Coursera

4.62

Explain different types of data analyses – descriptive, diagnostic, predictive, prescriptive Understand how to perform descriptive data analytics in the cloud with typical data sets How to build simple visualizations in AWS QuickSight to do...

4.76

In this course, you will get hands-on instruction of advanced Excel 2013 functions. You’ll learn to use PowerPivot to build databases and data models. We’ll show you how to perform different types of scenario and...

4.89

Welcome to this course on Getting started with TensorFlow 2! In this course you will learn a complete end-to-end workflow for developing deep learning models with Tensorflow, from building, training, evaluating and predicting with models...

4.46

Principles and practical considerations for integrating AI into clinical workflowsBest practices of AI applications to promote fair and equitable healthcare solutionsChallenges of regulation of AI applications and which components of a model can be r...

4.59

In this course, you will learn best practices for how to use data analytics to make any company more competitive and more profitable. You will be able to recognize the most critical business metrics and...

4.49

In the first course of this specialization, we will recap what was covered in the Machine Learning with TensorFlow on Google Cloud Platform Specialization (https: //www. coursera. org/specializations/machine-learning-tensorflow-gcp). One of the best...

4.69

Looking to start a career in Deep Learning? Look no further. This course will introduce you to the field of deep learning and help you answer many questions that people are asking nowadays, like what...

4.43

Use the Keras Sequential and Functional APIs for simple and advanced model creation Design and build a TensorFlow 2. x input data pipelineUse the tf. data library to manipulate data and large datasetsTrain, deploy, and...

4.67

Estimate treatment effects using data from randomized control trialsExplore methods to interpret diagnostic and prognostic modelsApply natural language processing to extract information from unstructured medical data

4.48

Learn the general concepts of data mining along with basic methodologies and applications. Then dive into one subfield in data mining: pattern discovery. Learn in-depth concepts, methods, and applications of pattern discovery in data mining....

4.47

>>> By enrolling in this course you agree to the End User License Agreement as set out in the FAQ. Once enrolled you can access the license in the Resources area

4.43

Interprofessional Healthcare Informatics is a graduate-level, hands-on interactive exploration of real informatics tools and techniques offered by the University of Minnesota and the University of Minnesota's National Center for Interprofessional Pra...

4.66

One of the skills that characterizes great business data analysts is the ability to communicate practical implications of quantitative analyses to any kind of audience member. Even the most sophisticated statistical analyses are not useful...

4.8

In this course, you will learn how to solve problems with large, high-dimensional, and potentially infinite state spaces. You will see that estimating value functions can be cast as a supervised learning problem-function approximation-allowing you...

4.76

Learners will understand how signals, images, and data are represented and manipulated in MATLAB Learners will gain experience with methods for data visualization, including high dimensional datasets in MATLABLearners will apply machine learning meth...

5

Develop a toolkit for exploring and communicating complex data using visualizationProduce basic data visualizations using a chosen datasetCompare methods for visualizing data and understand how these methods may guide users towards different conclusi...

4.86

This course introduces you to one of the main types of modeling families of supervised Machine Learning: Classification. You will learn how to train predictive models to classify categorical outcomes and how to use error...

4.56

Ingest, transform, and query data to extract valuable insights. Leverage existing SQL skills to start working with Apache Spark.

4.75

By taking this course, you will be able explain what data science is and identify the key disciplines involved. ​You will be able to use the steps of the data science process to create a...

4.91

Course DescriptionIn this course, you learn about Structured Query Language (SQL) and how it can be used in SAS programs to create reports and query your data. “By the end of this course, a learner...