Mastering Quantitative Trading: Python, AI & Algorithmic Strategies
- Level
- Intermediate
- Duration
- 16 weeks
- Each week
- 3 hours
- Mode
- Online
- Fee
- Free
Launch Your Career in High-Frequency Finance
In the rapidly evolving financial landscape, quantitative trading has emerged as the most sophisticated approach to global markets. Combining mathematics, computer science, and financial theory, algorithmic trading now accounts for over 70% of global equity volumes.
Edu Global Institute’s Quantitative Trading Course is a rigorous, comprehensive program designed to take you from foundational mathematics to deploying advanced, AI-driven algorithmic strategies. Whether you are in India, the USA, the UK, or the UAE, this course equips you with the exact tools hedge funds and proprietary trading firms demand.
Why Choose Edu Global Institute?
- Learn from the Best: Taught by industry experts with deep experience in market microstructure and algorithmic execution.
- Tech-Driven Curriculum: Heavy focus on Python, Machine Learning, and Artificial Intelligence (AI) in trading.
- Global Certification: Earn a globally recognized Algorithmic Trading Certification.
- Dedicated Career Placement: Resume optimization, mock interviews, and direct placement assistance with top trading firms.
The Comprehensive Syllabus
Module 1: The Absolute Foundations (Mathematics & Statistics)
- Probability Theory & Statistical Inference
- Linear Algebra & Principal Component Analysis (PCA) for factor modeling
- Calculus and Convex Optimization for portfolio management
Module 2: Programming & Data Architecture (Python Mastery)
- High-performance data manipulation with
NumPyandPandas - Managing tick-level data and working with time-series databases
- Hands-on Project: Building a high-speed financial data ingestion pipeline
Module 3: Financial Markets & Microstructure
- Understanding Equities, Fixed Income, Futures, and Derivatives (Greeks)
- Deep dive into Market Microstructure: The Limit Order Book (LOB) and order types
- Liquidity, bid-ask spreads, and maker-taker models
Module 4: Time Series Analysis for Trading
- Stationarity testing (ADF, Hurst Exponent) and fractional differencing
- Linear models (ARIMA) and Volatility modeling (GARCH)
- Cointegration and the mathematics of Statistical Arbitrage (Pairs Trading)
Module 5: Algorithmic Strategy Design & Backtesting
- Strategy Types: Mean Reversion, Trend Following, and Market Making
- The Science of Backtesting: Avoiding look-ahead bias and overfitting
- Hands-on Project: Developing and backtesting a Pairs Trading strategy from scratch
Module 6: Portfolio Management & Risk
- Position Sizing: The Kelly Criterion
- Modern Portfolio Theory and the Efficient Frontier
- Advanced Risk Management: Value at Risk (VaR) and Conditional VaR
Module 7: Advanced Machine Learning & AI in Finance
- Why standard ML fails in finance (and how to fix it with Purged Cross-Validation)
- Feature Engineering: Dollar bars, Meta-labeling
- Implementing Gradient Boosting (XGBoost) and Deep Learning for signal generation
What students will be able to do
- Build and backtest a trading strategy in Python
- Work with pandas and NumPy on real market data
- Measure performance using Sharpe ratio, drawdown and other standard metrics
- Recognise overfitting and survivorship bias in a backtest
- Understand how execution costs and slippage change a result
Common questions
Is programming experience required?
Basic Python helps. The course begins with the data-handling libraries rather than assuming quantitative finance experience.
Which libraries are used?
pandas and NumPy for data, matplotlib for visualisation, and scikit-learn where a strategy uses machine learning.
Does this teach how to make money trading?
No. It teaches the quantitative methods used in the field: data handling, backtesting and risk measurement. No strategy is presented as profitable.
What roles does this lead towards?
Quantitative analysis, algorithmic trading and data science. Most such roles also expect strong statistics and probability.
Is mathematics needed?
Yes. Probability, statistics and linear algebra at Class 12 level or above underpin most of the material.
Book a trial
Three sessions with the mentor who would teach the full course. Nothing is charged until your slot is confirmed.
- A diagnostic, a taught class and written feedback
- Taught by the mentor who leads the course
- You pick the slot from our live calendar
- Pay only after the slot is confirmed
- Level
- Intermediate
- Duration
- 16 weeks
- Each week
- 3 hours
- Mode
- Online
- Fee
- Free
Ask a question, or book a trial
Tell us about the student and we will reply with an honest view of whether this programme fits. If you would like to see the teaching first, add a trial class.
- No obligation - send the enquiry without booking anything
- Three sessions if you do book: a diagnostic, a taught class and feedback
- Taught by the mentor who would lead the full course
- You choose the slots from our calendar after payment
| Class 1 to 5 | 3 sessions | INR 599 |
| Class 6 to 8 | 3 sessions | INR 799 |
| Class 9 and 10 | 3 sessions | INR 899 |
| Class 11 and 12 | 3 sessions | INR 999 |
| Graduation and above | 4 sessions | INR 1,099 |
Sending an enquiry is free. The fee applies only if you tick the trial box below.