


Getting to grips with data visualization, exploratory data analysis, then harnessing the power of data and its role in corporate decision-making.
The main concepts covered in this module are: data-driven decision making, data cleaning, data coding, and data visualization using Python.
Learn about and use the fundamental techniques of machine learning, and know how to gauge the impact of such tools in a business.
The main concepts covered in this module are: time series, clustering (data partitioning), and regression methods using scikit-learn.
Explore the main challenges of machine learning and the ethical and legal considerations of using data in the business world.
The main concepts covered in this module are: model evaluation, performance analysis, overfitting vs. underfitting, data augmentation, ensemble methods, and the ethical, legal, and social issues surrounding data use.
