Share Description
In this course, you will:
- Learn about statistical learning, which will serve as a foundation for understanding the mechanics of machine learning.
- Explore supervised learning utilizing tree-based models and neural networks, as well as unsupervised learning with K-means and hierarchical clustering.
- Learn about the process of uncovering more robust patterns to ensure that models are useful.
- This course is designed for professionals looking to fill any gaps in their data science skills and expertise. The technical nature of the content would assist IT workers looking to quickly expand their data science toolset with proven and practical abilities.
- Professionals from various industries will learn how to use key data and programming skills to increase efficiencies and identify new opportunities for their organization.
Syllabus:
- Data science and statistical learning
- Tree-based methods
- Managing the complexity of tree-based methods
- Neural networks
- Managing the complexity of neural networks
- K-means clustering
- Hierarchical clustering
- Data science in the real world
