Sofia Varypati

Sofia has more than 5 years of working experience in the field of data and predictive analytics. She has worked in the banking industry for the last 4 years on several projects, such as pricing of products, customer segmentation, risk modelling and financial analytics. Sofia’s academic background includes a BSc/MSc in Applied Mathematics and Physics, as well as an MSc in Operational Research and Computational Optimisation from the University of Edinburgh.

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Predictive Analytics using Machine Learning (edX)

Learn how to build predictive models using machine learning. This course will give you an overview of machine learning-based approaches for predictive modelling, including tree-based techniques, support vector machines, and neural networks using Python.

Statistical Predictive Modelling and Applications (edX)

Learn how to apply statistical modelling techniques to real-world business scenarios using Python. In this course, you will learn three predictive modelling techniques - linear and logistic regression, and naive Bayes - and their applications in real-world scenarios. The first half of the course focuses on linear regression. This [...]

Successfully Evaluating Predictive Modelling (edX)

Gain an in-depth understanding of evaluation and sampling approaches for effective predictive modelling using Python. A predictive exercise is not finished when a model is built. This course will equip you with essential skills for understanding performance evaluation metrics, using Python, to determine whether a model is performing [...]