Python & Machine Learning for Financial Analysis
Master Python Programming Fundamentals and Harness the Power of ML to Solve Real-World Practical Applications in Finance
4.52 (4559 reviews)
101,857
students
23 hours
content
Jun 2024
last update
$84.99
regular price
What you will learn
Master Python 3 programming fundamentals for Data Science and Machine Learning with focus on Finance.
Understand how to leverage the power of Python to apply key financial concepts such as calculating daily portfolio returns, risk and Sharpe ratio.
Understand the theory and intuition behind Capital Asset Pricing Model (CAPM)
Understand how to use Jupyter Notebooks for developing, presenting and sharing Data Science projects.
key Python Libraries such as NumPy for scientific computing, Pandas for Data Analysis, Matplotlib/Seaborn for data plotting/visualization
Master SciKit-Learn library to build, train and tune machine learning models using real-world datasets.
Apply machine and deep learning models to solve real-world problems in the banking and finance sectors
Understand the theory and intuition behind several machine learning algorithms for regression, classification and clustering
Assess the performance of trained machine learning regression models using various KPI (Key Performance indicators)
Assess the performance of trained machine learning classifiers using various KPIs such as accuracy, precision, recall, and F1-score.
Understand the underlying theory, intuition behind Artificial Neural Networks (ANNs), Recurrent Neural Networks (RNNs) & Long Short Term Memory Networks (LSTM).
Train ANNs using back propagation and gradient descent algorithms.
Optimize ANNs hyper parameters such as number of hidden layers and neurons to enhance network performance.
Master feature engineering and data cleaning strategies for machine learning and data science applications.
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udemy ID
8/18/2020
course created date
9/25/2020
course indexed date
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