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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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 [...]
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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 [...]
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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.
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Introduction to Predictive Analytics using Python (edX)

Learn the predictive modelling process in Python. Create the insights needed to compete in business. This course provides you with the skills to build a predictive model from the ground up, using Python. You will learn the full lifecycle of building the model. First, you'll understand the data discovery [...]
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