Applied Data Science & Machine Learning

This workshop offers a comprehensive, hands-on introduction to the core principles of data science and machine learning, focusing on how raw data can be transformed into meaningful insights and predictive models. Participants begin by understanding how data is collected, structured, and prepared, learning essential techniques in data cleaning, visualization, and exploratory analysis to uncover patterns and relationships.

The program then moves into foundational statistical concepts, including probability, distributions, and hypothesis testing, which form the basis for building reliable models. Participants explore key machine learning techniques such as regression, classification, clustering, and an introduction to neural networks, gaining insight into how these models function and where they are most effectively applied.

Through guided coding exercises and real-world datasets, participants develop practical skills in implementing models, evaluating their performance, and refining them for improved accuracy. The workshop also emphasizes critical thinking around model limitations, including overfitting, bias in data, and the importance…