Machine Learning for Finance

In this 4-hour course, you'll learn how to apply Machine Learning techniques to solve problems in finance. From stock price prediction using regression models to designing an optimal investment portfolio, this course provides hands-on experience with practical tools like NumPy, Matplotlib, and Pandas.

What I will be able to do after this course

• Master the fundamentals of exploratory data analysis (EDA) and feature engineering in financial data.
• Build predictive models for stock prices using Machine Learning techniques like Linear Regression and Neural Networks.
• Understand and implement ensemble learning methods, such as Random Forest and XGBoost, for financial data analysis.
• Design optimal investment portfolios using Modern Portfolio Theory and metrics like the Sharpe Ratio.
• Develop skills to detect fraudulent transactions using classification models and machine learning approaches.

Course Instructor(s)

Aryan Singh is an experienced data scientist with a focus on Machine Learning applications in the financial domain. With years of experience in fintech and a passion for teaching, Aryan is dedicated to making advanced technologies accessible to learners of all levels. In this course, Aryan combines hands-on practical instruction with in-depth theoretical insights.

Who is it for?

This course is tailored for professionals in the finance sector who are adept in Python and seek to specialize in Machine Learning application for fintech. If you aim to enhance your technical capabilities and want to harness the power of data-driven decision-making in finance, this course is ideal for you.