Advance Your Skills as a Machine Learning Specialist

Courses under this program:
Course 1: Machine Learning with Python: Decision Trees
-Learn how to build decision trees in Python to measure impurity within a partition and improve outcomes on machine learning projects.

Course 2: Machine Learning with Python: k-Means Clustering
-Learn the basics of k-means clustering, one of the most popular unsupervised machine learning approaches.

Course 3: Machine Learning with Python: Association Rules
-Explore the unsupervised machine learning approach known as association rules, as well as a step-by-step guide on how to use the approach for market basket analysis in Python.

Course 4: Machine Learning with Python: Logistic Regression
-Get an introduction to logistic regression by exploring how to build supervised machine learning models with Python.

Course 5: Machine Learning and AI Foundations: Producing Explainable AI (XAI) and Interpretable Machine Learning Solutions
-Learn best practices for how to produce explainable AI and interpretable machine learning solutions.

Course 6: Machine Learning and AI Foundations: Decision Trees with KNIME
-Expand your data science skills and establish a strong foundation in codeless machine learning.

Course 7: Machine Learning and AI Foundations: Causal Inference and Modeling
-Learn about the modeling techniques and experimental designs that allow you to establish causal inference, and how to use them.

Course 8: Machine Learning and AI Foundations: Prediction, Causation, and Statistical Inference
-Gain insights to help improve your machine learning models and statistical analyses.

Course 9: Deep Learning: Model Optimization and Tuning (2022)
-Learn about various optimization and tuning options available for deep learning models and use them to improve models.