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The Complete GPT Algorithmic Trading Course: GenAI & Python+
Welcome
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Introduction to Algorithmic Trading
01 Introduction to Algorithmic Trading
Code Python on the Web (Intro to Colab)
01 What Is Google Colab (4:24)
02 What If I Get Errors (2:40)
03 How Do I Terminate A Session (2:40)
Introduction to Python
01. Intro To Python (5:46)
02. Variables (19:17)
02b. Variables Examples (10:42)
03. Type Conversion Examples (10:04)
04. Operators (7:04)
05. Operators Examples (21:52)
06. Collections (8:23)
07. Lists (11:38)
08. Multidimensional List Examples (8:05)
09. Tuples Examples (8:34)
10. Dictionaries Examples (14:24)
11. Ranges Examples (8:30)
12. Conditionals (6:41)
13. If Statement Examples (10:16)
14. If Statement Variants Examples (11:18)
15. Loops (7:00)
16. While Loops Examples (11:30)
17. For Loops Examples (11:18)
18. Functions (7:47)
19. Functions Examples (9:16)
20. Parameters And Return Values Examples (13:46)
21. Classes And Objects (11:13)
22. Classes Example (13:11)
23. Objects Examples (9:54)
24. Inheritance Examples (17:26)
25. Static Members Example (11:03)
26. Summary And Outro (4:06)
Source code
Disclaimer - Use Caution for Safe Trading
Disclaimer - Use Caution for Safe Trading
Advanced Machine Learning Techniques for Algorithmic Trading
01 Introduction to Machine Learning in Trading
02 Feature Engineering for Trading Algorithm
03 01 Setting up and Preparing Data (20:47)
03 02 Training Model and Visualizing Results (16:44)
Resources
High-Frequency Trading Strategies
01 Introduction to High-Frequency Trading
02 Market Microstructure
03 Designing High-Frequency Trading
04 Risk Management in High-Frequency Trading
05 Algorithm Stress Test in Colab (21:24)
Resources
Portfolio Optimization and Risk Management
01 Introduction to Portfolio Optimization and Risk Management
02 01 Setting up intial data and formulas (27:13)
02 02 Integrating Portfolio Optimization and Black-litterman (25:48)
Resources
Sentiment Analysis and NLP for Algorithmic Trading
01 Introduction to Sentiment Analysis and NLP for Algorithmic Trading
02 Data Collection and Processing for Sentiment Analysis
03 Sentiment Analysis Techniques
04 01 Integrating Sentiment Analysis and Back Testing (19:07)
04 02 Finishing up script and Testing (16:58)
Resources
Starting on Quantitative Finance
01 Fundamentals of Quantitative Finance
02 Basic Statistics and Probability
03 Understanding Time Series Data
04 Implementing Time Series in Colab (12:24)
Resources
Compute returns from prices
00a Stock Prices and Calculating Returns
00b Complete Commented Project Code
01 Calculate Stock Returns with Python (4:34)
02a Stock Analysis with Pandas
02b Use Pandas DataFrame for Multiple Stocks (3:58)
03a Analyzing CSV Data
03b Read Data from a CSV File in Python (3:04)
04a Compounding and Annualizing Returns
04b Compound and Annualize Returns in Python (4:28)
Source Files
Analyze Volatility and Returns of Stock Portfolios
00 Full Commented Project Code - Analyze Volatility and Returns of Stock Portfolios
01a Understanding stock portfolio data
01b Clean and visualize data with Python (4:40)
02a Understanding volatility and standard deviation
02b Calculate volatility with Python (3:49)
03a Annualized volatility
03b Annualize volatility and returns in Python (5:04)
04a Is the Return Worth the Risk? 😨 🎲 💰 Use the Sharpe Ratio to Decide
04b Calculate Sharpe Ratio for risk-adjusted return in Python (2:56)
Source files
Time Series Manipulation and Drawdown Analysis in Python
00a Project Introduction - Time Series Manipulation and Drawdown Analysis in Python
00b Complete Commented Project Code
01 Data Loading and Preprocessing (4:26)
02 Change Timestamp to Datetime (5:36)
02a Understanding Data Types - Timestamp and Datetime
03 Calculate Drawdowns (3:56)
03a Understanding Drawdowns
Source files
Calculate Measures of Downside Risk with Python
00a Project Preview - Measures of Downside Risk with Python
00b Complete Commented Project Code
01 Load Hedge Fund Data in Python (3:19)
02a Understanding the Semideviation Downside Risk
02b Calculate Semideviation in Python (2:36)
03a Exploring Value at Risk Metric for Risk Assessment
03b Calculate Value at Risk in Python (3:36)
04a Conditional Value at Risk as a Tool for Measuring Downside Risk
04b Calculate Conditional Value at Risk in Python (3:22)
05a Examining the Role of Parametric Gaussian Value at Risk in Assessing Downside Risk
05b Calculate Parametric Gaussian Value at Risk in Python (1:34)
06a Interpreting Cornish-Fisher Modification as a Metric for Downside Risk Evaluation
06b Calculate Cornish-Fisher Modification in Python (9:42)
Source files
Efficient Frontier Data Analysis and Visualization in Python
00a Project Preview - Efficient Frontier Data Analysis and Visualization in Python
00b Complete Commented Project Code
01 Load Industry Portfolio Monthly Returns mock data in Python (2:57)
02a Annualized Returns and Covariance for Efficient Frontier
02b Calculate Annualized Returns and Covariance (3:32)
03a Weights in Efficient Frontier Analysis
03b Define weights (2:55)
04a Understanding returns formula with weights
04b Calculate portfolio returns (3:26)
05a Understanding volatility formula with weights
05b Calculate portfolio volatility (2:59)
06a Understanding the Efficient Frontier
06b Visualize Efficient Frontier (3:43)
07a Capital Market Line and Tangency Portfolio
07b Plot the Capital Market Line in Python (4:45)
08 Visualize tangency portfolio in Python (7:30)
Source Files
Build Constant Proportion Portfolio Insurance Algorithm in Python
00a Project Preview - Portfolio Insurance Dynamic Risk Budget Algorithm
00b Complete Commented Project Code
01 Load Industry Returns, Firms and Size Data (3:03)
02a Understanding the total market index
02b Calculate the total market index (2:48)
03a Understanding parameters for our Portfolio Insurance strategy
03b Define initial values (5:54)
04a Steps of the Constant Proportion Portfolio Insurance (CPPI) strategy
04b Backtest the Strategy (11:27)
05 Visualize results (8:12)
Source files
Quantitative Trading
01 Quantitative Trading
Simulate a stock trading strategy with Z-score
00a Project Preview - Simulate a stock trading strategy with Z-score
00b Complete Commented Project Code
01 Generate Single Stock Data with Python in Colab (7:00)
02 Calculate cumulative moving average of stock price (1:26)
03 Simulate Trading Strategy with ZScore (5:34)
Source files
Mean Reversion on Stock Portfolio
00a Project Preview - Mean Reversion on Stock Portfolio
00b Complete Commented Project Code
01 Stock Portfolio Data Generation (6:56)
02 Visualize returns (5:05)
03 Mean Reversion on Stock Portfolio (3:28)
source files
Simulate and Predict Interest Rates and Bond Prices Like a Pro with Python
00a Project Preview - Simulating interest rates with mean-reversion
00b Complete Commented Project Code
01 Build initial conditions for simulating interest rates (7:21)
02a Understanding bond prices
02b Set Up Bond Prices (10:24)
03a Understanding Cox-Ingersoll-Ross algorithm
03b Calculate bond prices with the Cox-Ingersoll-Ross (CIR) model (4:06)
04 Convert instantaneous interest rates to annualized rates- (4:50)
Source Files
Trading Strategies and Techniques - Introduction To The Course
02 Introduction Of The Instructor (1:24)
01 Introduction To The Course (2:35)
03 Course Requirements (1:11)
Course Script Files
Interactive Brokers API Trading
01 01 Setting Up Our Dependencies (8:15)
01.02 Connecting To The IKBR Desktop App (12:39)
01.03 Grabbing Previous Candle Data (16:36)
01.04 Grabbing Current Candle Data (WITH SUBSCRIPTION) (6:45)
01.05 Grabbing Current Candle Data (WITHOUT SUBSCRIPTION) (5:17)
01.06 Performing TA On A Candle (14:48)
01.07 How To Place Orders (13:56)
01.08 Bracket Orders & Putting Everything Together (13:22)
Source Files
Real-Time Stock Data Acquisition: Cutting-Edge Strategies for Market Analysis
01 01 Introduction To yFinance & Real Time Data (11:29)
01.02 Grabbing & Interpreting yFinance Data (20:25)
01.03 Setting Up Our Web Scraper Environment (8:14)
01.04 Introduction To Finviz and Basic Scraping (14:52)
01.05 How To Deal With Pagination For Web Scraping (15:17)
01.06 Putting Our Scraped Data Into Excel (22:06)
Source Files
Tradingview & Pinescript
01 01 Introduction To Tradingview (7:34)
01.02 Basics Of Pinescript (13:04)
01.03 Creating Our First Overlay Indicator (17:37)
01.04 Creating A Non Overlay Indicator (10:39)
01.05 Creating A Strategy From Our Indicator (12:05)
Source Code
Options 101
01 01 What Are Options + Benefits & Drawbacks (11:59)
01.02 Options Terminology (5:19)
01.03 Buying Vs Selling Options (5:20)
02.01 What Is Delta (7:11)
02.02 What Is Gamma (6:31)
02.03 What Is Theta (6:09)
02.04 What Is Vega (4:15)
02.05 What Is Rho (3:17)
03.01 Common Options Strategies (10:00)
Market Basics
01.01 Why You Should Trade (7:28)
01.02 What Is A Stock (4:45)
01.03 What Is A Market (2:27)
01.04 What Is A Stock Exchange (3:03)
01.05 What Is A Broker (5:10)
01.06 Where To Trade (4:36)
Orders And Prices
01.01 Orders And Order Types (17:15)
01.02 Orders Driving Prices (2:30)
01.03 Different Players (4:06)
01.04 Ways To Make Money (3:45)
Technical Analysis
01.01 What Is Technical Analysis (10:37)
01.02 Charts And Candlesticks (20:59)
01.03 Trends, Support And Resistance (7:41)
01.04 Chart Patterns (7:10)
01.05 Volume (9:57)
01.06 Bollinger Bands (7:25)
01.07 Relative Strength Index (10:21)
01.08 Average True Range (5:01)
Fundamental Analysis
01.01 What Is Fundamental Analysis (15:43)
01.02 Financial Statements (13:58)
01.03 Fundamental Ratios (4:39)
01.04 Current Vs Expected (2:46)
01.05 Growth Vs Value Companies (4:59)
01.06 Trend Analysis (8:18)
01.07 Benchmarking (7:30)
01.08 Dividend Discount Model (13:19)
01.09 Stock Splits (5:45)
01.10 Other Metrics (4:22)
Risk And Money Management
01.01 What To Expect (15:22)
01.02 Gambling Vs Educated Betting (3:19)
01.03 Batting Average (3:56)
01.04 Win-Loss Ratio (5:15)
01.05 Risk Management (7:24)
01.06 Money Management (10:35)
01.07 Position Sizing (10:03)
Day Trading - Introduction To The Course
01 Introduction (1:35)
Course Script PDF Files
Day Trading Fundamentals
01 What Is Day Trading (1:51)
02 Why Most People Fail At Day Trading (5:02)
03 Pros And Cons Of Day Trading (13:46)
04 Types Of Day Trading (1:18)
Stock Analysis For Day Trading
01 Risk And Account Management (4:11)
02 How To Choose The Right Stock (13:46)
03 Scale Out Your Trade (2:38)
04 How To Use Stock Screeners (3:33)
05 Important Indicators To Use (5:43)
06 Get Trading Signals From Indicators (5:56)
07 Use A Trading View Platform (3:53)
Strategies And Tools (With Practical Examples)
01 Overview Of Day Trading (8:27)
02 Trading Plans Overview (5:40)
03 Deployment Process (5:10)
04 Analyze Historical Performance (9:55)
05 Which Broker To Use (6:46)
Open Price Gaps Strategy
01 What Is The Open Price Gaps Strategy (3:09)
02 Warning About Scammers (3:30)
03 Opening And Closing Auctions (4:26)
04 Build A Trading Plan And Stock Screening (2:17)
Equity Dilution Strategy
01 What Is The Equity Dilution Strategy (4:39)
02 Why The Strategy Works (2:49)
03 How To Research (3:02)
04 How To Backtest (5:52)
05 Build A Trading Plan And Stock Screening (1:44)
Dividend Cuts Strategy
01 What Is The Dividend Cuts (5:10)
02 Present Value Of Money (13:46)
03 When A Company Cuts Dividends (3:02)
04 Build A Trading Plan And Stock Screening (1:37)
Cryptocurrency Trading - Introduction To The Course
01 Introduction To The Course (4:02)
02 Introduction Of The Instructor (2:05)
03 Course Requirements (0:22)
Course Script Files
Cryptocurrency Fundamentals
01 Introduction Of Crypto Currencies (4:32)
02 Introduction Of Bitcoin (7:06)
03 Introduction Of Ethereum (2:25)
04 Inroduction Of Altcoins (1:30)
05 Introduction Of Multiplier (2:25)
06 Difference Of Fiat And Satoshi (7:21)
07 Difference Of Coin And Token (6:31)
Crypto Investing Fundamentals
01 Most Profitable Cryptocurrencies (8:48)
02 Where To Find Cryptocurrency Data (0:35)
03 Tips For Investing (10:17)
04 Warnings About Investing (3:33)
05 Invest In A Coin Long-Term (2:43)
06 Invest In A Coin Short-Term (3:44)
07 When To Buy And Exit (1:46)
08 Maximize Gains (2:00)
09 Spot Hidden Coins (3:33)
Buy Your First Cryptocurrency
01 Need To Buy Crypto (9:21)
02 Buy Bitcoin With Your Normal Currency (1:16)
03 Send Money To An Exchange (5:21)
04 Sell Your First Cryptocurrency (13:46)
05 Decentralised Exchanges & Uniswap (21:10)
06 Pancakeswap (7:36)
Criteria For Investing
01 Large, Mid And Micro Cap Coins (9:37)
02 How To Get Regular Profits (10:52)
03 Calculate Your Potential For Gains (2:39)
04 Additional Bonuses (2:52)
05 Investment’S Long Term Capability (1:28)
Buying Strategies
01 Short Term Strategy (4:31)
02 Long Term Strategy (7:04)
03 Playing The Market (2:05)
04 React When Your Investment Loses Money (3:13)
Technical Analysis - Crypto Trading Tactics
01 Bear Vs Bull Market (7:00)
02 Predict If A Crypto Will Soar Or Crash (12:27)
03 Find Optimal Price Of A Coin (9:58)
04 Stay Or Exit A Trade (8:15)
05 How To Use Candlesticks (4:27)
06 Spot Trends And Predict Future Prices (6:31)
Profitable Types Of Cryptocurrency
01 Why Blockchain Infrastructure Coins Are Valuable (35:50)
02 Why Privacy Coins Are Valuable (12:51)
03 Why Iot Coins Are Valuable (4:38)
04 Why Currencies Are Valuable (10:28)
05 Dapputility Coins Are Valuable (2:37)
How To Cash Out
01 Profits Back To Fiat (8:09)
02 Avoid High Fees When Selling (7:24)
DeFi Crypto Investing And Yield Farming
01 Defi And Yield Farming (20:02)
02 Why You Should Be A Yield Farmer (2:05)
03 Warnings About Yield Farmers (2:23)
04 How Buy New Defi Coins (2:14)
05 How To Reduce Gas Prices (8:35)
NFT Cryptos
01 What Are NFTs (4:33)
02 NFTs Are A High Profit Investment (4:36)
03 Different NFT Platforms (2:17)
04 Yield Farming & NFT Platforms (3:07)
Invest In ICOs
01 What Are ICO (11:55)
02 Why Invest In ICOs (2:46)
03 Optimum Price During Pre-Sales (2:48)
04 Partake In Private Sales (4:07)
Options Trading - Introduction To The Course
01. Introduction To The Course (3:26)
Course Script Text Files
Introduction To Call And Put Options
01. What Are Options (6:30)
02. Practical Example With A Stock (4:42)
03. Introduction To Call Options (1:40)
04. Practical Example Of A Call Option (4:28)
05. What Are In-The-Money (ITM), At-The-Money (ATM) And Out-Of-The-Money (OTM) Options (4:24)
06. Buyer And Seller Risk Profiles (4:21)
07. Risk Graphs (5:57)
08. Option Chain And Quote Screen (3:04)
09. Practical Stock Example - Choice Of Expiry Series And Itm, Atm And Otm Options (8:04)
10. Call Option Performance In Real-Time And On The Day Of Expiry (4:58)
11. Risk Graphs Of Itm, Atm And Otm Options (1:35)
12. Option Sellers Risk Profile (5:10)
13. Real-World Example Of Put Options (3:08)
Introduction To Time Decay
01 What Is Time Decay (3:31)
02 Practical Examples Of Time Decay (5:59)
Implied Volatility
01. What Is Implied Volatility (2:47)
02. Practical Examples Of Implied Volatility (3:02)
Option Greeks
01. What Are Option Greeks (3:36)
02. Option Delta (7:27)
03. Option Gamma (7:49)
04. Option Vega (4:52)
05. Option Theta (8:34)
Basic Strategies
01. Long Call Strategy (7:47)
02. Long Put Strategy (7:28)
03. Trade Set Up For Monthly Options (Indicators Settings) (13:39)
04. Covered Call Strategy (5:49)
05. Protective Put Strategy (6:54)
06. Writing Put Strategy (Selling Put Options) (7:28)
Options Spreads - Monthly Income Strategies
01. Bull Call Spread Strategy (13:28)
02. Bull Put Spread Strategy (8:42)
03 Bear Call Spread Strategy (8:03)
04. Bear Put Spread Strategy (6:48)
05. Call Back Spread Strategy (4:56)
06. Profitable Condition For Call Back Spread (10:04)
07. Put Back Spread Strategy (3:48)
08. Profitable Condition For Put Back Spread Strategy (7:37)
Neutral Strategies
01. Short Strangle Strategy (6:39)
02. Collar Strategy (6:30)
03. Long Butterfly Spread Strategy (7:14)
Volatile Strategies
01. Long Straddle Strategy (5:22)
Financial AI and ChatGPT Applications
01 Introduction Of The Instructor (2:25)
Source Files
Build your first ChatGPT AI prompts with Prompt Engineering - Intro to prompt engineering
01 What Is ChatGPT (7:50)
02 Intro To Prompt Engineering-Prompt Types (8:28)
03 Intro To Prompt Engineering-Effective Prompts (8:41)
Source Files
Build your first prompts
01 Project Preview (2:04)
02A Simplify Complex Information (8:38)
02B Simplify Complex Information-Other Strategies (8:41)
Source files
Predict stock performance with ChatGPT
01 Course Requirement (3:20)
02 Project Preview (2:03)
02A Analyze Financial Statements Of Stock (9:00)
02B Financial Ratio And Trend Analysis (4:25)
03 Balance Sheet, Income Statement And Cash Flow Statement (9:00)
04 Loopholes And Weaknesses In Stock Financials (8:39)
05 Analyze Historical Stock Performance (11:16)
06 Predict Stock Performance (5:08)
Source Files
Stock Analysis with ChatGPT
01 Market Share (5:31)
02 Industry Analysis (7:48)
03 Management Team Analysis (8:25)
04 Analyze Stock Risks (6:56)
05 Valuation (8:11)
06 Explain Business Model Of A Company (6:24)
07 Perform A Swot Analysis (8:16)
08 Summarize A Company’s Earnings Report Calls (6:55)
09 Evaluate A Company’s ESG Credentials (4:39)
Source Files
Build an Investment Plan with ChatGPT
01 Project Preview (0:48)
02A Invest Short Term (6:22)
02B Implementing Your Short-Term Investment Strategy (8:06)
03A Invest Long Term (5:58)
03B Analyzing The Results (7:27)
04A Using Chatgpt To Assess Your Risk Tolerance (7:32)
04B Customized Investment Recommendations Based On Individual Financial Goals And Risk Tolerance (5:26)
04C Implementing Your Customized Investment Plan (8:47)
Source Files
Stock Market Prediction and Risk Analysis with ChatGPT
01 Project Preview (1:25)
02A Recent Past Stock Market State (7:44)
02B Analyzing Past Trends And Economic Events (9:24)
03 Present Stock Market State (6:29)
04A Future Stock Market State (8:12)
04B Insights On Macroeconomic Factors (7:09)
05 Project Preview (2:22)
06 Analyze Credit Scores (7:56)
07 Assess Loan Applicant Risk (7:35)
Source Files
Trading Strategies, Sentiment Analysis and Fraud Detection with ChatGPT
01 Project Preview (1:12)
02 Pick Stocks With Company Evaluation (6:00)
03A Build A Trading Strategy (8:54)
03B Test Trading Hypthothesis (8:29)
04 Project Preview (1:03)
05 Chatgpt And Sentiment Analysis (8:52)
06 Analyzing Sentiments On Social Media Posts (8:45)
07 Project Preview (1:03)
07A Fraud Detection With Chatgpt (7:37)
07B Detecting Exploitation Prone Weaknesses (8:01)
08A Red Flags And Anomaly Detection (6:07)
08B Anomaly Detection Techniques (8:01)
09 Conclusion (2:20)
Source File
CoPilot Prompt Engineering in Excel - Unleash Data with AI
00 Course Overview (1:51)
01 Overview (2:03)
02 Microsoft-s Approach to AI (3:42)
03 Microsoft-s AI-Enhanced Productivity Tools (3:26)
04 Copilot for Microsoft 365 (5:20)
05 Data Considerations (2:14)
06 Copilot Interaction for Microsoft 365 (4:18)
07 Recap (1:36)
08 Overview (1:49)
09 Accessing Copilot in Excel (3:07)
10 Insight Identification (15:50)
11 Managing Data with Copilot (9:37)
12 Generating Formulas (11:05)
Source Files
Prompt Engineering with Microsoft Copilot - Mastering Prompts for Personalized Results
00 Course Overview (1:48)
01 Overview (1:00)
02 Understanding Copilot (3:51)
03 Accessing Microsoft Copilot (2:39)
04 What to Keep in mind (2:52)
05 Recap (0:51)
06 Overview (1:07)
07 The Interface (19:18)
08 Understanding Copilot Prompts (1:27)
09 Interaction with Copilot (5:38)
10 Recap (1:10)
11 Overview (1:23)
12 Copilot- Answers & Create (36:56)
13 Image Prompting (13:24)
14 Prompting Advance Tasks (21:10)
15 Recap (1:42)
Resources
Python and AI Integration
01. Introduction (4:42)
Ollama LLM Comprehensive Guide - Enhancing AI Conversations and Integrating with Python
01 Run And Chat With Llama 2 In Command Line (2:57)
02 Write Code With Code Llama (3:45)
03 Run Uncensored Llm Model With Ollama (3:55)
Resources
Customize Ollama Models
01 Build More Creative Ollama Llm With Higher Temperature (4:07)
02 Customize Sentiment Analyzer With Template (4:31)
03 Customize Model With Reusable System Prompt (3:26)
04 Customize Model With Template (5:37)
05 List And Delete Custom Ollama Models (1:10)
Resources
Customize Ollama Model for Sentiment Analysis
01 Pull Orca Model For Enhanced Reasoning (5:35)
02 Customize Ollama Model With More Parameters (4:51)
Resources
Connect to Ollama with Python Client
01 Connect To Ollama With Python Client (8:03)
02 Format Llama2 Response With Json (2:58)
03 Build User Interface For Ollama Language Model Chat (4:34)
Resources
(Prerequisite) Introduction to HTML
01. Course Requirements (2:56)
02. What Is JSbin (3:15)
03. Setting Up The HTML Document (2:41)
04. Header Tags And Paragraphs Tags (4:06)
05. Styles (3:32)
06. Bold Underline And Italic Tags (3:10)
07. Adding In A Link (1:38)
08. Adding In A Image (3:01)
09. Adding A Link To An Image (1:55)
10. Lists (4:03)
11. Tables (3:29)
12. Different Kinds Of Input (4:59)
13. Adding In A Submit Button (3:01)
14. Scripts And Style Tags (3:27)
How OpenAI API Works
Advisory Notice: About Using API Keys on External Platforms
01 OpenAI API Models To Work With (2:53)
02 How OpenAI API Works (2:09)
03 Adjust OpenAI API Model Parameters (7:58)
Source files
Build your first OpenAI API queries with Python
01 Use OpenAI API To Answer Questions Like ChatGPT (10:19)
02 Correct Grammar With OpenAI API (3:30)
03 Summarize And Simplify Text With OpenAI API (4:03)
04 Translate Text With OpenAI API (3:04)
Source files
Build OpenAI API queries for to automate coding tasks
01 Generate Code With OpenAI API (7:11)
02 Explain Code With OpenAI API (5:24)
03 Calculate Time Complexity With OpenAI API (3:40)
04 Translate Programming Languages With OpenAI API (4:24)
05 Fix Bugs In Code With OpenAI API (3:19)
Source files
Use OpenAI API to automate data science tasks
01 Generate SQL Queries With OpenAI Py (5:15)
02 Build Structured Table Data From Long Form Text (4:29)
03 Classify Items Into Categories With OpenAI API (4:50)
04 Generate Spreadsheets And Lists With ChatGPT OpenAI API (5:46)
Source files
Use OpenAI API to automate copywriting with GPT Turbo
01 Convert Notes To Summary With OpenAI API (5:40)
02 Add Emotional Sentiment To Text With OpenAI Models (9:40)
03 Generate Questions On A Topic With GPT Turbo (9:26)
04 Generate Text Conversation With ChatGPT API (5:19)
Source files
Use OpenAI API to automate marketing with GPT Turbo
01 Classify Text Emotion Sentiment With ChatGPT Models (5:09)
02 Extract Keywords From Text With ChatGPT API (4:31)
03 Convert Product Description To Ad With ChatGPT Python (3:57)
04 Generate Product Names With ChatGPT In Python (4:04)
05 Extract Information From Text With ChatGPT API (2:57)
Source files
Scrape web data in text form with Python
01 Build HTML Parser With Python (4:31)
02 Scrape Hyperlinks From URL Webpage With Python (4:09)
03 Filter Out URLs Not Part Of Domain (7:03)
04 Save Web Content To Files With Python (10:07)
Source files
Process web data for OpenAI machine learning
01 Convert Text To CSV With Python (6:36)
02 Remove Whitespace And Lines From Text With Python (4:58)
03 Tokenize Text With Python For Machine Learning Models (2:50)
04 Split Long Lines With Python (4:11)
05 Split Pandas Dataframe Into Sections With Python (7:19)
06 Embed Text For Machine Learning With OpenAI API (8:05)
Source files
Customize OpenAI model to learn from your data
01 Embed Question With Python (5:48)
02 Answer Questions About Your Data With Customized OpenAI Model (10:36)
Source files
Answer questions about PDF with ChatGPT model in Python
01 Load And Read PDF In Python (3:40)
02 Build Vector Index From PDF Text In Python (4:32)
03 Answer Questions About PDF With Chatgpt Model In Python (5:10)
Source files
Generate and Embed text data with OpenAI API
01 Generate Review Data With ChatGPT API (8:14)
02 Format Python Text To Multidimensional Pandas Dataframe (11:50)
03 Change Column Data Type In Pandas Dataframe (2:40)
04 Embed Text Data With OpenAI API (6:25)
Source Files
Transcribe Video
01 Set Up Transcribing Project (2:25)
02 Transcribe Video With OpenAI Whisper API (2:22)
Resources
Build image captioning app with OpenAI GPT Vision 4
00A Project Preview - Build Image Captioning App With OpenAI Vision (2:25)
00B Introduction To OpenAI GPT Vision 4 (9:23)
01 Gpt Vision 4 Image Captioning With OpenAI API (10:38)
02 Build User Interface For Image Captioning App (8:30)
Resources
Build image classification app with OpenAI Vision
00 Project Preview - Image Classification App With OpenAI Vision (1:49)
01 Binary Image Classification With OpenAI Vision (11:13)
02 Send Request To OpenAI (4:26)
03 Build User Interface For Image Classification App (6:21)
Resources
Build GPT Assistant with ChatGPT Editor
00 Project Preview - Build GPT For GPT Store (1:24)
01 What Are GPT Assistants From OpenAI (9:14)
02 Build GPT Assistant With ChatGPT Editor (12:22)
Resources
Build GPT Assistant with OpenAI API
01 Build GPT Assistant With OpenAI API (6:09)
02 Add Message To Thread (3:58)
Resources
Build GPT Assistant to Answer Questions about File
00 Project Preview - GPT Assistant To Answer Questions About File (1:49)
01 Build File For OpenAI Assistant API (2:55)
02 Build GPT Assistant With File (3:44)
03 Build GPT Assistant Thread With File (6:26)
Resources
Build Youtube video summarizer app
00 Project Preview - Youtube Video Summarizer App (1:20)
01 Generate Youtube Transcript With Python (6:18)
02 Summarize Youtube Transcript With OpenAI (6:12)
03 Build User Interface For Youtube Summarizer App (6:27)
Resources
Video analysis with OpenAI's Vision Model
00 Project Preview - AI Video Voiceover Generator App (2:25)
01 Encode Video For Openai API (8:14)
02 Describe Video With Openai API (5:02)
03 Generate Video Voiceover Script With OpenAI (5:21)
04 Generate Mp3 Audio From Script With OpenAI Speech (6:31)
05 Combine Video And Audio With Python (6:03)
06 Build User Interface For AI Video Narration App (6:25)
07 Generate Voiceover Upon Video Submission (8:48)
Resources
Build a Screenshot to Code OpenAI Generator App
01 Buid System And User Prompts To OpenAI Vision (9:23)
02 Send Image To OpenAI Vision (7:05)
Resources
Improve web clone results with prompt engineering
01 Improve Web Clone Results With Prompt Engineering (9:46)
02 Generate Webpage Bootstrap Styling With OpenAI (13:02)
03 Generate Image Placeholders With OpenAI (6:40)
Resources
Generate replacement images with DALL-E
01 Scrape Image Tags From Webpage (4:55)
02 Generate Replacement Image With Dall-E (6:46)
03 Generate Replacements For All Placeholders (6:43)
Resources
Replace placeholders in webpage with generated images
01 Replace Placeholders In Webpage With Generated Images (7:52)
02 Resize HTML Images With Python (6:04)
Resources
Generate data with OpenAI JSON mode
00 Project Preview - Generate Data With OpenIA Json (0:56)
01 Generate Data With OpenAI Json Mode (8:38)
Resources
Call function upon user query with OpenAI
01 Define Messages To OpenAI (4:36)
02 Define Functions To Trigger On OpenAI Response (8:01)
03 Call Function Upon User Query With OpenAI (8:33)
04 Build Multiple Functions For OpenAI To Choose (3:14)
Resources
Extracting information from input in structured manner
01 Set Up Messages For OpenAI (5:14)
02 Create Functions For When OpenAI Replies (5:33)
03 Take Action When OpenAI Responds (5:26)
Resources
Build Python Projects with OpenAI
01. Initial installation and configuration (7:02)
02. Benefits of clear prompts (7:02)
02.01 Making A Simple Chat Bot App (12:36)
03. Image Generation Using Python And ChatGPT (11:35)
04.01 Transcribing Speech To Text (8:46)
04.02 Translating Speech To English (6:42)
Source Code
Build a ChatGPT Clone with Python Custom UI
01. Introduction And Demo (2:31)
02. Backend Of The Chat Bot (10:20)
03. Frontend Of The Chat Bot (18:20)
04. Troubleshooting And Testing (9:06)
Source files
Build a ChatGPT Chrome Extension with Python
01 Introduction And Project Setup (6:18)
02. Setting Up The Configuration Files (9:26)
03. Completing The Front End Of The Extension (11:22)
04. Completing The Backend Of The Extension (20:35)
05. Testing And Troubleshooting (11:13)
Source Code
Build Transcriber Python Web App with OpenAI Whisper API
00 Requirements
01 Introduction And Project Setup (5:04)
02. Coding The Backend Of The App (18:16)
03. Coding The Frontend Of The App (21:47)
04. Testing And Troubleshooting The App (4:34)
Source Code
Build Image Generation Web App with OpenAI API
01 Introduction And App Setup (4:18)
02. Completing The Backend Of The App (7:21)
03. Completing The Front End Of The App (8:03)
04. Adding Styles To The App (7:17)
05. Testing And Troubleshooting (9:44)
Source Code
Test Your Knowledge
Practice Exam - Build coding and data science AI apps with OpenAI Python API
Practice Exam - Automate marketing and copywriting with ChatGPT API Python
Practice Exam - Customize OpenAI machine learning with Python web scraping data
Practice Exam - Build custom OpenAI ChatGPT API Python apps with embeddings
Practice Exam - Build AI Applications with OpenAI Vision and Whisper
Practice Exam - Master OpenAI with GPT Assistants, Function Calling and JSON Mode
Practice Exam - Build Python Projects with OpenAI
Practice Exam - Build a ChatGPT Clone with Python Custom UI
Practice Exam - Build a ChatGPT Chrome Extension with Python
Practice Exam - Build AI Apps with ChatGPT and Python
Practice Exam - Video Analysis and AI Python App Development with OpenAI Vision
Practice Exam - Build a Screenshot to Code OpenAI Python App
Introduction to Prompt Engineering with LangChain
01 Introduction to LangChain - A Comprehensive Framework for LLM Applications
01b Understanding LangChain for Language Model Applications
02 Set up LangChain project in Jupyter Notebook with Anthropic (6:27)
03 Understanding retrieval chains in LangChain
04 Build a Retrieval Chain with LangChain and OpenAI (6:48)
Automate prompt to function pipeline with LangChain tool calling
01 What is LangChain Tool Use
02 Build a tool with LangChain Python SDK (6:15)
03 Build tool function calling with LangChain OpenAI Python SDK (4:49)
04 Invoke LangChain tool with a chain (5:16)
Source Files
Dataset Generation with LangChain Python for Synthetic CSV Data Analysis
01 Build a Data Model (5:53)
02 Build sample data for synthetic generation in Python (5:36)
03 Build a prompt template for data generation LLM (4:31)
04 Build a data generator with LangChain OpenAI Python SDK (3:17)
05 Generate synthetic data with LangChain OpenAI in Colab (4:19)
06 Save list to CSV in Python (9:15)
Source Files
Automate CSV Data Analysis with LangChain OpenAI Python SDK
01 Load CSV file into Pandas dataset (4:15)
02 Generate Pandas Code with LangChain OpenAI Python SDK (5:08)
03 Build Function Call to Use Python LangChain Tool (8:21)
04 Build Chain to Automate LangChain Tool Use (11:00)
Source Files
Mastering Google Gemini - Google Gemini Large Language Model API Essentials
01 Connect to Google's Gemini API with Python
01b Install Gemini and Add Secret API Key to Colab (3:04)
02 Exploring Gemini API - Model Selection and Capabilities
02b List content generation models with Gemini Python SDK (1:57)
03 Leveraging the Gemini API for Text Generation
03b Send a request to Gemini with Python SDK (3:51)
04 Multimodal Content Generation with Gemini API
04b Caption an image with Gemini Python SDK (4:41)
05 Mastering Conversations with Gemini's Chat API and Python
05b Build chat session with Gemini Python SDK (2:23)
06 Maximizing Model Performance - Token Count Management in the Gemini API
06b Count tokens with Gemini Python SDK (1:50)
07 Harness the Power of Text Embeddings with Gemini API
07b Build embeddings with Gemini Python SDK (3:01)
Practice Exam
AI App Development Mastery - Build with Gemini Python SDK and Practice Exam
01 Integrating Gemini with Function Calling in Python
01b Set up function calling project with Gemini Python SDK (5:56)
02 Use the Gemini Pro Model for API Calls in Python
02b Build function call with Gemini Python SDK (4:53)
03 Build Complex Function Calls in APIs
03b Execute external API function call with Gemini Python SDK (10:18)
04 Integrate Function Calls in Chat Sessions with Gemini
04b Simulate function calls in chat session with Gemini Python SDK (8:26)
Practice Exam
An Intro to Gemini as Virtual Assistant
01 Gemini as Virtual Assistant (13:05)
Resources
Communication and Collaboration
01 Email Management (7:28)
02 Language Translation (8:45)
03 Document Drafting (10:10)
04 Smart Collaboration (1:42)
Resources
Creativity and Entertainment
01 Creative Brainstorming (15:25)
02 Entertainment Recommendations (8:50)
03 Planning Activities (13:34)
Resources
Research and Information
01 Fact finding and research (13:03)
02 Staying up to date (7:22)
03 Learning and education (8:26)
Resources
Task Management and Productivity
01 Invoice Documentation (17:37)
02 Project Trackers and To-do lists (9:34)
03 Aesthetic Presentation (5:21)
04 Creating Letter Head (4:04)
Resources
Practice Exam
An Intro to Content Creation with Gemini
00 An Intro to Content Creation with Gemini (11:07)
Editing and Refinement
01 Fact-checking and verification (10:10)
02 Proofreading and error correction (6:05)
03 Improving readability (5:00)
04 Repurposing content (6:48)
Resources
Idea Generation and Brainstorming
01 Overcoming creative blocks (11:46)
02 Developing unique angles (6:03)
03 Mind mapping and outlining (5:54)
04 Target audience analysis (5:51)
Resources
Research and SEO
01 Finding Reliable Sources (6:32)
02 Keyword research and optimization (5:50)
03 Understanding content analytics and metrics (7:29)
Resources
Writing and Drafting
01 Expanding on initial ideas (7:32)
02 Tone and style variations (7:54)
03 Overcoming grammar and language barriers (3:03)
04 Long-form vs. short-form content (4:41)
Writing and Drafting
Practice Exam
An Intro to Business Analytics with Gemini AI
An Intro to Business Analytics with Gemini AI (11:07)
Competitive Analysis and Benchmarking
01 Monitoring Competitors (5:18)
02 Identifying Industry Trends (4:51)
03 Evaluating Your Business Performance (3:45)
Resources
Customer Iinsights and Segmentation
01 Understanding Customer Behavior (8:05)
02 Personalizing Marketing and Outreach (5:33)
03 Measuring Customer Sentiment (6:18)
Resources
Data Exploration and Visualization
01 Understanding Your Data (9:10)
02 Creating Effective Visualizations (8:27)
03 Interactive Data Analysis (9:12)
Resources
Forecasting and Predictive Modeling
01 Predicting Future Trends (10:05)
02 Scenario Analysis (11:11)
03 Risk Assessment (9:45)
Resources
Practice Exam
An Intro to Gemini AI for Education
An Intro to Gemini AI for Education (11:07)
Creative Expression and Project Development
01 Brainstorming and Ideation (4:13)
02 Overcoming Writer-s Block (5:50)
03 Project Visualization (4:46)
04 Content Creation Tools (5:36)
Resources
Educator Support an Lesson Planning
01 Administrative tasks automation (8:50)
02 Lesson plan inspiration (4:01)
03 Classroom management strategies (2:47)
Resources
Personalized Learning and Adaptive Tutoring
01 Tailored learning experiences (8:36)
02 Identifying knowledge gaps (3:24)
03 Gamified Learning (3:59)
04 Differentiated instruction (2:43)
Resources
Research and Knowledge Exploration
01 Summarizing Complex Topics (4:54)
02 Finding Credible Sources (4:59)
03 Answering In-Depth Questions (4:19)
04 Encouraging Curiosity (4:32)
Resources
Practice Exam
Advanced Techniques with Claude AI API - Prompt Engineering for Claude LLM with Anthropic API
01 Create API keys (2:07)
02 Send your first API request (10:49)
03 Conversing with Code: Unpacking Anthropic's API
04 Unleashing Clarity - Mastering Direct Communication in AI Prompting
Practice Exam
Advanced Chatbot Prompting Techniques with Claude Anthropic API
01 Engineer Complex Prompts from Scratch
01b Hands-on connect to Anthropic API (8:11)
02 Chain Multiple Prompts
02b Hands-on chain prompts with Anthropic Python SDK (2:26)
02c Building System Prompts
03 Function calling or tool use with Claude
03b Hands-on function calling with Anthropic Python SDK (17:21)
03c Format result for Claude tool (10:47)
Practice Exam
Master Computer Vision with Claude AI Python SDK
01 Describe an image with Claude Vision Python SDK
01b Hands-on image captioning with Anthropic Python SDK (5:02)
02 Compare multiple images with Claude and Python
02b Hands-on image comparison with Anthropic Python SDK (6:00)
03 Understanding Claude Vision capabilities
Practice Exam
Transform Data into Insights - AI PDF Analysis and Data Visualization in Claude, Python and Matplotlib
00 Project setup
00b Set up Anthropic PDF project in Colab (3:18)
01 Encode PDF to image for Claude with Python
01b Hands-on encode PDF in Anthropic Python SDK (6:38)
01c Convert question to high-quality prompt (4:33)
02 Extract information from PDFs
02b Hands-on PDF analysis with Anthropic Python SDK (4:37)
03 Generate Matplotlib code with Claude
04 Hands-on Pyplot generation with Anthropic Python SDK (7:25)
Source files
Practice Exam
Advanced Claude Prompt Engineering - Innovate in Voyage AI with Python
01 Why every prompt engineer must understand embeddings
02 Overview of Embeddings with Anthropic
03 Getting Started with Voyage AI
04 Use the Voyage Python Package for Text Embeddings
05 Access Text Embeddings via Voyage HTTP API
06 Practical Application of Voyage Embeddings - A Semantic Search Example
06b Hands-on build embeddings with Voyage Python SDK (6:52)
07 Accessing Voyage Embeddings on AWS Marketplace
Practice Exam
Claude AI Applications and Training - Advanced Personal Assistant
An Intro to Claude AI as an Advanced Personal Assistant (11:19)
Communication and Coordination
01 Facilitating Communication (5:44)
02 Multilingual Communication (6:33)
03 Conflict Resolution (3:55)
Resources
Daily Task Management
01 Schedule Management (6:14)
02 Task Delegation (5:55)
Resources
Information Retrieval and Research
01 Information Gathering (5:03)
02 Research Summarization (4:58)
03 Decision-Making Assistance (4:51)
Resources
Personalized Learning and Development
01 Customized Educational Content (4:25)
02 Interactive Learning Experiences (4:11)
03 Resource Recommendations (3:34)
Resources
Practice Exam
Claude Chatbot Prompting Strategies with Anthropic API
01 Delegating Tasks through Role Prompting
02 Separate Data and Instructions
02b Hands-on chat to Claude with Anthropic Python SDK (6:36)
03 Format Output and Customize Claude Chatbot Model
03b Hands-on format outputting in Anthropic Python SDK (6:52)
Practice Exam
An Intro to Document Analysis and Management with Claude AI
An Intro to Document Analysis and Management with Claude AI (11:20)
Automated Document Sorting and Organization
01 Categorization Mechanisms (5:39)
02 Tagging and Metadata (5:38)
03 Document Information Retrieval (3:54)
Source Files
Compliance and Security Checks
01 Regulatory Compliance (3:39)
02 Security Risk Assessment (5:01)
Source Files
Content Summarization and Analysis
01 Content Summarization (5:18)
02 Key Point Extraction (4:51)
03 Sentiment Analysis (4:55)
Source Files
Enhancement of Collaborative Work
01 Edit Suggestions and Feedback (11:30)
Source Files
Practice Exam
An Intro to Claude AI
01 Introduction to Claude AI (11:11)
Resources
Content Creation and Editing
01.01 Drafting Initial Outlines with Claude AI (8:55)
01.02 Content Development and Expansion (7:47)
01.03 Refining and Editing Content (7:42)
Resources
Design Feedback and Suggestions
01.01 Principles of Design Feedback (14:42)
01.02 Enhancing User Experience through AI Suggestions (7:23)
01.03 Iterative Design Improvements with Claude AI (4:51)
Resources
Ideation and Concept Development
01.01 Generating Creative Ideas with Claude AI (13:27)
01.02 Concept Development and Enhancement (8:06)
01.03 Inspiration Across Domains (5:01)
Resources
Personalized Content Curation
01.01 Understanding User Preferences and Behavior (5:05)
01.02 Continuous Learning and Content Optimization (2:51)
Resources
Practice Exam
An Intro to Education with Claude AI
00 Introduction to Claude AI (11:11)
Resources
Assessment and Feedback
01 Performance Assesment (12:10)
02 Instant Feedback (6:56)
03 Recommendations for Improvement (7:09)
Resources
Claude AI Assisted Learning
01 Enhancing Learning Experiences (10:41)
02 Streamlining Academic Tasks (8:45)
03 Fostering Student Engagement (4:40)
Resources
Educational Content Creation
01 Lesson Development (6:25)
02 Quiz and Assessment Creation (9:51)
03 Content Customization and Scalability (9:44)
Resources
Tutoring and Knowledge Reinforcement
01 Role of AI as Tutor (5:58)
02 Interactive Learning Exercises (6:05)
03 Integration in Educational Environments (3:30)
Resources
Practice Exam
An Intro to Claude AI Innovative Sales Assistant
01 An Intro to Claude AI Innovative Sales Assistant (11:19)
Data-Driven Sales Strategies
01 Sales Funnel Optimization (5:49)
02 Sales Data Analysis (4:27)
Resources
Enhancing Customer Interaction
01 Customer Simulation (8:17)
02 Real-Time Support (7:28)
03 Customer Feedback Analysis (4:22)
Resources
Streamlining Sales Processes
01 Lead Qualification Automation (4:03)
02 Task Automation and Management (7:44)
Resources
Training and Onboarding
01 Interactive Training Modules (5:47)
02 Real-Time Assistance (7:17)
Resources
Practice Exam
Foundations of Machine Learning and AI for Everyone
Decoding Machine Learning: From Birth to Modern Applications
The Landscape of Machine Learning Strategies
Decoding the Language of AI
Machine Learning Algorithms - An In-Depth Exploration
Exploring Decision Trees and Random Forests in Machine Learning
The Intricacies of Neural Networks: An Insight into AI's Brain
Practice Exam
Cutting-Edge AI - Advanced Techniques and Emerging Technologies
Unraveling the AI Revolution - An Exploration of AI in Consumer Technology
Innovating Business Practices Through AI
Ethics in AI - Navigating the Human-AI Interaction
Society and AI - Navigating a New Era
The AI Revolution - Manufacturing and Retail Transformed
Artificial Intelligence in Healthcare - Transforming Patient Care and Medical Practice
AI Transforms The Financial Sector - Risk Assessment, Trading, and Client Services
Artificial Intelligence Redefining Logistics Efficiency
Practice Exam
The Future is Now - AI in Modern Industry and Beyond
Unveiling the Power of Advanced AI Algorithms
Harnessing Big Data for Transformative Advances in AI
Addressing the Major Challenges in AI Development
Exploring Advanced AI Algorithms - From Reinforcement Learning to Transfer Learning
Future of Artificial Intelligence - An Exploration of Key Trends
The Ethical Dimensions of Artificial Intelligence - Shaping the Future
Exploring Quantum Leap - The Next Phase in AI's Evolution
Envisioning an AI-Driven Tomorrow
Practice Exam
AI at Work - Applications and Industry Transformations
Untangling the Web of AI Jargon - A Comprehensive Guide
Inspiring Tales of AI Transformations
Learning from AI Missteps - A Journey Through Past Failures and Insights
Deep Learning Exploration - Unveiling Machine Intelligence
Reinforcement Learning - Mimicking Interactive Learning from Environment
Exploring Generative Models - Concepts, Applications, and Future Possibilities
Understanding Natural Language Processing - The Language of Artificial Intelligence
Exploring AI in Robotics - The Rise of Autonomous Systems and the Impact of Machine Learning
Practice Exam
AI in Action - Specialized Applications Across Sectors
Transforming the Spectrum of Healthcare with AI
Harnessing AI for Strategic Decision-Making in Finance
Artificial Intelligence - The Backbone of Smart and Sustainable Cities
Quantum Machine Learning - Revolutionizing AI & Computation
Understanding Edge AI - Unleashing Intelligence at the Source of Data
Understanding Feret and the Evolution of AI-empowered Computer Vision
Artificial Intelligence at Work - Reshaping Supply Chain Management and Optimization
Practice Exam
Python Data Science and Machine Learning for Financial Analysis - Compare stock performance with Python
00 Project Overview (2:58)
01 Define Stocks To Compare From Yahoo Finance (4:17)
02 Scrape Stock Data From Yfinance Api (13:49)
03 Visualize Stock Performance (11:29)
Source Files
Course Overview
01 Project Preview (3:29)
Introduction to Machine Learning (Prerequisite)
01 What Is Machine Learning (5:26)
02 What Is Unsupervised Learning (8:17)
Project - Classify Review Sentiment
01 Create A Dataset (5:17)
02 Vectorize Text (16:27)
03 Build A Word Cloud (7:08)
04 Reduce Data Dimensionality With Principal Component Analysis (6:08)
05 Perform Unsupervised Classification With K-Means Clusters (17:33)
Source Files
Course overview
00 Course Overview - Python Crypto Stock Analysis (4:32)
Source files
Introduction to Blockchain (Prerequisite)
00 Blockchain Introduction (8:32)
01 What Are Blockchains And Distributed Ledgers (3:48)
02 What Are Bitcoin And Ethereum (5:28)
03 Introduction To Crypto Trading (2:44)
Introduction to the Stock Market
01 What Do Day Traders Trade (9:45)
02 What Is Volatility And Standard Deviation (3:33)
03 What Are The Best Assets To Day Trade (4:53)
04 Strategies For Stock Market Trading (2:37)
06 Stock Market Indicators (1:56)
07 Stock Market Lifecycle Trend Phases (2:20)
Source Files
Introduction to DataFrames with Pandas Python Library - Setup
00. Setting Up Pandas (2:24)
Introduction to DataFrames with Pandas Python Library - Datastructures
01. Creating A Dataframe (22:42)
02. Sorting And Series (19:19)
03. Expanding A Dataframe (17:14)
Introduction to DataFrames with Pandas Python Library - 02. Manipulating DataFrames
01 Getting Values And Dealing With Nan Values (21:29)
02 Dropping Rows And Columns (23:57)
Introduction to DataFrames with Pandas Python Library - 03. Reading and Writing Data
01 Reading From CSV (19:40)
02 Writing To CSV (20:41)
Introduction to DataFrames with Pandas Python Library - 04. Analytical Approaches to Data
01 Starting With An Analysis (21:22)
02 Locating Data By Labels (20:16)
03 Statistical Description Of Data (19:50)
04 Histogram Plots In Pandas (21:56)
05 Starting An Analysis Of All Our Data (21:12)
06 Continuing An Analysis Of All Our Data (16:52)
Introduction to Data Science with NumPy Python Library - Introduction
01. Introduction (2:34)
Numpy Arrays
01 Creating And Reshaping Numpy Arrays (21:04)
02 Creating Standard Numpy Arrays (21:05)
03 Creating Standard 2D Arrays (13:52)
04 Attributes On Numpy Arrays (19:09)
05 Resizing Arrays (13:19)
Manipulating Numpy Arrays
01 Writing An Array To File And Formating Strings (28:30)
02 Random Numbers (18:09)
03 Sorting In Numpy (22:56)
Calculations and Math
01 Calculations Within Numpy Arrays (22:30)
02 Math Functions With Numpy (22:56)
03 Integrating With Numpy (21:55)
04 Statistics With Numpy (20:39)
05 Polynomials (21:06)
06 Polynomials (Cont'd) (19:47)
Analyze and visualize stock returns with Pandas, NumPy and Pyplot
01 Visualize Stock Prices With Pyplot (4:21)
02 Calculate Yearly Returns On Crypto Stocks (4:06)
Source Files
Stock Portfolio Analysis with Python
00 Project Overview - Stock Portfolio Analysis With Python (2:35)
01 Build A Stock Portfolio (3:03)
02 Calculate Stock Portfolio Performance With Python (6:36)
03 Visualize Crypto Portfolio Returns With Pyplot (3:41)
04 Analyze Stock Portfolio Returns With Data Science (6:32)
05 Calculate Expected Cryptocurrency Returns With Pandas (3:04)
06 Visualize Stock Drawdowns With Python (4:13)
Source Files
Build a Trading Strategy with Indicators
01 Build Sma And Ema With Ta-Lib (4:46)
02 Calculate Bollinger Bands For Crypto Stock (5:00)
03 Calculate Rsi For Stocks With Python (4:25)
04 Calculate Obv For Crypto Price Prediction With Python (5:02)
05 Calculate Moving Average Convergence Divergence (3:21)
Source Files
Time Series Stock Forecasting on Crypto with Python
00 Project Overview - Time Series Stock Forecasting On Crypto Stock With Python (2:25)
01 Fit A Prophet Model For Stock Forecasting (10:08)
02 Visualize Stock Forecast With Python (2:47)
Source Files
Calculate stock risk and return with Python
01 Calculate Risk Vs Return Of Crypto Stock (5:55)
02 Visualize Risk Vs Return In Python (8:38)
Source Files
The Complete Recommender Systems Masterclass - Build 7 Projects
00-01 Introduction To Recommender Systems (9:08)
00-02 How To Evaluate Recommender Systems (14:54)
00-03 Content Based Recommendations (4:37)
00-04 Neighborhood Based Collaborative Filtering (2:22)
01-00 Project Preview (1:59)
01-01 Load Data As Pandas Dataframes (12:17)
01-02 Merge Movies And Ratings Dataframes (8:30)
01-03 Build A Correlation Matrix (6:20)
01-04 Test The Recommender (6:55)
Course Source Files
Projects Preview - Machine Learning Movie Recommender
00 Project Preview (4:51)
Machine Learning Fundamentals
00A What Is Machine Learning (5:26)
00B Types Of Machine Learning Models (12:17)
00C What Is Supervised Learning (11:03)
Introduction to User Similarity
01 Load Data Into Dataframes (6:50)
02 Find A Recommendation Based On Different Movie Features (16:03)
03 Calculate Distance Between Users (5:59)
04 Find Similar Users With Euclidean Distance (9:26)
Source Files
Recommend a Movie Based on User Similarity
01 Define Similarity Between Users (6:29)
02 Find Top Similar Users (8:05)
03 Recommend A Movie Based On User Similarity (8:08)
Source Files 5-7
Recommend a Movie with a K Nearest Neighbors Classifier
01 What Is K Nearest Neighbours (8:07)
02 Recommend A Movie With A K Nearest Neighbors Classifier (12:23)
03 Create A Sample User For Testing (11:09)
04 Recommend Movies To Sample User (3:08)
Source Files
Project Preview - Complex Machine Learning Recommender
00 Project Preview (4:38)
Data Processing Profiles and Items
01 Load Data For Machine Learning (15:14)
02 Process Data For Machine Learning (11:25)
03 Build Categories (9:31)
Source Files
Build Models for User Recommendations
01 What Is Regression (19:55)
02 Regression Introduction (8:58)
03 Build A Ridge Regression Model (13:43)
04 Evaluate Model Error (7:04)
05 Visualize Top Features Affecting Rating (11:27)
06 Build A Lasso Regression Model (8:01)
07 Visualize Top Features From Lasso Regression (8:07)
08 Determine Which Model Is Best (3:28)
Source Files
Build a Model to Predict Ratings
01 Load Data For A Neural Network (9:16)
02 Build A Singular Value Decomposition Algorithm (10:14)
03 Calculate Model Error (11:27)
Source FIles
Deep Learning Fundamentals
01 What Is Deep Learning (7:42)
02 What Is A Neural Network (8:47)
03 What Is Unsupervised Learning (8:17)
Build a Neural Network to Predict Ratings
01 Build A Neural Network (15:16)
02 Train The Neural Network (12:27)
Source Files
Data Analysis with Pandas, Numpy and Sci-kit Learn
00 Project Preview (2:38)
01 Load Data Into Dataframes (5:28)
02 Explore Data In Our Dataset (3:49)
03 Build A Rating Pivot Table (5:22)
04 Calculate Average Rating Of A Movie (5:51)
05 Find Ratings For A Movie In Every Slice (6:17)
06 Find Rating Averages For Every Movie In The Slice (7:54)
07 Build An Average Ratings Column (13:25)
Source Files
Course overview - Python Crypto Machine Learning
00 Course Overview - Python Crypto Machine Learning (6:11)
Source Files
Overview of Regression Models (Prerequisite)
00 Regression Introduction (8:58)
01 What Is Regression (19:55)
02 What Is Linear Regression (5:03)
Support Vector Machine Machine Learning (Prerequisite)
01 Why Do We Need SVM (7:15)
02 How Does SVM Work (6:28)
03 SVM On Non-Linear Data (4:48)
04 What Are SVM Kernels (4:44)
05 What Is The Precision-Recall Score (4:42)
Numpy Arrays
01 Creating And Reshaping Numpy Arrays (21:04)
02 Creating Standard Numpy Arrays (21:05)
03 Creating Standard 2D Arrays (13:52)
04 Attributes On Numpy Arrays (19:09)
05 Resizing Arrays (13:19)
Manipulating Numpy Arrays
01 Writing An Array To File And Formating Strings (28:30)
02 Random Numbers (18:09)
03 Sorting In Numpy (22:56)
Calculations and Math
01 Calculations Within Numpy Arrays (22:30)
02 Math Functions With Numpy (22:56)
03 Integrating With Numpy (21:55)
04 Statistics With Numpy (20:39)
05 Polynomials (21:06)
06 Polynomials (Cont'd) (19:47)
Compare regression techniques for crypto machine learning
00 Project Overview - Regression Machine Learning For Crypto Stocks (3:00)
01 Load Eth Data From Yahoo Finance With Python (3:45)
02 Build Regression Models To Predict Eth Price (7:14)
Regression source files
Decision Tree Machine Learning (Prerequisite)
01 Make Decisions With Decision Trees (10:51)
02 What Is The Random Forest Classifier Model (5:42)
Trees - Compare regression techniques for crypto machine learning
01 Build Tree Regression Models To Predict Crypto Price (2:55)
02 Compare Regression Model Results For Asset Prediction (3:18)
Trees - Source files
Build an AdaBoost machine learning model for stock prediction
01 Project Overview - Adaboost Stock Prediction (7:28)
01b What Is Ada Boost (5:48)
02 Build Stock Dataset For Machine Learning (5:33)
03 Build An Adaboost Regression Machine Learning Model For Stock Prediction (6:47)
04 Find Best Ml Model With Optimal Number Of Estimators (15:18)
AdaBoost Source Files
Overview of Classification Models
00 What Is Naive Bayes Machine Learning (1:34)
00b What Is K Nearest Neighbours (8:07)
01 What Is Gaussian Probability Distribution- (2:31)
Source files
Compare classification models for crypto machine learning
00 Project Overview - Classification Machine Learning For Crypto Stocks (7:05)
01 Load And Prepare Crypto Data In Colab (8:32)
02 Build Classification Models To Predict Stock (7:59)
03 Build Tree Classification Models To Predict Crypto Price (3:25)
04 Compare Classification Model Results With Numpy And Pandas (3:51)
Classification source files
Build a Support Vector Machine to Predict Trading
01 Load Yfinance Data Into Colab (4:10)
02 Build Trading Signals With Sma Windows (3:50)
03 Calculate And Visualize Strategy Returns (2:48)
04 Prepare Data For Machine Learning (6:40)
05 Build A Support Vector Classifier With Sklearn (3:01)
06 Calculate And Visualize Returns From Model (4:08)
SVM Source files
Trading Bot Masterclass - Course Overview
00 Course Overview (8:08)
Source Files
Scrape and Process Tweets
01 Get Twitter Developer API (6:49)
02 Get Latest Tweet Via API (12:53)
03 Check If Tweeted About Cryptocurrency (5:59)
Source Files
Tweet Sentiment Analysis
01 What Is Sentiment Analysis (10:28)
02 Analyze Tweet Sentiment (11:02)
Source Files
Buy Cryptocurrency Algorithmically - Test with Sandbox
01 Get Coinbase Pro Sandbox API (6:40)
02 Open Coinbase Pro Sandbox Account Via API (17:45)
03 Test Buy From Coinbase Sandbox Via API (7:44)
Source Files
Buy Cryptocurrency Algorithmically - Real Coins
01 Get Coinbase API (5:33)
02 Buy Cryptocurrency From API (6:56)
Source Files
Buy Doge with Kraken API
01 How To Access Kraken API (5:22)
02 Buy Doge Algorithmically (5:22)
Source Files
Run Bot All Day
01 Run Bot All Day (6:11)
Source Files
Data Analysis - Other Cryptos Affected by Tweets
00 Project Preview (3:25)
01 Fetch Crypto Stock Data (5:40)
02 Visualize Crypto Data (4:32)
03 Scrape Historical Tweets (13:11)
04 Filter Tweets About Crypto Only (4:21)
05 Visualize Tweet Effects On Crypto Value (7:05)
Source Files
How to Expand Bot
01 Challenge - How To Expand Bot (2:47)
Source Files
Stock Market Data Analysis and Visualization with Python, Pandas, NumPy, Seaborn and Matplotlib
00 Project Preview (3:17)
Compare Stocks and Returns
01 Fetch Stock Data (9:12)
02 Visualize Stock Data Features (7:32)
03 Calculate Daily Return (3:27)
04 Compare Returns Of Different Stocks (10:45)
05 Compare Closing Prices (8:48)
Source Files
Calculate and Visualize Risk
01 Visualize Standard Deviation And Expected Returns (5:44)
02 Calculate Value At Risk (3:52)
03 Monte Carlo Analysis To Estimate Risk (9:11)
04 Visualize Price Distribution (9:07)
Source Files
Build a Stock Ticker Dashboard Web App with Python, Dash and Pandas
00 Project Preview (3:00)
Build a Stock Ticker Website
00 Stock List CSV File
01 Import Stock Data (7:47)
02 Build A Dash Web App (6:19)
03 Build Stock And Date Range Pickers (10:04)
04 Show Stock Data In The Web App (14:51)
Source Files
Preprocess Twitter Sentiment and Stock Prices Data
01 Fetch Twitter Sentiment And Stock Prices Datasets (5:34)
02 Merge Datasets Into Dataframe (11:46)
Source Files
Build a Random Forest Classifier Machine Learning Model
00 Project Preview (2:27)
01 What Is The Random Forest Classifier Model (5:42)
02-03 Processing And Sorting Sentiment Data (14:40)
04 Calculate Stock Trend (Rising Or Falling) (8:16)
05 Build A Binary Encoding Of Sentiment (5:14)
06 Split And Scale Data (13:56)
07 Build A Random Forest Classifier Model (13:06)
08 Evaluate The Model (6:48)
Source Files
Build a Gradient Boosting Classifier
00 Project Preview (1:33)
01 What Is Gradient Boosting (1:56)
02 Test Different Learning Rates (8:09)
03 Make A Prediction With A Gradient Boosting Classifier (7:13)
04 Evaluate The Model (3:20)
Source Files
Course overview - Python Crypto Trading Strategies
Course Overview - Python Crypto Trading Strategies (4:39)
Introduction to the Stock Market
01 What Do Day Traders Trade (9:45)
02 What Is Volatility And Standard Deviation (3:33)
03 What Are The Best Assets To Day Trade (4:53)
04 Strategies For Stock Market Trading (2:37)
06 Stock Market Indicators (1:56)
07 Stock Market Lifecycle Trend Phases (2:20)
Source Files
Introduction to Data Science with NumPy Python Library - 00. Introduction
01. Introduction (2:34)
Numpy Arrays
01 Creating And Reshaping Numpy Arrays (21:04)
02 Creating Standard Numpy Arrays (21:05)
03 Creating Standard 2D Arrays (13:52)
04 Attributes On Numpy Arrays (19:09)
05 Resizing Arrays (13:19)
Manipulating Numpy Arrays
01 Writing An Array To File And Formating Strings (28:30)
02 Random Numbers (18:09)
03 Sorting In Numpy (22:56)
Calculations and Math
01 Calculations Within Numpy Arrays (22:30)
02 Math Functions With Numpy (22:56)
03 Integrating With Numpy (21:55)
04 Statistics With Numpy (20:39)
05 Polynomials (21:06)
06 Polynomials (Cont'd) (19:47)
Introduction to DataFrames with Pandas Python Library - 00. Setup
00. Setting Up Pandas (2:24)
Datastructures
01. Creating A Dataframe (22:42)
02. Sorting And Series (19:19)
03. Expanding A Dataframe (17:14)
Manipulating DataFrames
01 Getting Values And Dealing With Nan Values (21:29)
02 Dropping Rows And Columns (23:57)
Reading and Writing Data
01 Reading From CSV (19:40)
02 Writing To CSV (20:41)
Analytical Approaches to Data
01 Starting With An Analysis (21:22)
02 Locating Data By Labels (20:16)
03 Statistical Description Of Data (19:50)
04 Histogram Plots In Pandas (21:56)
05 Starting An Analysis Of All Our Data (21:12)
06 Continuing An Analysis Of All Our Data (16:52)
Simple Moving Averages Trading Strategy
00 Backtesting Simple Moving Averages Explained (2:05)
01 Load Data For Backtesting SMA With VectorBT (3:20)
02 Build Trading Strategies With VectorBT (3:40)
03 Simulate Portfolio With VectorBT (3:41)
04 Visualize Price Vs Stock Indicators (5:37)
SMA Source files
Big Three Trading Strategy
00 What Is The Big Three Trading Strategy (2:27)
01 Big Three Trading Strategy On Binance Coin (6:58)
02 Big Three Trading Strategy On 1 Year Of Stocks (2:38)
Big Three Trading Strategy Source Files
Exponential moving average trading strategy
00 EMA Trading Strategy For Crypto - Overview (2:57)
01 Load Data With Cryptometrics API (7:53)
02 Visualize Historical Stock Prices With Matplotlib (6:31)
03 Build Exponential Moving Average Trading Strategy (3:54)
04 Visualize Trading Strategy With Kaleido (4:40)
Source Files
Build autocorrelation for crypto stock prediction
00 Autocorrelation Explained For Crypto Stock Prediction (2:45)
01 Load Data For Crypto Price Autocorrelation With Pandas (5:52)
02 Visualize Crypto Price Data With Pyplot (3:14)
03 Apply Hodrick-Prescott Filter To Data With Python (4:10)
04 Calculate Autocorrelation With Python (3:25)
Autocorrelation Source Files
Algorithmic Trading with Python, Statistics and Pandas - Build Investing Strategies
00 Project Preview (1:58)
Build Your First Investing Strategy
01 Make An API Call (6:18)
02 Convert Data To A Pandas Dataframe (9:41)
05 Build An Excel File From The Pandas Dataframe (4:18)
03 Batch API Calls To Improve Performance (11:23)
04 Calculate The Number Of Shares To Buy (7:18)
Source Files
Find 50 Best Momentum Stocks with 2 Investing Strategies
00 Project 2 Preview (2:42)
01 Make An API Call (9:47)
02 Execute A Batch API Call (14:59)
03 Remove Low Momentum Stocks (6:06)
04 Calculate The Number Of Shares To Buy (7:53)
05 Find High Quality Momentum Stocks (11:42)
06 Calculate Momentum Percentiles (7:19)
07 Find The 50 Best Momentum Stocks (8:10)
08 Calculate New Number Of Shares To Buy (5:30)
09 Build An Excel File (3:41)
Source Files
Find 50 Best Value Stocks with 2 Investing Strategies
00 Project 3 Preview (1:55)
01 Build A Dataframe (5:58)
02 Remove Glamour Stocks (5:01)
03 Calculate The Number Of Shares To Buy (3:51)
04 Build A Composite Of Valuation Metrics (15:22)
05 Clean Dataframe (5:49)
06 Calculate Value Percentiles (4:50)
07 Find The 50 Best Value Stocks (6:58)
08 Calculate New Number Of Shares To Buy (3:24)
Source Files
02 Writing To CSV
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