On completion of this course, you’ll walk away with: The ability to apply data science and analysis techniques to inform decision-making. The tools to build and modify robust models in order to help solve business problems. A practical grounding in the widely used Jupyter Notebook. The ability to fit data to a model using Python in order to gain insight into business problems. A certificate of completion from UCT as validation of your new data science skill set, and unlimited access to edX’s Career Engagement Network, offering you exclusive resources and events to support your professional journey and drive your career forward.
Overview
Obtain significant insights from data to facilitate informed decision-making.
On completion of this course, you’ll walk away with: The ability to apply data science and analysis techniques to inform decision-making. The tools to build and modify robust models in order to help solve business problems. A practical grounding in the widely used Jupyter Notebook. The ability to fit data to a model using Python in order to gain insight into business problems. A certificate of completion from UCT as validation of your new data science skill set, and unlimited access to edX’s Career Engagement Network, offering you exclusive resources and events to support your professional journey and drive your career forward.
On completion of this course, you’ll walk away with: The ability to apply data science and analysis techniques to inform decision-making. The tools to build and modify robust models in order to help solve business problems. A practical grounding in the widely used Jupyter Notebook. The ability to fit data to a model using Python in order to gain insight into business problems. A certificate of completion from UCT as validation of your new data science skill set, and unlimited access to edX’s Career Engagement Network, offering you exclusive resources and events to support your professional journey and drive your career forward.
Syllabus
- Orientation module: Welcome to your Online Campus
- Module 1: Data science and statistical learning
- Module 2: Tree-based methods
- Module 3: Managing the complexity of tree-based methods
- Module 4: Neural networks
- Module 5: Managing the complexity of neural networks
- Module 6: K-means clustering
- Module 7: Hierarchical clustering
- Module 8: Data science in the real world
Taught by
Grant Oosterwyk and Etienne Pienaar