012 pandas-DataFrames-Data-Selection.loc-Solution.ipynb -
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     001 Technical Analysis - Principles, Applications, Assumptions.mp4 -
8.3 MB



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4.5 KB



     002 Charts Used in Technical Analysis.mp4 -
25.7 MB



     002 Charts Used in Technical Analysis_en.srt -
8.4 KB



     003 Other Tools Used in Technical Analysis.mp4 -
13.2 MB



     003 Other Tools Used in Technical Analysis_en.srt -
2.8 KB



     004 Trend, Support and Resistance Lines.mp4 -
27.8 MB



     004 Trend, Support and Resistance Lines_en.srt -
6.1 KB



     005 Common Chart Patterns.mp4 -
16.0 MB



     005 Common Chart Patterns_en.srt -
6.6 KB



     006 Price Indicators.mp4 -
18.2 MB



     006 Price Indicators_en.srt -
5.8 KB



     007 Momentum Oscillators.mp4 -
13.9 MB



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     008 Non-price Based Indicators.mp4 -
13.4 MB



     008 Non-price Based Indicators_en.srt -
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     009 Technical Analysis - Cycles.mp4 -
15.9 MB



     009 Technical Analysis - Cycles_en.srt -
5.8 KB



     010 Intermarket Analysis.mp4 -
3.4 MB



     010 Intermarket Analysis_en.srt -
1.8 KB



     001 Bonus Lecture Next Steps.html -
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