At the end of this BOOST program, you will be able to:

• Describe a dataset through principal component analysis.
• Select the appropriate classification algorithm.
• Perform a classification with the k-means algorithm.
• Perform a hierarchical classification.

Prerequisites

To enroll in this program, you need to meet the following conditions:

• Language level: a good level of English (for non-native speakers, a CEFR level of B2, an IELTS band score of 6.5, or a TOEFL score of 80 is recommended).
• Equipment: access to a computer (PC or Mac), equipped with a microphone, a webcam and a good internet connection.
• Education level: a high school diploma, GCSE or equivalent.
• Technical prerequisites: fundamentals of probability, statistics, and linear algebra (i.e. matrices multiplication).

Recommended Skills

To ensure success in your BOOST program, we recommend having already mastered the following skills:

• Clean a dataset.
• Describe a dataset using a univariate analysis.
• Describe a dataset using a bivariate analysis.

If you need to get these skills, they can be acquired by taking the BOOST program Exploratory Data Analysis with Python.