Anomaly Detection
In this course you will learn how to examine data with the goal of detecting anomalies or abnormal instances.
Courses – Machine Learning
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Deep Learning
This course will introduce you to the essential techniques of text mining as the extension of data mining’s standard predictive methods to unstructured text.
Introduction to NLP and Text Mining
This course will teach you the essential techniques of text mining, understood here as the extension of data mining’s standard predictive methods to unstructured text.
NLP and Deep Learning
This course will teach you the algorithms, techniques and software used in natural language processing (NLP).
Predictive Analytics – Project Capstone
A predictive modeling practicum for the predictive analytices course program.
Predictive Analytics 1 – Machine Learning Tools with Python
This course introduces to the basic concepts in predictive analytics, with a focus on Python, to visualize and explore data that account for most business applications of predictive modeling: classification and prediction.
Predictive Analytics 1 – Machine Learning Tools with R
This course introduces to the basic concepts in predictive analytics, with a focus on R, to visualize and explore data that account for most business applications of predictive modeling: classification and prediction.
Predictive Analytics 2 – Neural Nets and Regression with Python
As a continuation of Predictive Analytics 1, this course introduces to the basic concepts in predictive analytics, with a focus on Python, to visualize and explore predictive modeling.
Predictive Analytics 2 – Neural Nets and Regression with R
As a continuation of Predictive Analytics 1, this course introduces to the basic concepts in predictive analytics, with a focus on R, to visualize and explore predictive modeling.
Predictive Analytics 3 – Dimension Reduction, Clustering, and Association Rules with Python
This course, with a focus on Python, will teach you key unsupervised learning techniques of association rules – principal components analysis, and clustering – and will include an integration of supervised and unsupervised learning techniques.
Predictive Analytics 3 – Dimension Reduction, Clustering, and Association Rules with R
This course, with a focus on R, will teach you key unsupervised learning techniques of association rules – principal components analysis, and clustering – and will include an integration of supervised and unsupervised learning techniques.
The Ethical Practice of Data Science
There is increasing public and corporate concern about bias and other unintended harmful effects resulting from data science models. This course, for both data science