Hear From Our Instructor
Applied Machine Learning is the ideal next step for those interested in furthering their foundational Python skills. This is an advanced course that utilizes concepts learned from the Python Fundamentals course and combines them with popular machine learning algorithms from the popular Scikit-Learn Machine Learning Package to solve real-world business problems. Although this course can be taken by any business professional, we recommend taking Python Fundamentals prior to enrolling in Applied Machine Learning.
3 hours of video content.
Estimated 6 hours to complete.
Become one of the few in the Finance Industry that can write & use real patented algorithms for investment banking and capital markets decisions. By the end of the course, you will be trained to identify the ideal opportunities to apply this technology in your specific environment, so that you can immediately use your new skills to make an impact on your team and company.
- Multiple exercises and real case studies
- Liquidity Regressor Model: This model will help advise large corporations on raising capital. Corporations often ask for advice about how much liquidity they should maintain and how they stack up against peer companies. You will use 5 different regression algorithms to find the optimal solution based on a set of inputs.
- Investor Classifier Model: This model is an altered version of a real machine learning algorithm used by top investment banks to predict investor behavior when raising capital for large corporate clients. You will learn to use 4 different classification algorithms to determine which investors to invite to participate in the deal and how much capital you should invite them to commit.
Complete topics step by step or jump to any of the below at any time.
- Using the Scikit-Learn Machine Learning Package in Python
- Advanced data cleaning, exploration, and visualization
- Identifying opportunities in your workplace
- Regression algorithms
- Classification algorithms
- Using ML to advise corporations on raising capital
- Using ML to predict investor behavior
- Identifying overfit models and selecting optimal algorithms
- Splitting data into training and testing sets
- Constructing model pipelines with hyperparameter tuning
- Building and finalizing a machine learning classifier from start to finish
We recommend taking Python Fundamentals before enrolling in Applied Machine Learning.
We offer discounts for group orders on our self-study products. Group orders are an attractive option for companies or teams looking to upskill together.
Contact us at email@example.com to learn more about how to save money on group orders.
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