This bundle is designed to provide professionals with essential machine learning skills using Python, empowering you to analyze data effectively and uncover meaningful insights for your business.

You’ll receive a comprehensive introduction to state-of-the-art machine learning techniques, covering how algorithms function, how to engineer features for the best predictive models, and strategies for fine-tuning models to achieve optimal predictive performance.

The curriculum is tailored to professionals from any field and does not require prior knowledge of advanced mathematics, statistics or Python. Participants will develop practical, actionable skills through immersive, hands-on labs utilizing free and open-source software.

Topics Include:

Upon completion of this course, you will learn:

• The foundational skills of Python programming, using Jupyter notebooks, understanding data types and structures, managing control flow, creating functions, handling data tables, and visualizing data effectively.
• The different types of machine learning and supervised learning.
• The CART classification tree algorithms including their mathematical foundations and implementations.
• Techniques for tuning CART models and evaluating their accuracy to optimize performance.
• Exploration of overfitting in machine learning and strategies to address the bias-variance tradeoff.
• Feature engineering principles for enhancing decision tree predictive models.
• Insights into the random forest algorithm, its advantages for production systems, and methods for fine-tuning.
• Access to additional resources for further development of machine learning expertise.