The Complete GPT Algorithmic Trading Course: GenAI & Python+
Master algorithmic trading with Python, GPT, and AI. Gain practical skills, boost returns, and thrive in any market with our BUNDLE!
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The information provided in this bundle is for educational purposes only. The content is designed to offer a foundational understanding of algorithmic trading concepts, tools, and techniques.
The course content does not constitute financial advice, investment recommendations, or trading signals. The examples and strategies discussed are hypothetical and should not be interpreted as recommendations for buying or selling any financial instruments.
Risk of Loss: Trading in financial markets, including algorithmic trading, involves substantial risk. You may lose all or more than the initial investment. It is important to understand these risks and be willing to accept them before engaging in any trading activities.
Past Performance: Past performance is not indicative of future results. Any historical performance examples included in this course are for illustrative purposes only and do not guarantee future results.
Research and Due Diligence: You are responsible for conducting your own research and due diligence before making any trading decisions. The course material should be used as a tool to enhance your understanding, but it should not replace independent research and critical thinking.
No Guarantees: The course instructors and creators do not guarantee any specific outcomes, profits, or success from following the course material. Trading success depends on many factors, including market conditions, individual skill, and experience.
Legal and Regulatory Compliance: Ensure that you comply with all applicable laws and regulations in your jurisdiction when trading. This includes understanding the tax implications and legal responsibilities associated with trading.
Caution: Never trade or invest money you cannot afford to lose. The projects included in this bundle are intended solely for testing and educational purposes and should not be used for actual investment activities.
Your Instructor
Team Mammoth
This bundle is a collaborative effort between multiple Mammoth Instructors.
Mammoth Interactive is a leading online course provider in everything from learning to code to becoming a YouTube star. Mammoth Interactive courses have been featured on Harvard’s edX, Business Insider and more.
Over 14 years, Mammoth Interactive has built a global student community with 6+ million courses sold. Mammoth Interactive has released over 1,000 courses and 5,000 hours of video content.
Founder and CEO John Bura has been programming since 1997 and teaching
since 2002. John has created top-selling applications for iOS, Xbox and
more. John also runs SaaS company Devonian Apps, building
efficiency-minded software for technology workers like you.
Course Curriculum
Welcome
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Introduction to Algorithmic Trading
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Code Python on the Web (Intro to Colab)
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Introduction to Python
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Start01. Intro To Python (5:46)
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Start02. Variables (19:17)
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Start02b. Variables Examples (10:42)
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Start03. Type Conversion Examples (10:04)
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Start04. Operators (7:04)
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Start05. Operators Examples (21:52)
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Start06. Collections (8:23)
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Start07. Lists (11:38)
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Start08. Multidimensional List Examples (8:05)
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Start09. Tuples Examples (8:34)
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Start10. Dictionaries Examples (14:24)
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Start11. Ranges Examples (8:30)
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Start12. Conditionals (6:41)
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Start13. If Statement Examples (10:16)
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Start14. If Statement Variants Examples (11:18)
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Start15. Loops (7:00)
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Start16. While Loops Examples (11:30)
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Start17. For Loops Examples (11:18)
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Start18. Functions (7:47)
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Start19. Functions Examples (9:16)
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Start20. Parameters And Return Values Examples (13:46)
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Start21. Classes And Objects (11:13)
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Start22. Classes Example (13:11)
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Start23. Objects Examples (9:54)
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Start24. Inheritance Examples (17:26)
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Start25. Static Members Example (11:03)
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Start26. Summary And Outro (4:06)
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StartSource code
Disclaimer - Use Caution for Safe Trading
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Advanced Machine Learning Techniques for Algorithmic Trading
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High-Frequency Trading Strategies
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Portfolio Optimization and Risk Management
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Sentiment Analysis and NLP for Algorithmic Trading
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Start01 Introduction to Sentiment Analysis and NLP for Algorithmic Trading
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Start02 Data Collection and Processing for Sentiment Analysis
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Start03 Sentiment Analysis Techniques
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Start04 01 Integrating Sentiment Analysis and Back Testing (19:07)
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Start04 02 Finishing up script and Testing (16:58)
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StartResources
Starting on Quantitative Finance
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Compute returns from prices
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Start00a Stock Prices and Calculating Returns
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Start00b Complete Commented Project Code
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Start01 Calculate Stock Returns with Python (4:34)
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Start02a Stock Analysis with Pandas
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Start02b Use Pandas DataFrame for Multiple Stocks (3:58)
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Start03a Analyzing CSV Data
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Start03b Read Data from a CSV File in Python (3:04)
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Start04a Compounding and Annualizing Returns
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Start04b Compound and Annualize Returns in Python (4:28)
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StartSource Files
Analyze Volatility and Returns of Stock Portfolios
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Start00 Full Commented Project Code - Analyze Volatility and Returns of Stock Portfolios
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Start01a Understanding stock portfolio data
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Start01b Clean and visualize data with Python (4:40)
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Start02a Understanding volatility and standard deviation
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Start02b Calculate volatility with Python (3:49)
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Start03a Annualized volatility
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Start03b Annualize volatility and returns in Python (5:04)
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Start04a Is the Return Worth the Risk? 😨 🎲 💰 Use the Sharpe Ratio to Decide
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Start04b Calculate Sharpe Ratio for risk-adjusted return in Python (2:56)
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StartSource files
Time Series Manipulation and Drawdown Analysis in Python
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Start00a Project Introduction - Time Series Manipulation and Drawdown Analysis in Python
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Start00b Complete Commented Project Code
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Start01 Data Loading and Preprocessing (4:26)
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Start02 Change Timestamp to Datetime (5:36)
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Start02a Understanding Data Types - Timestamp and Datetime
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Start03 Calculate Drawdowns (3:56)
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Start03a Understanding Drawdowns
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StartSource files
Calculate Measures of Downside Risk with Python
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Start00a Project Preview - Measures of Downside Risk with Python
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Start00b Complete Commented Project Code
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Start01 Load Hedge Fund Data in Python (3:19)
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Start02a Understanding the Semideviation Downside Risk
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Start02b Calculate Semideviation in Python (2:36)
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Start03a Exploring Value at Risk Metric for Risk Assessment
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Start03b Calculate Value at Risk in Python (3:36)
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Start04a Conditional Value at Risk as a Tool for Measuring Downside Risk
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Start04b Calculate Conditional Value at Risk in Python (3:22)
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Start05a Examining the Role of Parametric Gaussian Value at Risk in Assessing Downside Risk
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Start05b Calculate Parametric Gaussian Value at Risk in Python (1:34)
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Start06a Interpreting Cornish-Fisher Modification as a Metric for Downside Risk Evaluation
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Start06b Calculate Cornish-Fisher Modification in Python (9:42)
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StartSource files
Efficient Frontier Data Analysis and Visualization in Python
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Start00a Project Preview - Efficient Frontier Data Analysis and Visualization in Python
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Start00b Complete Commented Project Code
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Start01 Load Industry Portfolio Monthly Returns mock data in Python (2:57)
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Start02a Annualized Returns and Covariance for Efficient Frontier
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Start02b Calculate Annualized Returns and Covariance (3:32)
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Start03a Weights in Efficient Frontier Analysis
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Start03b Define weights (2:55)
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Start04a Understanding returns formula with weights
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Start04b Calculate portfolio returns (3:26)
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Start05a Understanding volatility formula with weights
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Start05b Calculate portfolio volatility (2:59)
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Start06a Understanding the Efficient Frontier
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Start06b Visualize Efficient Frontier (3:43)
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Start07a Capital Market Line and Tangency Portfolio
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Start07b Plot the Capital Market Line in Python (4:45)
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Start08 Visualize tangency portfolio in Python (7:30)
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StartSource Files
Build Constant Proportion Portfolio Insurance Algorithm in Python
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Start00a Project Preview - Portfolio Insurance Dynamic Risk Budget Algorithm
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Start00b Complete Commented Project Code
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Start01 Load Industry Returns, Firms and Size Data (3:03)
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Start02a Understanding the total market index
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Start02b Calculate the total market index (2:48)
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Start03a Understanding parameters for our Portfolio Insurance strategy
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Start03b Define initial values (5:54)
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Start04a Steps of the Constant Proportion Portfolio Insurance (CPPI) strategy
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Start04b Backtest the Strategy (11:27)
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Start05 Visualize results (8:12)
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StartSource files
Quantitative Trading
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Simulate a stock trading strategy with Z-score
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Start00a Project Preview - Simulate a stock trading strategy with Z-score
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Start00b Complete Commented Project Code
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Start01 Generate Single Stock Data with Python in Colab (7:00)
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Start02 Calculate cumulative moving average of stock price (1:26)
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Start03 Simulate Trading Strategy with ZScore (5:34)
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StartSource files
Mean Reversion on Stock Portfolio
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Simulate and Predict Interest Rates and Bond Prices Like a Pro with Python
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Start00a Project Preview - Simulating interest rates with mean-reversion
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Start00b Complete Commented Project Code
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Start01 Build initial conditions for simulating interest rates (7:21)
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Start02a Understanding bond prices
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Start02b Set Up Bond Prices (10:24)
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Start03a Understanding Cox-Ingersoll-Ross algorithm
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Start03b Calculate bond prices with the Cox-Ingersoll-Ross (CIR) model (4:06)
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Start04 Convert instantaneous interest rates to annualized rates- (4:50)
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StartSource Files
Trading Strategies and Techniques - Introduction To The Course
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Interactive Brokers API Trading
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Start01 01 Setting Up Our Dependencies (8:15)
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Start01.02 Connecting To The IKBR Desktop App (12:39)
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Start01.03 Grabbing Previous Candle Data (16:36)
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Start01.04 Grabbing Current Candle Data (WITH SUBSCRIPTION) (6:45)
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Start01.05 Grabbing Current Candle Data (WITHOUT SUBSCRIPTION) (5:17)
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Start01.06 Performing TA On A Candle (14:48)
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Start01.07 How To Place Orders (13:56)
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Start01.08 Bracket Orders & Putting Everything Together (13:22)
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StartSource Files
Real-Time Stock Data Acquisition: Cutting-Edge Strategies for Market Analysis
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Start01 01 Introduction To yFinance & Real Time Data (11:29)
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Start01.02 Grabbing & Interpreting yFinance Data (20:25)
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Start01.03 Setting Up Our Web Scraper Environment (8:14)
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Start01.04 Introduction To Finviz and Basic Scraping (14:52)
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Start01.05 How To Deal With Pagination For Web Scraping (15:17)
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Start01.06 Putting Our Scraped Data Into Excel (22:06)
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StartSource Files
Tradingview & Pinescript
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Options 101
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Start01 01 What Are Options + Benefits & Drawbacks (11:59)
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Start01.02 Options Terminology (5:19)
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Start01.03 Buying Vs Selling Options (5:20)
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Start02.01 What Is Delta (7:11)
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Start02.02 What Is Gamma (6:31)
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Start02.03 What Is Theta (6:09)
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Start02.04 What Is Vega (4:15)
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Start02.05 What Is Rho (3:17)
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Start03.01 Common Options Strategies (10:00)
Market Basics
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Orders And Prices
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Technical Analysis
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Start01.01 What Is Technical Analysis (10:37)
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Start01.02 Charts And Candlesticks (20:59)
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Start01.03 Trends, Support And Resistance (7:41)
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Start01.04 Chart Patterns (7:10)
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Start01.05 Volume (9:57)
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Start01.06 Bollinger Bands (7:25)
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Start01.07 Relative Strength Index (10:21)
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Start01.08 Average True Range (5:01)
Fundamental Analysis
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Start01.01 What Is Fundamental Analysis (15:43)
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Start01.02 Financial Statements (13:58)
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Start01.03 Fundamental Ratios (4:39)
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Start01.04 Current Vs Expected (2:46)
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Start01.05 Growth Vs Value Companies (4:59)
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Start01.06 Trend Analysis (8:18)
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Start01.07 Benchmarking (7:30)
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Start01.08 Dividend Discount Model (13:19)
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Start01.09 Stock Splits (5:45)
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Start01.10 Other Metrics (4:22)
Risk And Money Management
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Day Trading - Introduction To The Course
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Day Trading Fundamentals
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Stock Analysis For Day Trading
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Start01 Risk And Account Management (4:11)
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Start02 How To Choose The Right Stock (13:46)
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Start03 Scale Out Your Trade (2:38)
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Start04 How To Use Stock Screeners (3:33)
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Start05 Important Indicators To Use (5:43)
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Start06 Get Trading Signals From Indicators (5:56)
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Start07 Use A Trading View Platform (3:53)
Strategies And Tools (With Practical Examples)
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Open Price Gaps Strategy
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Equity Dilution Strategy
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Dividend Cuts Strategy
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Cryptocurrency Trading - Introduction To The Course
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Cryptocurrency Fundamentals
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Start01 Introduction Of Crypto Currencies (4:32)
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Start02 Introduction Of Bitcoin (7:06)
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Start03 Introduction Of Ethereum (2:25)
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Start04 Inroduction Of Altcoins (1:30)
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Start05 Introduction Of Multiplier (2:25)
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Start06 Difference Of Fiat And Satoshi (7:21)
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Start07 Difference Of Coin And Token (6:31)
Crypto Investing Fundamentals
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Start01 Most Profitable Cryptocurrencies (8:48)
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Start02 Where To Find Cryptocurrency Data (0:35)
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Start03 Tips For Investing (10:17)
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Start04 Warnings About Investing (3:33)
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Start05 Invest In A Coin Long-Term (2:43)
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Start06 Invest In A Coin Short-Term (3:44)
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Start07 When To Buy And Exit (1:46)
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Start08 Maximize Gains (2:00)
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Start09 Spot Hidden Coins (3:33)
Buy Your First Cryptocurrency
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Criteria For Investing
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Buying Strategies
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Technical Analysis - Crypto Trading Tactics
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Profitable Types Of Cryptocurrency
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How To Cash Out
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DeFi Crypto Investing And Yield Farming
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NFT Cryptos
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Invest In ICOs
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Options Trading - Introduction To The Course
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Introduction To Call And Put Options
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Start01. What Are Options (6:30)
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Start02. Practical Example With A Stock (4:42)
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Start03. Introduction To Call Options (1:40)
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Start04. Practical Example Of A Call Option (4:28)
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Start05. What Are In-The-Money (ITM), At-The-Money (ATM) And Out-Of-The-Money (OTM) Options (4:24)
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Start06. Buyer And Seller Risk Profiles (4:21)
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Start07. Risk Graphs (5:57)
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Start08. Option Chain And Quote Screen (3:04)
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Start09. Practical Stock Example - Choice Of Expiry Series And Itm, Atm And Otm Options (8:04)
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Start10. Call Option Performance In Real-Time And On The Day Of Expiry (4:58)
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Start11. Risk Graphs Of Itm, Atm And Otm Options (1:35)
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Start12. Option Sellers Risk Profile (5:10)
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Start13. Real-World Example Of Put Options (3:08)
Introduction To Time Decay
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Implied Volatility
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Option Greeks
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Basic Strategies
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Options Spreads - Monthly Income Strategies
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Start01. Bull Call Spread Strategy (13:28)
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Start02. Bull Put Spread Strategy (8:42)
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Start03 Bear Call Spread Strategy (8:03)
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Start04. Bear Put Spread Strategy (6:48)
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Start05. Call Back Spread Strategy (4:56)
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Start06. Profitable Condition For Call Back Spread (10:04)
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Start07. Put Back Spread Strategy (3:48)
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Start08. Profitable Condition For Put Back Spread Strategy (7:37)
Neutral Strategies
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Volatile Strategies
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Financial AI and ChatGPT Applications
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Build your first ChatGPT AI prompts with Prompt Engineering - Intro to prompt engineering
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Build your first prompts
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Predict stock performance with ChatGPT
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Start01 Course Requirement (3:20)
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Start02 Project Preview (2:03)
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Start02A Analyze Financial Statements Of Stock (9:00)
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Start02B Financial Ratio And Trend Analysis (4:25)
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Start03 Balance Sheet, Income Statement And Cash Flow Statement (9:00)
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Start04 Loopholes And Weaknesses In Stock Financials (8:39)
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Start05 Analyze Historical Stock Performance (11:16)
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Start06 Predict Stock Performance (5:08)
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StartSource Files
Stock Analysis with ChatGPT
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Start01 Market Share (5:31)
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Start02 Industry Analysis (7:48)
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Start03 Management Team Analysis (8:25)
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Start04 Analyze Stock Risks (6:56)
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Start05 Valuation (8:11)
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Start06 Explain Business Model Of A Company (6:24)
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Start07 Perform A Swot Analysis (8:16)
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Start08 Summarize A Company’s Earnings Report Calls (6:55)
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Start09 Evaluate A Company’s ESG Credentials (4:39)
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StartSource Files
Build an Investment Plan with ChatGPT
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Start01 Project Preview (0:48)
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Start02A Invest Short Term (6:22)
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Start02B Implementing Your Short-Term Investment Strategy (8:06)
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Start03A Invest Long Term (5:58)
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Start03B Analyzing The Results (7:27)
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Start04A Using Chatgpt To Assess Your Risk Tolerance (7:32)
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Start04B Customized Investment Recommendations Based On Individual Financial Goals And Risk Tolerance (5:26)
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Start04C Implementing Your Customized Investment Plan (8:47)
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StartSource Files
Stock Market Prediction and Risk Analysis with ChatGPT
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Start01 Project Preview (1:25)
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Start02A Recent Past Stock Market State (7:44)
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Start02B Analyzing Past Trends And Economic Events (9:24)
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Start03 Present Stock Market State (6:29)
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Start04A Future Stock Market State (8:12)
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Start04B Insights On Macroeconomic Factors (7:09)
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Start05 Project Preview (2:22)
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Start06 Analyze Credit Scores (7:56)
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Start07 Assess Loan Applicant Risk (7:35)
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StartSource Files
Trading Strategies, Sentiment Analysis and Fraud Detection with ChatGPT
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Start01 Project Preview (1:12)
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Start02 Pick Stocks With Company Evaluation (6:00)
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Start03A Build A Trading Strategy (8:54)
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Start03B Test Trading Hypthothesis (8:29)
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Start04 Project Preview (1:03)
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Start05 Chatgpt And Sentiment Analysis (8:52)
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Start06 Analyzing Sentiments On Social Media Posts (8:45)
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Start07 Project Preview (1:03)
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Start07A Fraud Detection With Chatgpt (7:37)
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Start07B Detecting Exploitation Prone Weaknesses (8:01)
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Start08A Red Flags And Anomaly Detection (6:07)
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Start08B Anomaly Detection Techniques (8:01)
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Start09 Conclusion (2:20)
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StartSource File
CoPilot Prompt Engineering in Excel - Unleash Data with AI
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Start00 Course Overview (1:51)
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Start01 Overview (2:03)
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Start02 Microsoft-s Approach to AI (3:42)
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Start03 Microsoft-s AI-Enhanced Productivity Tools (3:26)
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Start04 Copilot for Microsoft 365 (5:20)
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Start05 Data Considerations (2:14)
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Start06 Copilot Interaction for Microsoft 365 (4:18)
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Start07 Recap (1:36)
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Start08 Overview (1:49)
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Start09 Accessing Copilot in Excel (3:07)
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Start10 Insight Identification (15:50)
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Start11 Managing Data with Copilot (9:37)
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Start12 Generating Formulas (11:05)
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StartSource Files
Prompt Engineering with Microsoft Copilot - Mastering Prompts for Personalized Results
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Start00 Course Overview (1:48)
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Start01 Overview (1:00)
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Start02 Understanding Copilot (3:51)
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Start03 Accessing Microsoft Copilot (2:39)
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Start04 What to Keep in mind (2:52)
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Start05 Recap (0:51)
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Start06 Overview (1:07)
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Start07 The Interface (19:18)
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Start08 Understanding Copilot Prompts (1:27)
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Start09 Interaction with Copilot (5:38)
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Start10 Recap (1:10)
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Start11 Overview (1:23)
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Start12 Copilot- Answers & Create (36:56)
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Start13 Image Prompting (13:24)
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Start14 Prompting Advance Tasks (21:10)
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Start15 Recap (1:42)
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StartResources
Python and AI Integration
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Ollama LLM Comprehensive Guide - Enhancing AI Conversations and Integrating with Python
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Customize Ollama Models
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Start01 Build More Creative Ollama Llm With Higher Temperature (4:07)
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Start02 Customize Sentiment Analyzer With Template (4:31)
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Start03 Customize Model With Reusable System Prompt (3:26)
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Start04 Customize Model With Template (5:37)
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Start05 List And Delete Custom Ollama Models (1:10)
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StartResources
Customize Ollama Model for Sentiment Analysis
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Connect to Ollama with Python Client
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(Prerequisite) Introduction to HTML
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Start01. Course Requirements (2:56)
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Start02. What Is JSbin (3:15)
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Start03. Setting Up The HTML Document (2:41)
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Start04. Header Tags And Paragraphs Tags (4:06)
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Start05. Styles (3:32)
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Start06. Bold Underline And Italic Tags (3:10)
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Start07. Adding In A Link (1:38)
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Start08. Adding In A Image (3:01)
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Start09. Adding A Link To An Image (1:55)
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Start10. Lists (4:03)
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Start11. Tables (3:29)
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Start12. Different Kinds Of Input (4:59)
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Start13. Adding In A Submit Button (3:01)
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Start14. Scripts And Style Tags (3:27)
How OpenAI API Works
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Build your first OpenAI API queries with Python
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Build OpenAI API queries for to automate coding tasks
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Use OpenAI API to automate data science tasks
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Use OpenAI API to automate copywriting with GPT Turbo
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Use OpenAI API to automate marketing with GPT Turbo
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Start01 Classify Text Emotion Sentiment With ChatGPT Models (5:09)
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Start02 Extract Keywords From Text With ChatGPT API (4:31)
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Start03 Convert Product Description To Ad With ChatGPT Python (3:57)
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Start04 Generate Product Names With ChatGPT In Python (4:04)
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Start05 Extract Information From Text With ChatGPT API (2:57)
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StartSource files
Scrape web data in text form with Python
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Process web data for OpenAI machine learning
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Start01 Convert Text To CSV With Python (6:36)
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Start02 Remove Whitespace And Lines From Text With Python (4:58)
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Start03 Tokenize Text With Python For Machine Learning Models (2:50)
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Start04 Split Long Lines With Python (4:11)
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Start05 Split Pandas Dataframe Into Sections With Python (7:19)
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Start06 Embed Text For Machine Learning With OpenAI API (8:05)
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StartSource files
Customize OpenAI model to learn from your data
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Answer questions about PDF with ChatGPT model in Python
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Transcribe Video
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Video analysis with OpenAI's Vision Model
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Start00 Project Preview - AI Video Voiceover Generator App (2:25)
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Start01 Encode Video For Openai API (8:14)
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Start02 Describe Video With Openai API (5:02)
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Start03 Generate Video Voiceover Script With OpenAI (5:21)
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Start04 Generate Mp3 Audio From Script With OpenAI Speech (6:31)
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Start05 Combine Video And Audio With Python (6:03)
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Start06 Build User Interface For AI Video Narration App (6:25)
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Start07 Generate Voiceover Upon Video Submission (8:48)
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StartResources
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Improve web clone results with prompt engineering
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Extracting information from input in structured manner
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Build Python Projects with OpenAI
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Start01. Initial installation and configuration (7:02)
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Start02. Benefits of clear prompts (7:02)
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Start02.01 Making A Simple Chat Bot App (12:36)
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Start03. Image Generation Using Python And ChatGPT (11:35)
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Start04.01 Transcribing Speech To Text (8:46)
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Start04.02 Translating Speech To English (6:42)
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StartSource Code
Build a ChatGPT Clone with Python Custom UI
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Test Your Knowledge
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StartPractice Exam - Build coding and data science AI apps with OpenAI Python API
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StartPractice Exam - Build custom OpenAI ChatGPT API Python apps with embeddings
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StartPractice Exam - Build AI Applications with OpenAI Vision and Whisper
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StartPractice Exam - Master OpenAI with GPT Assistants, Function Calling and JSON Mode
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StartPractice Exam - Build Python Projects with OpenAI
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StartPractice Exam - Build a ChatGPT Clone with Python Custom UI
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StartPractice Exam - Build a Screenshot to Code OpenAI Python App
Introduction to Prompt Engineering with LangChain
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Start01 Introduction to LangChain - A Comprehensive Framework for LLM Applications
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Start01b Understanding LangChain for Language Model Applications
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Start02 Set up LangChain project in Jupyter Notebook with Anthropic (6:27)
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Start03 Understanding retrieval chains in LangChain
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Start04 Build a Retrieval Chain with LangChain and OpenAI (6:48)
Automate prompt to function pipeline with LangChain tool calling
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Dataset Generation with LangChain Python for Synthetic CSV Data Analysis
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Start01 Build a Data Model (5:53)
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Start02 Build sample data for synthetic generation in Python (5:36)
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Start03 Build a prompt template for data generation LLM (4:31)
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Start04 Build a data generator with LangChain OpenAI Python SDK (3:17)
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Start05 Generate synthetic data with LangChain OpenAI in Colab (4:19)
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Start06 Save list to CSV in Python (9:15)
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StartSource Files
Automate CSV Data Analysis with LangChain OpenAI Python SDK
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Mastering Google Gemini - Google Gemini Large Language Model API Essentials
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Start01 Connect to Google's Gemini API with Python
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Start01b Install Gemini and Add Secret API Key to Colab (3:04)
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Start02 Exploring Gemini API - Model Selection and Capabilities
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Start02b List content generation models with Gemini Python SDK (1:57)
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Start03 Leveraging the Gemini API for Text Generation
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Start03b Send a request to Gemini with Python SDK (3:51)
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Start04 Multimodal Content Generation with Gemini API
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Start04b Caption an image with Gemini Python SDK (4:41)
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Start05 Mastering Conversations with Gemini's Chat API and Python
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Start05b Build chat session with Gemini Python SDK (2:23)
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Start06 Maximizing Model Performance - Token Count Management in the Gemini API
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Start06b Count tokens with Gemini Python SDK (1:50)
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Start07 Harness the Power of Text Embeddings with Gemini API
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AI App Development Mastery - Build with Gemini Python SDK and Practice Exam
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Start01 Integrating Gemini with Function Calling in Python
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Start01b Set up function calling project with Gemini Python SDK (5:56)
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Start02 Use the Gemini Pro Model for API Calls in Python
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Start02b Build function call with Gemini Python SDK (4:53)
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Start03 Build Complex Function Calls in APIs
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Start03b Execute external API function call with Gemini Python SDK (10:18)
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Start04 Integrate Function Calls in Chat Sessions with Gemini
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Start04b Simulate function calls in chat session with Gemini Python SDK (8:26)
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An Intro to Gemini as Virtual Assistant
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Advanced Techniques with Claude AI API - Prompt Engineering for Claude LLM with Anthropic API
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Advanced Chatbot Prompting Techniques with Claude Anthropic API
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Start01 Engineer Complex Prompts from Scratch
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Start01b Hands-on connect to Anthropic API (8:11)
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Start02 Chain Multiple Prompts
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Start02b Hands-on chain prompts with Anthropic Python SDK (2:26)
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Start02c Building System Prompts
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Start03 Function calling or tool use with Claude
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Start03b Hands-on function calling with Anthropic Python SDK (17:21)
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Start03c Format result for Claude tool (10:47)
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StartPractice Exam
Master Computer Vision with Claude AI Python SDK
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Start01 Describe an image with Claude Vision Python SDK
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Start01b Hands-on image captioning with Anthropic Python SDK (5:02)
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Start02 Compare multiple images with Claude and Python
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Start02b Hands-on image comparison with Anthropic Python SDK (6:00)
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Start03 Understanding Claude Vision capabilities
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StartPractice Exam
Transform Data into Insights - AI PDF Analysis and Data Visualization in Claude, Python and Matplotlib
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Start00 Project setup
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Start00b Set up Anthropic PDF project in Colab (3:18)
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Start01 Encode PDF to image for Claude with Python
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Start01b Hands-on encode PDF in Anthropic Python SDK (6:38)
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Start01c Convert question to high-quality prompt (4:33)
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Start02 Extract information from PDFs
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Start02b Hands-on PDF analysis with Anthropic Python SDK (4:37)
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Start03 Generate Matplotlib code with Claude
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Start04 Hands-on Pyplot generation with Anthropic Python SDK (7:25)
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StartSource files
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Advanced Claude Prompt Engineering - Innovate in Voyage AI with Python
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Start01 Why every prompt engineer must understand embeddings
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Start02 Overview of Embeddings with Anthropic
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Start03 Getting Started with Voyage AI
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Start04 Use the Voyage Python Package for Text Embeddings
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Start05 Access Text Embeddings via Voyage HTTP API
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Start06 Practical Application of Voyage Embeddings - A Semantic Search Example
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Start06b Hands-on build embeddings with Voyage Python SDK (6:52)
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Start07 Accessing Voyage Embeddings on AWS Marketplace
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Claude AI Applications and Training - Advanced Personal Assistant
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Communication and Coordination
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Personalized Learning and Development
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Claude Chatbot Prompting Strategies with Anthropic API
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Start01 Delegating Tasks through Role Prompting
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Start02 Separate Data and Instructions
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Start02b Hands-on chat to Claude with Anthropic Python SDK (6:36)
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Start03 Format Output and Customize Claude Chatbot Model
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Start03b Hands-on format outputting in Anthropic Python SDK (6:52)
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StartPractice Exam
An Intro to Document Analysis and Management with Claude AI
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Automated Document Sorting and Organization
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An Intro to Education with Claude AI
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Assessment and Feedback
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Claude AI Assisted Learning
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Tutoring and Knowledge Reinforcement
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An Intro to Claude AI Innovative Sales Assistant
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Data-Driven Sales Strategies
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Enhancing Customer Interaction
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Streamlining Sales Processes
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Training and Onboarding
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Foundations of Machine Learning and AI for Everyone
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StartDecoding Machine Learning: From Birth to Modern Applications
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StartThe Landscape of Machine Learning Strategies
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StartMachine Learning Algorithms - An In-Depth Exploration
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StartExploring Decision Trees and Random Forests in Machine Learning
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StartThe Intricacies of Neural Networks: An Insight into AI's Brain
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Cutting-Edge AI - Advanced Techniques and Emerging Technologies
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StartUnraveling the AI Revolution - An Exploration of AI in Consumer Technology
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StartInnovating Business Practices Through AI
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StartEthics in AI - Navigating the Human-AI Interaction
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StartSociety and AI - Navigating a New Era
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StartThe AI Revolution - Manufacturing and Retail Transformed
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StartArtificial Intelligence in Healthcare - Transforming Patient Care and Medical Practice
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StartAI Transforms The Financial Sector - Risk Assessment, Trading, and Client Services
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StartArtificial Intelligence Redefining Logistics Efficiency
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The Future is Now - AI in Modern Industry and Beyond
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StartUnveiling the Power of Advanced AI Algorithms
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StartHarnessing Big Data for Transformative Advances in AI
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StartAddressing the Major Challenges in AI Development
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StartExploring Advanced AI Algorithms - From Reinforcement Learning to Transfer Learning
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StartFuture of Artificial Intelligence - An Exploration of Key Trends
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StartThe Ethical Dimensions of Artificial Intelligence - Shaping the Future
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StartExploring Quantum Leap - The Next Phase in AI's Evolution
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StartEnvisioning an AI-Driven Tomorrow
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AI at Work - Applications and Industry Transformations
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StartUntangling the Web of AI Jargon - A Comprehensive Guide
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StartInspiring Tales of AI Transformations
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StartLearning from AI Missteps - A Journey Through Past Failures and Insights
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StartDeep Learning Exploration - Unveiling Machine Intelligence
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StartReinforcement Learning - Mimicking Interactive Learning from Environment
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StartExploring Generative Models - Concepts, Applications, and Future Possibilities
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StartUnderstanding Natural Language Processing - The Language of Artificial Intelligence
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AI in Action - Specialized Applications Across Sectors
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StartTransforming the Spectrum of Healthcare with AI
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StartHarnessing AI for Strategic Decision-Making in Finance
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StartArtificial Intelligence - The Backbone of Smart and Sustainable Cities
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StartUnderstanding Edge AI - Unleashing Intelligence at the Source of Data
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StartUnderstanding Feret and the Evolution of AI-empowered Computer Vision
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Python Data Science and Machine Learning for Financial Analysis - Compare stock performance with Python
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Course Overview
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Introduction to Machine Learning (Prerequisite)
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Project - Classify Review Sentiment
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Course overview
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Introduction to Blockchain (Prerequisite)
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Introduction to the Stock Market
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Start01 What Do Day Traders Trade (9:45)
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Start02 What Is Volatility And Standard Deviation (3:33)
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Start03 What Are The Best Assets To Day Trade (4:53)
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Start04 Strategies For Stock Market Trading (2:37)
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Start06 Stock Market Indicators (1:56)
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Start07 Stock Market Lifecycle Trend Phases (2:20)
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StartSource Files
Introduction to DataFrames with Pandas Python Library - Setup
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Introduction to DataFrames with Pandas Python Library - Datastructures
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Introduction to DataFrames with Pandas Python Library - 02. Manipulating DataFrames
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Introduction to DataFrames with Pandas Python Library - 03. Reading and Writing Data
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Introduction to DataFrames with Pandas Python Library - 04. Analytical Approaches to Data
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Introduction to Data Science with NumPy Python Library - Introduction
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Numpy Arrays
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Manipulating Numpy Arrays
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Calculations and Math
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Analyze and visualize stock returns with Pandas, NumPy and Pyplot
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Stock Portfolio Analysis with Python
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Start00 Project Overview - Stock Portfolio Analysis With Python (2:35)
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Start01 Build A Stock Portfolio (3:03)
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Start02 Calculate Stock Portfolio Performance With Python (6:36)
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Start03 Visualize Crypto Portfolio Returns With Pyplot (3:41)
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Start04 Analyze Stock Portfolio Returns With Data Science (6:32)
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Start05 Calculate Expected Cryptocurrency Returns With Pandas (3:04)
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Start06 Visualize Stock Drawdowns With Python (4:13)
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StartSource Files
Build a Trading Strategy with Indicators
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Start01 Build Sma And Ema With Ta-Lib (4:46)
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Start02 Calculate Bollinger Bands For Crypto Stock (5:00)
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Start03 Calculate Rsi For Stocks With Python (4:25)
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Start04 Calculate Obv For Crypto Price Prediction With Python (5:02)
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Start05 Calculate Moving Average Convergence Divergence (3:21)
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StartSource Files
Time Series Stock Forecasting on Crypto with Python
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Calculate stock risk and return with Python
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The Complete Recommender Systems Masterclass - Build 7 Projects
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Start00-01 Introduction To Recommender Systems (9:08)
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Start00-02 How To Evaluate Recommender Systems (14:54)
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Start00-03 Content Based Recommendations (4:37)
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Start00-04 Neighborhood Based Collaborative Filtering (2:22)
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Start01-00 Project Preview (1:59)
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Start01-01 Load Data As Pandas Dataframes (12:17)
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Start01-02 Merge Movies And Ratings Dataframes (8:30)
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Start01-03 Build A Correlation Matrix (6:20)
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Start01-04 Test The Recommender (6:55)
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StartCourse Source Files
Projects Preview - Machine Learning Movie Recommender
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Machine Learning Fundamentals
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Introduction to User Similarity
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Recommend a Movie Based on User Similarity
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Recommend a Movie with a K Nearest Neighbors Classifier
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Project Preview - Complex Machine Learning Recommender
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Data Processing Profiles and Items
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Build Models for User Recommendations
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Start01 What Is Regression (19:55)
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Start02 Regression Introduction (8:58)
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Start03 Build A Ridge Regression Model (13:43)
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Start04 Evaluate Model Error (7:04)
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Start05 Visualize Top Features Affecting Rating (11:27)
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Start06 Build A Lasso Regression Model (8:01)
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Start07 Visualize Top Features From Lasso Regression (8:07)
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Start08 Determine Which Model Is Best (3:28)
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StartSource Files
Build a Model to Predict Ratings
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Deep Learning Fundamentals
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Build a Neural Network to Predict Ratings
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Data Analysis with Pandas, Numpy and Sci-kit Learn
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Start00 Project Preview (2:38)
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Start01 Load Data Into Dataframes (5:28)
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Start02 Explore Data In Our Dataset (3:49)
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Start03 Build A Rating Pivot Table (5:22)
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Start04 Calculate Average Rating Of A Movie (5:51)
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Start05 Find Ratings For A Movie In Every Slice (6:17)
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Start06 Find Rating Averages For Every Movie In The Slice (7:54)
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Start07 Build An Average Ratings Column (13:25)
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StartSource Files
Course overview - Python Crypto Machine Learning
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Overview of Regression Models (Prerequisite)
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Support Vector Machine Machine Learning (Prerequisite)
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Numpy Arrays
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Manipulating Numpy Arrays
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Calculations and Math
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Compare regression techniques for crypto machine learning
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Decision Tree Machine Learning (Prerequisite)
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Trees - Compare regression techniques for crypto machine learning
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Build an AdaBoost machine learning model for stock prediction
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Start01 Project Overview - Adaboost Stock Prediction (7:28)
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Start01b What Is Ada Boost (5:48)
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Start02 Build Stock Dataset For Machine Learning (5:33)
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Start03 Build An Adaboost Regression Machine Learning Model For Stock Prediction (6:47)
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Start04 Find Best Ml Model With Optimal Number Of Estimators (15:18)
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StartAdaBoost Source Files
Overview of Classification Models
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Compare classification models for crypto machine learning
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Start00 Project Overview - Classification Machine Learning For Crypto Stocks (7:05)
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Start01 Load And Prepare Crypto Data In Colab (8:32)
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Start02 Build Classification Models To Predict Stock (7:59)
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Start03 Build Tree Classification Models To Predict Crypto Price (3:25)
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Start04 Compare Classification Model Results With Numpy And Pandas (3:51)
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StartClassification source files
Build a Support Vector Machine to Predict Trading
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Start01 Load Yfinance Data Into Colab (4:10)
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Start02 Build Trading Signals With Sma Windows (3:50)
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Start03 Calculate And Visualize Strategy Returns (2:48)
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Start04 Prepare Data For Machine Learning (6:40)
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Start05 Build A Support Vector Classifier With Sklearn (3:01)
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Start06 Calculate And Visualize Returns From Model (4:08)
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StartSVM Source files
Trading Bot Masterclass - Course Overview
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Scrape and Process Tweets
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Tweet Sentiment Analysis
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Buy Cryptocurrency Algorithmically - Test with Sandbox
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Buy Cryptocurrency Algorithmically - Real Coins
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Buy Doge with Kraken API
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Run Bot All Day
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Data Analysis - Other Cryptos Affected by Tweets
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How to Expand Bot
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Stock Market Data Analysis and Visualization with Python, Pandas, NumPy, Seaborn and Matplotlib
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Compare Stocks and Returns
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Calculate and Visualize Risk
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Build a Stock Ticker Dashboard Web App with Python, Dash and Pandas
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Build a Stock Ticker Website
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Preprocess Twitter Sentiment and Stock Prices Data
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Build a Random Forest Classifier Machine Learning Model
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-
Start00 Project Preview (2:27)
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Start01 What Is The Random Forest Classifier Model (5:42)
-
Start02-03 Processing And Sorting Sentiment Data (14:40)
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Start04 Calculate Stock Trend (Rising Or Falling) (8:16)
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Start05 Build A Binary Encoding Of Sentiment (5:14)
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Start06 Split And Scale Data (13:56)
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Start07 Build A Random Forest Classifier Model (13:06)
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Start08 Evaluate The Model (6:48)
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StartSource Files
Build a Gradient Boosting Classifier
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Course overview - Python Crypto Trading Strategies
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Introduction to the Stock Market
Available in
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-
Start01 What Do Day Traders Trade (9:45)
-
Start02 What Is Volatility And Standard Deviation (3:33)
-
Start03 What Are The Best Assets To Day Trade (4:53)
-
Start04 Strategies For Stock Market Trading (2:37)
-
Start06 Stock Market Indicators (1:56)
-
Start07 Stock Market Lifecycle Trend Phases (2:20)
-
StartSource Files
Introduction to Data Science with NumPy Python Library - 00. Introduction
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Numpy Arrays
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Manipulating Numpy Arrays
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Calculations and Math
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Introduction to DataFrames with Pandas Python Library - 00. Setup
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Datastructures
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Manipulating DataFrames
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Reading and Writing Data
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Analytical Approaches to Data
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Simple Moving Averages Trading Strategy
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Big Three Trading Strategy
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Exponential moving average trading strategy
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Start00 EMA Trading Strategy For Crypto - Overview (2:57)
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Start01 Load Data With Cryptometrics API (7:53)
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Start02 Visualize Historical Stock Prices With Matplotlib (6:31)
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Start03 Build Exponential Moving Average Trading Strategy (3:54)
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Start04 Visualize Trading Strategy With Kaleido (4:40)
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StartSource Files
Build autocorrelation for crypto stock prediction
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Start00 Autocorrelation Explained For Crypto Stock Prediction (2:45)
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Start01 Load Data For Crypto Price Autocorrelation With Pandas (5:52)
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Start02 Visualize Crypto Price Data With Pyplot (3:14)
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Start03 Apply Hodrick-Prescott Filter To Data With Python (4:10)
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Start04 Calculate Autocorrelation With Python (3:25)
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StartAutocorrelation Source Files
Algorithmic Trading with Python, Statistics and Pandas - Build Investing Strategies
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Build Your First Investing Strategy
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Find 50 Best Momentum Stocks with 2 Investing Strategies
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Start00 Project 2 Preview (2:42)
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Start01 Make An API Call (9:47)
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Start02 Execute A Batch API Call (14:59)
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Start03 Remove Low Momentum Stocks (6:06)
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Start04 Calculate The Number Of Shares To Buy (7:53)
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Start05 Find High Quality Momentum Stocks (11:42)
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Start06 Calculate Momentum Percentiles (7:19)
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Start07 Find The 50 Best Momentum Stocks (8:10)
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Start08 Calculate New Number Of Shares To Buy (5:30)
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Start09 Build An Excel File (3:41)
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StartSource Files
Find 50 Best Value Stocks with 2 Investing Strategies
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Start00 Project 3 Preview (1:55)
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Start01 Build A Dataframe (5:58)
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Start02 Remove Glamour Stocks (5:01)
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Start03 Calculate The Number Of Shares To Buy (3:51)
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Start04 Build A Composite Of Valuation Metrics (15:22)
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Start05 Clean Dataframe (5:49)
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Start06 Calculate Value Percentiles (4:50)
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Start07 Find The 50 Best Value Stocks (6:58)
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Start08 Calculate New Number Of Shares To Buy (3:24)
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StartSource Files
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