Courses

Advanced Methods for Data Analysis – Summer 2020

This course on Time Series Analysis, Machine Learning and Natural Language Processing will explain how to build systems that learn and adapt using real-world applications. Some of the topics to be covered include time series analysis, machine learning, python data analysis, natural language processing models and recurrent models. The course will be project-oriented, with emphasis placed on writing software implementations of learning algorithms applied to real-world problems, in particular, churn modeling, natural language processing, sentiment detection, among others.

https://github.com/albahnsen/PracticalMachineLearningClass

Practical Machine Learning – Spring 2019

This course on Machine Learning will explain how to build systems that learn and adapt using real-world applications. Some of the topics to be covered include machine learning, python data analysis, deep learning frameworks, natural language processing models and recurrent models. The course will be project-oriented, with emphasis placed on writing software implementations of learning algorithms applied to real-world problems, in particular, image analysis, image captioning, natural language processing, sentiment detection, among others.

https://github.com/albahnsen/PracticalMachineLearningClass

Applied Deep Learning – Summer 2018

This course on Deep Learning will explain how to build systems that learn and adapt using real-world applications. Some of the topics to be covered include deep learning frameworks, convolutional neural networks, generative models nadrecurrent models. The course will be project-oriented, with emphasis placed on writing software implementations of learning algorithms applied to real-world problems, in particular, image analysis, image captioning, natural language pocessing, sentiment detection, among others.

https://github.com/albahnsen/AppliedDeepLearningClass