Probability Foundations for Data Science

Probability – the ability to predict the likelihood of an event occurring – is crucial knowledge for anyone interested in data science and analysis. Probability has innumerable applications in a wide variety of fields – including comprising of the core of many machine learning and data science algorithms.

From a basic understanding of Probability fundamentals and common terminology, to understanding conditional probability and Bayes Theorem, this course will provide you with all you need to begin making accurate predictions. Finally, you will apply your knowledge by building a Naïve Bayes Classifier that predicts whether or not a flight will arrive on time using a set of real-world data.

Frameworks and tools covered: Python 3.7, Anaconda 5.3, Pandas 0.23, NumPy 1.15

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