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    Stock Market Data Analysis Using Chatgpt & Python

    Posted By: ELK1nG
    Stock Market Data Analysis Using Chatgpt & Python

    Stock Market Data Analysis Using Chatgpt & Python
    Published 5/2023
    MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
    Language: English | Size: 2.01 GB | Duration: 3h 36m

    Mastering Technical Analysis and Algorithmic Trading in Python using ChatGPT

    What you'll learn

    Use ChatGPT to create technical analysis using Python

    Understand various technical indicators and their applications in trading.

    Backtest trading strategies and evaluate performance using Python programming language.

    Gain practical experience by building and testing trading algorithms in real market conditions.

    Requirements

    Basic understanding of financial markets and investment concepts

    Familiarity with programming languages like Python

    Understanding of basic mathematical concepts

    Familiarity with data analysis and visualization tools such as Pandas, Numpy

    Description

    The course "Quantitative Analysis using ChatGPT & Python" is designed for individuals interested in learning how to analyze their trading strategies and backtest their trading ideas using Python & ChatGPT. This course provides a practical introduction to algorithmic trading, including the basics of quantitative analysis and technical analysis.Through a step-by-step approach, this course teaches students how to develop and implement trading strategies using Python. The course starts by introducing the basics of Python programming, data analysis, and visualization, and then moves on to more advanced topics such as statistical modeling, time series analysis, and machine learning.The course also covers popular trading indicators, such as moving averages, Bollinger Bands, and Relative Strength Index (RSI), and shows students how to implement these indicators in Python to generate trading signals.In addition, students will learn how to use Python libraries such as pandas, NumPy, and Talib for data analysis and how to backtest their trading strategies.By the end of the course, students will have a solid understanding of algorithmic trading, backtesting, and the Python programming language, enabling them to develop and implement their own automated trading strategies.This course is ideal for individuals who have a basic understanding of financial markets and trading concepts and are looking to learn how to automate their trading strategies. Some prior programming experience, preferably in Python, would be helpful but is not required.

    Overview

    Section 1: Introduction to Stock Market Data Analysis

    Lecture 1 Introduction

    Lecture 2 What is the stock market & why data analysis is important for trading

    Lecture 3 What is ChatGPT and how can it be used for stock market data analysis

    Lecture 4 Overview of the course curriculum

    Section 2: Data Collection, Storage and Preparation using ChatGPT

    Lecture 5 Overview of different sources of stock market data

    Lecture 6 Retrieving data from different sources (e.g. APIs, CSV files, websites)

    Lecture 7 Fetching data from Yahoo Finance

    Lecture 8 Fetching data from Alpha Vantage

    Lecture 9 Fetching data from Quandl

    Lecture 10 Scraping data from NSE (Educational purpose only)

    Lecture 11 Scraping data from Nasdaq (Educational purpose only)

    Lecture 12 Storing data in a MySQL database (optional) using ChatGPT

    Section 3: Technical Indicators & ChatGPT

    Lecture 13 Understanding the basics of technical indicators and how they are used

    Lecture 14 Moving Average using ChatGPT

    Lecture 15 RSI using ChatGPT

    Lecture 16 Bollinger Bands using ChatGPT

    Section 4: Strategy Creation & Backtesting & Performance Measurement using ChatGPT

    Lecture 17 How a trading strategy is created

    Lecture 18 Creating a Trading Strategy Plan

    Lecture 19 Creating the Trading Strategy

    Lecture 20 Performance Measurement

    Section 5: Next Steps & Conclusion

    Lecture 21 Next Steps & Conclusion

    Anyone interested in learning about trading algorithms,Traders, Investors, Finance professionals, and students looking to gain hands-on experience in algorithmic trading,Python programmers