Python Pro Bootcamp

The ‘Algorithmic Trading & Quantitative Analysis Using Python’ course will teach you to build fully automated trading system and Implement quantitative trading strategies using Python. In this course, you will learn how to code and back test trading strategies using python.

The course will also give an introduction to relevant python libraries required to perform quantitative analysis. The course delves into API trading and familiarizes you with how to fully automate your trading strategies. The course is usually available for INR 2,799 on Udemy but you can click on the link and get the ‘Algorithmic Trading & Quantitative Analysis Using Python’ for INR 499.

Who all can opt for this course?

  • Anyone interested in quantitative analysis, including traders wishing to develop automated trading stations and automate their trading techniques

Course Highlights

Key HighlightsDetails
Registration LinkApply Now!
PriceINR 499 (INR 2,79980% off
Duration19.5 Hours
Student Enrollment28,792 students
InstructorMayank Rasu
Topics CoveredWeb Sraping, API, Automated Trading System, JSON
Course LevelAdvanced
Total Student Reviews3,417

Learning Outcomes

  • Python-based quantitative analysis and algorithmic trading
  • Execution of both technical analysis and fundamental analysis
  • Trading API

Course Content

S.No.Module (Duration)Topics
1.Introduction (24 minutes)What Is Covered in this Course?
Course Prerequisites
Is This For Me?
How To Get Help
Anaconda Distribution Intro
Creating Virtual Environment (Optional)
2.Getting Data (01 hour 16 minutes)Data Gathering Intro
yfinance Overview
yfinance – Getting Data for Multiple Stocks
yahoofinancials Library and Parsing JSON Data
yahoofinancials – Getting Data for Multiple Stocks
Alpha Vantage Python Library Intro
Alpha Vantage – Getting Data for Multiple Tickers
Other Free Data Resources
3.Web Scraping to Extract Financial Data (01 hour 11 minutes)Web Scraping Vs API Based Data Extraction
HTML Intro
Web Scraping Financial Data Using Python – I
Web Scraping Financial Data Using Python – II
Web Scraping Financial Data Using Python – III
4.Basic Data Handling and Operations (01 hour 03 minutes)Handling NaN Values
Basic Statistics – Familiarize Yourself With Your Data
Rolling Operations – Data In Motion
Visualization Basics – I
Visualization Basics – II
5.Technical Indicators (02 hours 39 minutes)Introduction to Technical Indicators
Introduction to Charting
MACD Overview
MACD Implementation in Python
ATR and Bollinger Bands Overview
ATR Implementation in Python
Bollinger Bands Implementation in Python
RSI Overview and Excel Implementation
RSI Implementation in Python
ADX Overview
ADX Implementation in Excel
ADX Implementation in Python
Renko Overview
Renko Implementation in Python
TA-Lib Introduction
TA-Lib Installation and Application
6.Performance Measurement – KPIs (49 minutes)Introduction to Performance Measurement
CAGR Overview
CAGR Implementation in Python
How to Measure Volatility
Volatility Measures’ Python Implementation
Sharpe Ratio and Sortino Ratio
Sharpe and Sortino in Python
Maximum Drawdown and Calmar Ratio
Maximum Drawdown and Calmar Ratio in Python
7.Backtest Your Strategies (02 hours 21 minutes)Why Should I Backtest My Strategies?
Strategy I – Portfolio Rebalancing
Strategy I in Python
Strategy II – Resistance Breakout
Strategy II in Python -I
Strategy II in Python -II
Strategy III – Renko and OBV
Strategy III in Python
Strategy IV – Renko and MACD
Strategy IV in Python
8.Value Investing (01 hour 10 minutes)Value Investing Overview
Introduction to Magic Formula
Magic Formula Implementation in Python
Updated Python Code – Yahoo-Finance Webpage Changes
Introduction to Piotroski F-Score
Piotroski F-Score Implementation in Python
Updated Python Code – Yahoo-Finance Webpage Changes
9.Building Automated Trading System on a Shoestring Budget (02 hours 42 minutes)Automated/Algorithmic Trading Overview
Using Time Module in Python
FXCM Overview
Introduction to FXCM Terminal
Building an Automated Trading System – part I
Building an Automated Trading System – part II
Building an Automated Trading System – part III
Building an Automated Trading System – part IV
OANDA Overview
SMA Crossover Strategy using OANDA API
10.Bonus Section: Running Your Algorithms in Cloud (01 hour 37 minutes)Why Cloud
Launching AWS EC2 Instance
Connecting To The EC2 Instance I
Connecting To The EC2 Instance II
Transferring Files to EC2 Instance
Scheduling/Automating Your Scripts Using Crontab
Keeping Track of Running Processes
Using Screen Command with Crontab
Shutting Down/Deleting EC2 Instance
11.Bonus Section: Sentiment Analysis (02 hours 21 minutes)Why Sentiment Analysis
Sentiment Analysis – Intuition
Natural Language Processing Basics
Lexicon Based Sentiment Analysis
VADER Introduction
Textblob Introduction
Building a Sentiment Analyzer using VADER – Part I
Building a Sentiment Analyzer using VADER – Part II
Machine Learning Based Sentiment Analysis
ML Feature Matrix & TF-IDF Introduction
Building ML Based Sentiment Analyzer – Part I
Building a ML Based Sentiment Analyzer – Part II
Building a ML Based Sentiment Analyzer – Part III
Sentiment Analysis Application – Opportunities & Challenges
12.Archived Lectures (02 hours 00 minutes)Archived Lectures – Important Note
Pandas Datareader Overview
Getting Data Using Pandas Datareader
OBV Overview and Excel Implementation
OBV Implementation in Python
Slope in a Chart
Slope Implementation in Python
Web Scraping Intro
Important Note – Yahoo Finance Web Scraping
Using Web Scraping to Extract Stock Fundamental Data – I
Using Web Scraping to Extract Stock Fundamental Data – II
Updated Web-Scraping Code – Yahoo-Finance Webpage Changes

Resources Required

  • Python proficiency at the intermediate level
  • Knowledge of mathematics and statistics at the high school level
  • Basic knowledge in FX and stock trading

Featured Review

Vikram B G (5/5) : Awesome course for the people who are looking forward to understanding algorithmic trading. I was impressed with the way the course was designed starting from the basics of python to introducing the machine learning concepts in trading. I will try to build on the knowledge this course gave me and become a successful trader. And finally, thank you MAYANK


  • Dan Treacher (5/5) : All the code is kept up to date, and the explanations are excellent.
  • Federico Borin (5/5) : very happy about the clarity of the explanations and the recommended tools.
  • Rahul Agarwal (5/5) : This Course is Great..and the Mayank has excellently explained each part.
  • Charles Demontigny (5/5) : Very good course! It helps you create an end-to-end automated trading plateform.


  • Kavan Motazedi (1/5) : The course is outdated and the code won’t work as it’s supposed to because of that, delivery is not good, and the instructor is also sniffing a lot.
  • Tushar Dwivedi (2/5) : I have done at least 50+ courses on Udemy, and trust me, none of them had this issue.
  • Sean Family (1/5) : The screen / board the instructor is using is extremely hard to see.
  • Tushar Dwivedi (2/5) : It’s because you have used normal (even smaller) font size while capturing your screen with some software, which recorded video in really terrible resolution, even if it claims 1080p.

About the Author

The instructor of this course is Mayank Rasu who is a Experienced Quant Researcher and Educator. With 4.6 Instructor Rating and 7,092 Reviews on Udemy, Instructor offers 9 Courses and has taught 47,544 Students so far.

  • Mayank Rasu has written and released best-selling courses and books on technology and money
  • He is passionate about making seemingly hard subjects like algorithmic trading, machine learning, and artificial intelligence understandable to students with no expertise in technology or finance
  • In the fields of quantitative analysis and risk management, he has more than ten years of experience working with major international investment banks
  • Mayank Rasu’s professional experience has solidified his conviction that he should constantly consider the qualitative parts of his work when making data-driven decisions
  • Mayank Rasu studied engineering for his undergraduate degree and have an MBA and MFE
  • Mayank Rasu consider himself to be a lifelong learner, and he greatly value the chance to impart his knowledge to others

Comparison Table

ParametersAlgorithmic Trading & Quantitative Analysis Using PythonAlgorithmic Trading using Interactive Broker’s Python APIQuantitative Finance & Algorithmic Trading in Python
OffersINR 499 (INR 2,799) 80% offINR 455 (INR 3,499) 87% offINR 455 (INR 3,499) 87% off
Duration19.5 hours12 hours15 hours
Rating4.5/54.6 /54.6 /5
Student Enrollments28,7927,32112,410
InstructorsMayank RasuMayank RasuHolczer Balazs
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