ML Finance – Machine Learning In Finance
Master the most in-demand skill-set of the world’s top financial institutions with one of the most practical, comprehensive and affordable courses in Financial Machine Learning.
15+ Real-World Practical Applications
Case studies along with their python-based implementation.
Financial Applications Coverage
Algo Trading
Portfolio Management
Fraud detection
Leanding and Loand Default prediction
Sentiment Analysis
Derivatives Pricing and Hedging
Asset Price Prediction
and many more
Who Should Take The Course
Buy/sell side quants
Asset/Wealth Managers
CXOs
Data Scientists
Machine Learning Engineers
Students targeting finance sector
Business Analysts
AI/ML enthusiasts
What You’ll Learn In Machine Learning In Finance
Apply machine and deep learning models to solve real-world problems in finance.
Understand the theory and intuition behind several machine learning algorithms for regression, classification and clustering
Understand the underlying theory, intuition and mathematics behind Artificial Neural Networks (ANNs) and Deep Neural network.
Different machine learning based cutting-edge approaches to portfolio optimization.
Master Python 3 programming fundamentals for Data Science and Machine Learning with focus on Finance.
Leverage the power of Python to apply key financial concepts such as calculating daily portfolio returns, risk and Sharpe ratio.
Use key Python Libraries such as NumPy for scientific computing, Pandas for Data Analysis, Matplotlib for data plotting/visualization, and Keras, tensorflow for deep learning.
Assess the performance of trained machine learning regression models using various KPIs.
Train ANNs using back propagation and gradient descent algorithms.
Master feature engineering and data cleaning strategies for machine learning and data science applications.
