Advanced Quantitative Finance & Algorithmic Trading Masterclass with Python & Machine Learning

Quant Finance & Python Trading

Master Python, Data Science, and API-based Automation to launch a high-growth career in Quantitative Analysis and Algorithmic Trading.

Navya Honey

English

Certificate Course

0 Students

00h 00m

Course Overview

The Advanced Quantitative Finance & Algorithmic Trading Masterclass teaches students to build and deploy automated trading strategies using Python, Pandas, NumPy, Scikit-Learn, and backtesting frameworks. Students will learn to analyze market data, design quantitative models, and implement machine learning-driven trading systems.

This course is unique because it focuses on practical, real-world trading applications, helping learners solve challenges like strategy optimization, risk management, and portfolio automation. It equips students with the skills needed to navigate volatile markets effectively.

Industry relevance is high, with demand for professionals in hedge funds, prop trading, and fintech, making the skills immediately applicable to real-world roles.

By the end, learners will be able to design, test, and execute algorithmic trading strategies, gaining a strong portfolio of hands-on projects and job-ready expertise.

FAQ

Basic understanding of Python and familiarity with mathematics or statistics is recommended. No prior trading experience is required.

Yes, the course is designed to accommodate beginners with Python knowledge while also providing advanced content for experienced learners.

Students will work with Python, Pandas, NumPy, SciPy, Scikit-Learn, Jupyter Notebook, Backtrader, QuantConnect Lean, and market APIs such as Interactive Brokers and Zerodha Kite Connect.

Yes, all students who complete the course and its assessments will receive an industry-recognized certificate of completion.

The course includes hands-on projects, backtesting exercises, and a capstone project that simulates real-world algorithmic trading scenarios.

Yes, the course is designed to provide job-ready skills relevant to roles like Quantitative Analyst, Algo Trader, Financial Data Scientist, and Portfolio Manager.

Students get lifetime access to all course materials, including videos, code examples, and downloadable resources.

Yes, each module includes quizzes and assignments to reinforce learning, along with projects to apply your knowledge practically.

Yes, the course is self-paced, allowing students to progress according to their individual schedules

Yes, dedicated mentor support is available to help with doubts, coding challenges, and project guidance.

Course curriculum

Requirment

Basic understanding of mathematics, especially probability and statistics
Fundamental knowledge of Python programming (variables, loops, functions)
A laptop with Python, Jupyter Notebook, and necessary libraries installed
Interest in financial markets and algorithmic trading concepts

Outcomes

Understand quantitative finance principles like returns, volatility, and risk models
Build and test algorithmic trading strategies using Python
Use financial data libraries to analyze markets and automate trades
Evaluate performance using backtesting, optimization, and risk metrics
Gain practical skills for careers in quant trading, fintech, or investment analytics

Instructor

Navya Honey

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₹ 18999

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Students
0
language
English
Duration
00h 00m
Level
advanced
Expiry period
12 Months
Certificate
Yes