Statistical Inference in Big Data | University of Toronto

Comprehensive coverage of statistical inference techniques for big data analysis, lectures by renowned experts, and hands-on demonstrations for practical learning.

Introduction

This course provides an introduction to statistical inference in the context of big data. It covers topics such as optimization, machine learning, unsupervised learning, deep learning, ensembles, kernel machines, visualization, and statistical inference.

Highlights

• Comprehensive coverage of statistical inference techniques for big data analysis
• Lectures by renowned experts in the field, including Nancy Reid and Mu Zhu
• Hands-on demonstrations and code examples for practical learning
• Exploration of cutting-edge topics like deep learning and data visualization

Recommendation

This course is recommended for students and professionals interested in developing a strong foundation in statistical inference and its applications in the era of big data. It is suitable for those with a background in statistics, machine learning, or data science who want to expand their knowledge and skills in this rapidly evolving field.