< Mastering Python for Cryptocurrency Trading: Advanced Strategies and Techniques
66 casts | 13:03:24 for the total course
created by Mammoth Interactive INC
- 1. Course overview
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              2. Introduction to Blockchain (Prerequisite)
              
              - 00 Blockchain Introduction - (Prerequisite) Introduction to Blockchain
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                        01 What Are Blockchains And Distributed Ledgers - (Prerequisite) Introduction to Blockchain 
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                        02A What Are Bitcoin And Ethereum - (Prerequisite) Introduction to Blockchain 
 
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              3. Introduction to the Stock Market
              
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                        01 What Do Day Traders Trade - (Pre-requisite) Stock Market 
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                        02 What Is Volatility And Standard Deviation - (Pre-requisite) Stock Market 
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                        03 What Are The Best Assets To Day Trade - (Pre-requisite) Stock Market 
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                        04 Strategies For Stock Market Trading - (Pre-requisite) Stock Market 
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                        06 Stock Market Indicators 
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                        07 Stock Market Lifecycle Trend Phases - (Pre-requisite) Stock Market 
 
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              4. (Prerequisite) Introduction to Python
              
              - 00. Introduction
- 01. Intro To Python
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                        02.01 What is Google Colab 
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                        02.02 What If I Get Errors 
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                        02.03 How Do I Terminate a Session 
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                        01. Variables 
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                        02. Type Conversion Examples 
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                        03. Operators 
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                        04. Collections 
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                        05. List Examples 
 
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              5. Introduction to DataFrames with Pandas Python Library
              
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                        00. Setting Up Pandas - Intro to Dataframes with Pandas Pyplot Library 
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                        01. Creating A Dataframe - 01. Intro to Dataframes with Pandas Pyplot Library 
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                        02. Sorting And Series - 01. Intro to Dataframes with Pandas Pyplot Library 
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                        03. Expanding A Dataframe - 01. Intro to Dataframes with Pandas Pyplot Library 
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                        01 Getting Values And Dealing With Nan Values - 02. Intro to Dataframes with Pandas Pyplot Library 
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                        02 Dropping Rows And Columns - 02. Intro to Dataframes with Pandas Pyplot Library 
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                        01 Reading From Csv - 03. Intro to Dataframes with Pandas Pyplot Library 
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                        02 Writing To Csv - 03. Intro to Dataframes with Pandas Pyplot Library 
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                        01 Starting With An Analysis - 04. Intro to Dataframes with Pandas Pyplot Library 
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                        02 Locating Data By Labels - 04. Intro to Dataframes with Pandas Pyplot Library 
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                        03 Statistical Description Of Data - 04. Intro to Dataframes with Pandas Pyplot Library 
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                        04 Histogram Plots In Pandas - 04. Intro to Dataframes with Pandas Pyplot Library 
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                        05 Starting An Analysis Of All Our Data - 04. Intro to Dataframes with Pandas Pyplot Library 
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                        06 Continuing An Analysis Of All Our Data - 04. Intro to Dataframes with Pandas Pyplot Library 
 
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              6. Introduction to Data Science with NumPy Python Library
              
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                        01. Introduction - 00. Intro to Data Science with Numpy Python Library 
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                        01 Creating And Reshaping Numpy Arrays - 01. Intro to Data Science with Numpy Python Library 
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                        02 Creating Standard Numpy Arrays - 02. Intro to Data Science with Numpy Python Library 
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                        03 Creating Standard 2D Arrays - 01. Intro to Data Science with Numpy Python Library 
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                        04 Attributes On Numpy Arrays - Intro to Data Science with Numpy Python Library 
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                        05 Resizing Arrays - 01. Intro to Data Science with Numpy Python Library 
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                        01 Writing An Array To File And Formating Strings - 02. Intro to Data Science with Numpy Python Library 
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                        02 Random Numbers - 02. Intro to Data Science with Numpy Python Library 
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                        03 Sorting In Numpy - 02. Intro to Data Science with Numpy Python Library 
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                        01 Calculations Within Numpy Arrays - 03. Intro to Data Science with Numpy Python Library 
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                        02 Math Functions With Numpy - 03. Intro to Data Science with Numpy Python Library 
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                        03 Integrating With Numpy - 03. Intro to Data Science with Numpy Python Library 
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                        04 Statistics With Numpy - 03. Intro to Data Science with Numpy Python Library 
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                        05 Polynomials - 03. Intro to Data Science with Numpy Python Library 
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                        06 Polynomials (Cont'd) - 03. Intro to Data Science with Numpy Python Library 
 
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              7. Simple Moving Averages Trading Strategy
              
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                        04-00 Backtesting Simple Moving Averages Explained 
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                        01 Load data for backtesting SMA with vectorbt 
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                        02 Build trading strategies with vectorbt 
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                        03 Simulate portfolio with vectorbt 
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                        04 Visualize trading strategy with kaleido 
 
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              8. Big Three Trading Strategy
              
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                        00 What Is The Big Three Trading Strategy 
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                        01 Big Three Trading Strategy On Binance Coin 
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                        02 Big Three Trading Strategy On 1 Year Of Stocks 
 
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              9. Exponential moving average trading strategy
              
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                        00 Ema Trading Strategy For Crypto - Overview 
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                        01 Load Data With Cryptometrics Api 
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                        02 Visualize Historical Stock Prices With Matplotlib 
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                        03 Build Exponential Moving Average Trading Strategy 
 
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              10. Build autocorrelation for crypto stock prediction
              
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                        00 Autocorrelation Explained For Crypto Stock Prediction 
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                        01 Load Data For Crypto Price Autocorrelation With Pandas 
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                        02 Visualize Crypto Price Data With Pyplot 
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                        03 Apply Hodrick-Prescott Filter To Data With Python 
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                        04 Calculate Autocorrelation With Python 
 
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