Algorithmic Trading with Python Complete Course

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Satyapal Singh

10:33:57

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1. Introduction

1. Introduction to Algorithmic Trading.mp4

07:44

2. Brokers and APIs.mp4

06:26

3. Setting up Environment.mp4

05:56

4. Introduction to Python Tools.mp4

09:56

2. Python for Data Science

1.1 1. arithmetic.zip

1. Arithmetic Operations in Python.mp4

09:36

2.1 2. data types.zip

2. Data Types.mp4

09:03

3.1 4. variables.zip

3. Variables.mp4

09:32

4.1 5. lists.zip

4. Intro to Lists.mp4

07:37

5. Lists 2.mp4

08:57

6. Lists 3.mp4

12:27

7.1 6. tuples-and-strings.zip

7. Tuples.mp4

06:36

8. Strings 1.mp4

06:36

9. Strings 2.mp4

05:54

10.1 7 dictionaries & sets.zip

10. Dictionaries.mp4

06:25

11. Sets.mp4

09:28

3. Python Pandas

1.1 1. pandas intro.zip

1.2 AAPL historical data.csv

1.3 bank data.csv

1.4 daily.csv

1.5 data.csv

1.6 IPL.csv

1.7 minute.csv

1.8 missing.csv

1.9 tick.csv

1.10 titanic.csv

1. Introduction to Pandas.mp4

09:47

2.1 2. pandas series part 1.zip

2. Pandas Series Part 1.mp4

04:30

3.1 3. pandas series part 2.zip

3. Pandas Series Part 2.mp4

07:32

4.1 4. pandas series unique.zip

4. Pandas Series Unique.mp4

05:29

5.1 5. sorting a series.zip

5. Pandas Series Sorting.mp4

04:35

6.1 6. dataframes intro.zip

6. Introduction to DataFrames.mp4

05:22

7.1 7 data from csv file.zip

7. Accessing csv files.mp4

05:10

8.1 8. data inspection.zip

8. Data Inspection.mp4

06:39

9.1 9. dataframes index.zip

9. Dataframe Indexing.mp4

03:04

10.1 10. dataframe filter.zip

10. Dataframe Filter.mp4

02:10

11.1 11. indexing in dataframes.zip

11. Dataframe Indexing Part 2.mp4

03:20

12.1 12. position based index iloc.zip

12. Position based indexing using iloc.mp4

07:03

13.1 13. index based slicing iloc.zip

13. Dataframe Slicing using iloc.mp4

04:27

14.1 14. label based slicing using loc.zip

14. Label based Slicing using loc.mp4

06:47

15.1 15. loc with numeric index.zip

15. Loc with numeric index.mp4

03:44

16.1 16. reset index.zip

16. Reset Index.mp4

03:54

17.1 17. rename columns.zip

17. Rename Columns.mp4

04:36

18.1 18. conditional filter.zip

18. Conditional Filter.mp4

05:01

19.1 19. advanced filter dataframe.zip

19. Advanced Filter.mp4

04:00

20.1 20. handling missing values - part 1.zip

20. Missing Values Part 1.mp4

02:28

21.1 21. handling missing values - part 2.zip

21. Missing Values Part 2.mp4

07:03

22.1 22. groupby.zip

22. Group By.mp4

05:37

4. Downloading Financial Data

1.1 23. introduction to time series data.zip

1. Intro to Time Series.mp4

03:29

2.1 27 downloading data yfinance api.zip

2. Downloading Data yfinance API.mp4

03:56

3.1 24. convert string to datetime column.zip

3. String to Datetime.mp4

04:18

5. Financial Data Analysis using Python

1.1 25. slice time series data.zip

1. Slice Time Series Data.mp4

03:17

2.1 28. pivot.zip

2. Pivot DataFrame.mp4

05:12

3.1 26. resample.zip

3. Resample DataFrame.mp4

08:19

4.1 29. data normalization.zip

4. Data Normalization.mp4

05:45

6. Financial Returns

1.1 30. calculate price changes.zip

1. Calculate Price Changes.mp4

03:49

2.1 31. calculate financial returns.zip

2. Calculate Financial Returns.mp4

02:01

3.1 32. risk vs reward.zip

3. Risk vs Returns.mp4

04:17

4.1 33. tvpi or multiples.zip

4. TVPI.mp4

03:54

5.1 34. cagr vs annual returns.zip

5. CAGR.mp4

03:22

6.1 35. geometric returns.zip

6. Geometric Returns.mp4

02:45

7.1 36. simple vs compound interest.zip

7. Simple vs Compound Interest.mp4

07:22

8.1 37 continuous compounding.zip

8. Continuous Compounding.mp4

05:35

9.1 38. intro to log returns.zip

9. Intro to log Returns.mp4

04:22

10.1 39. daily returns vs log returns.zip

10. Daily Return vs Log Returns.mp4

05:41

11.1 40. more about log returns.zip

11. More About Log Returns.mp4

04:30

7. Important Concepts in Stock Market

1. Instruments for Trading.mp4

06:21

2. Common Terms in Stock Market - I.mp4

12:17

3. Common Terms in Stock Market -II.mp4

13:15

4. Derivatives Risk.mp4

05:40

5. Intro to Futures.mp4

11:44

6. Intro to Options.mp4

05:52

8. Broker API Zerodha Kite Connect

1. Creating Kite Connect App.mp4

06:07

2.1 login - manual process.zip

2. Manual Login.mp4

07:18

3.1 access.txt

3.2 security.txt

3.3 selenium kite connect login new.zip

3. Automatic Login using Selenium.mp4

10:02

4.1 databaselogin.zip

4.2 download instruments.zip

4.3 instruments.zip

4. Downloading Instruments.mp4

11:55

5.1 daily+ohlc.zip

5.2 databaselogin.zip

5.3 download historical data.zip

5. Download Historical OHLC Data.mp4

05:50

6.1 databaselogin.zip

6.2 place+orders+using+api.zip

6.3 zerodha+orders+management.zip

6.4 zerodha+wrapper+class.zip

6. Place and Manage Orders.mp4

09:08

7.1 databaselogin.zip

7.2 other important functions.zip

7. Other Important Functions.mp4

04:00

8. Introduction to Kite Ticker.mp4

04:57

9.1 database.zip

9.2 tick.zip

9.3 tick+data+table.zip

9. Downloading Realtime Tick Data.mp4

09:56

10.1 option chain.zip

10. Option Chain Data.mp4

07:09

11.1 alarm.wav

11.2 databaselogin.zip

11.3 moniter+prices.zip

11.4 monitor+stock+price.zip

11. Get Price Alerts.mp4

04:56

9. Technical Analysis

1. Introduction to Technical Indicators.mp4

05:21

2.1 moving averages.zip

2.2 nifty.csv

2. Moving Averages.mp4

07:36

3.1 macd.zip

3. Moving Average ConvergenceDivergence (MACD).mp4

06:18

4.1 bollinger bands.zip

4. Bollinger Bands.mp4

07:11

5.1 atr.zip

5. Average True Range (ATR) Part 1.mp4

04:48

6. Average True Range (ATR) Part 2.mp4

07:13

7.1 rsi.zip

7.2 rsi.zip

7. Relative Strength Indicator (RSI) Part 1.mp4

08:51

8. Relative Strength Indicator (RSI) Part 2.mp4

09:44

9. Introduction to Supertrend.mp4

03:44

10.1 Super+Trend.xlsx

10. Supertrend using Google SheetsExcel.mp4

11:29

11.1 supertrend.zip

11. Supertrend using Python.mp4

09:38

12. Introduction to Renko.mp4

05:15

13.1 minute.csv

13.2 renko+-+brick+size.zip

13. Renko using Brick Size.mp4

05:15

14.1 renko atr display.zip

14. Visualize Renko Chart with ATR.mp4

04:58

15. Introduction to ADX.mp4

04:52

16.1 ADX.xlsx

16. ADX using Google SheetExcel.mp4

07:25

17.1 adx.zip

17. ADX using Python.mp4

04:57

10. Price Action

1. Introduction to Price Action.mp4

02:56

2. About Candlesticks.mp4

04:43

3. Support and Resistance.mp4

04:30

4. Introduction to Pivot Points.mp4

02:42

5.1 infy2023.csv

5.2 infy5min.csv

5.3 pivot point.zip

5. Pivot Points with Python.mp4

05:12

11. Strategy Development

1. Introduction to Strategy Development.mp4

04:33

2.1 mydatabase.zip

2.2 OHLCNifty.csv

2.3 sma+crossover+strategy+basic.zip

2. SMA Strategy Backtesting.mp4

08:02

3.1 sma+optimal+strategy.zip

3. Strategy Optimization.mp4

05:21

4.1 Supertrend.zip

4. Supertrend + MACD Strategy Part 1.mp4

07:03

5. Supertrend + MACD Strategy Part 2.mp4

07:48

12. Cloud VPS Deployment

1. Introduction to VPS.mp4

04:17

2. Virtual Private Server Deployment & Scheduling.mp4

05:39

3. Accessing strategy from VPS using a browser.mp4

03:44

Description

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

Who is this for?

Software Developers, Algo Traders, Software Students

What You Need to Know?

Basics of Stock Market/ Trading

Beginner level programming skills

More details

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.Â 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.
Who this course is for:
Software Developers, Algo Traders, Software Students

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20 years of experience as a Developer, Business Analyst, Investor & TraderDevelopment experience in .Net, Python, Microsoft SQL Server, MySQL, Web Development, Android, and iOS. Broad knowledge of Information Technology.5 years experience as an Investor & 2 years experience in Algo trading.Expert on Zerodha Kite Connect Integration using Python & MySql.Ex Developer at Honeywell International India LtdFounder & Chief Executive at Kimbly LabsCompleted Executive Programme in Algorithmic Trading - EPAT Microsoft Certified Professional (MCP/MCSD)Consultancy services are available.

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