Algorithmic Trading With Python Complete Course

Most Comprehensive Algorithmic Trading Course

What you'll learn

Python for Algo Trading including Pandas

Learn to Develop Trading Bots

Use Zerodha Kite Connect API for Algo Trading

Create Technical Indicators using python

Develop and Backtest Algo Trading Strategies

Requirements

Basics of Stock Market/ Trading

Beginner level programming skills

Description

Welcome to our most comprehensive course, "Algorithmic Trading using Python," where you will embark on a transformative journey into the world of algorithmic trading. This course is designed to provide you with a solid foundation in both Python programming and algorithmic trading strategies, catering to beginners and experienced developers alike.The course begins with a thorough exploration of Python's Object Oriented Programming (OOP) to equip you with the essential skills for algorithmic trading. You will delve into data analysis using Pandas, mastering the manipulation of financial data with ease. Utilizing libraries such as Numpy and Matplotlib, you will gain proficiency in numerical computations and data visualization.The course covers data normalization and the calculation of financial returns, essential steps in developing robust trading strategies. Dive into finance and investment concepts to understand the intricacies of the market.Learn to communicate with broker API using Python code. Automation Login using Selenium. Harness the potential of Zerodha Kite Connect API to implement your strategies seamlessly. In the realm of algorithmic trading, real-time data is paramount. Learn to stream live tick data and efficiently download and clean historical financial data. Order Management - Placing orders, modifying, canceling, placing & trail stop loss orders.  This course includes frequently asked questions & prerequisites for the API.Use MySQL Database to save and access Data. Import and export data using static files.Technical indicators play a pivotal role in trading decisions. This course empowers you to develop indicators like Moving Averages, Bollinger Bands, ATR, Relative Strength, MACD, Supertrend, and Renko using Python.Take your skills to the next level by learning to deploy your trading bot on a Virtual Private Server, accessible through a user-friendly web page. Achieve the pinnacle of automation as you develop a fully automatic trading bot, ready to navigate the financial markets.The course has all working code Jupyter notebooks available in the resources section. Whether you're a novice seeking a comprehensive introduction or an experienced developer aiming to enhance your algorithmic trading prowess, this course provides the knowledge and hands-on experience needed to succeed in the dynamic world of algorithmic trading using Python. Join us on this exciting journey and unlock the potential of algorithmic trading in the financial markets.

Overview

Section 1: Introduction

Lecture 1 Introduction to Algorithmic Trading

Lecture 2 Brokers and API's

Lecture 3 Setting up Environment

Lecture 4 Introduction to Python Tools

Section 2: Python for Data Science

Lecture 5 Arithmetic Operations in Python

Lecture 6 Data Types

Lecture 7 Variables

Lecture 8 Intro to Lists

Lecture 9 Lists 2

Lecture 10 Lists 3

Lecture 11 Tuples

Lecture 12 Strings 1

Lecture 13 Strings 2

Lecture 14 Dictionaries

Lecture 15 Sets

Section 3: Python Pandas

Lecture 16 Introduction to Pandas

Lecture 17 Pandas Series Part 1

Lecture 18 Pandas Series Part 2

Lecture 19 Pandas Series Unique

Lecture 20 Pandas Series Sorting

Lecture 21 Introduction to DataFrames

Lecture 22 Accessing csv files

Lecture 23 Data Inspection

Lecture 24 Dataframe Indexing

Lecture 25 Dataframe Filter

Lecture 26 Dataframe Indexing Part 2

Lecture 27 Position based indexing using iloc

Lecture 28 Dataframe Slicing using iloc

Lecture 29 Label based Slicing using loc

Lecture 30 Loc with numeric index

Lecture 31 Reset Index

Lecture 32 Rename Columns

Lecture 33 Conditional Filter

Lecture 34 Advanced Filter

Lecture 35 Missing Values Part 1

Lecture 36 Missing Values Part 2

Lecture 37 Group By

Section 4: Downloading Financial Data

Lecture 38 Intro to Time Series

Lecture 39 Downloading Data yfinance API

Lecture 40 String to Datetime

Section 5: Financial Data Analysis using Python

Lecture 41 Slice Time Series Data

Lecture 42 Pivot DataFrame

Lecture 43 Resample DataFrame

Lecture 44 Data Normalization

Section 6: Financial Returns

Lecture 45 Calculate Price Changes

Lecture 46 Calculate Financial Returns

Lecture 47 Risk vs Returns

Lecture 48 TVPI

Lecture 49 CAGR

Lecture 50 Geometric Returns

Lecture 51 Simple vs Compound Interest

Lecture 52 Continuous Compounding

Lecture 53 Intro to log Returns

Lecture 54 Daily Return vs Log Returns

Lecture 55 More About Log Returns

Section 7: Important Concepts in Stock Market

Lecture 56 Instruments for Trading

Lecture 57 Common Terms in Stock Market - I

Lecture 58 Common Terms in Stock Market -II

Lecture 59 Derivatives Risk

Lecture 60 Intro to Futures

Lecture 61 Intro to Options

Section 8: Broker API: Zerodha Kite Connect

Lecture 62 Creating Kite Connect App

Lecture 63 Manual Login

Lecture 64 Automatic Login using Selenium

Lecture 65 Downloading Instruments

Lecture 66 Download Historical OHLC Data

Lecture 67 Place and Manage Orders

Lecture 68 Other Important Functions

Lecture 69 Introduction to Kite Ticker

Lecture 70 Downloading Realtime Tick Data

Lecture 71 Option Chain Data

Lecture 72 Get Price Alerts

Section 9: Technical Analysis

Lecture 73 Introduction to Technical Indicators

Lecture 74 Moving Averages

Lecture 75 Moving Average Convergence/Divergence (MACD)

Lecture 76 Bollinger Bands

Lecture 77 Average True Range (ATR) Part 1

Lecture 78 Average True Range (ATR) Part 2

Lecture 79 Relative Strength Indicator (RSI) Part 1

Lecture 80 Relative Strength Indicator (RSI) Part 2

Lecture 81 Introduction to Supertrend

Lecture 82 Supertrend using Google Sheets/Excel

Lecture 83 Supertrend using Python

Lecture 84 Introduction to Renko

Lecture 85 Renko using Brick Size

Lecture 86 Visualize Renko Chart with ATR

Lecture 87 Introduction to ADX

Lecture 88 ADX using Google Sheet/Excel

Lecture 89 ADX using Python

Section 10: Price Action

Lecture 90 Introduction to Price Action

Lecture 91 About Candlesticks

Lecture 92 Support and Resistance

Lecture 93 Introduction to Pivot Points

Lecture 94 Pivot Points with Python

Section 11: Strategy Development

Lecture 95 Introduction to Strategy Development

Lecture 96 SMA Strategy Backtesting

Lecture 97 Strategy Optimization

Lecture 98 Supertrend + MACD Strategy Part 1

Lecture 99 Supertrend + MACD Strategy Part 2

Section 12: Cloud VPS Deployment

Lecture 100 Introduction to VPS

Lecture 101 Virtual Private Server Deployment & Scheduling

Lecture 102 Accessing strategy from VPS using a browser

Software Developers, Algo Traders, Software Students