Coursera

4.53

In this course you will learn how to quickly and easily get started with Artificial Intelligence using IBM Watson. You will understand how Watson works, become familiar with its use cases and real life client...

4.71

This course explores Excel as a tool for solving business problems. In this course you will learn the basic functions of excel through guided demonstration. Each week you will build on your excel skills and...

4.33

This second course of the AI Product Management Specialization by Duke University's Pratt School of Engineering focuses on the practical aspects of managing machine learning projects. The course walks through the keys steps of a...

4.52

This course provides an introduction to using Python to analyze team performance in sports. Learners will discover a variety of techniques that can be used to represent sports data and how to extract narratives based...

4.59

Describe how to improve data quality and perform exploratory data analysisBuild and train AutoML Models using Vertex AI and BigQuery MLOptimize and evaluate models using loss functions and performance metricsCreate repeatable and scalable training, e...

4.8

The basics of a machine learning systemHow to deploy a machine learning model to a microcontrollerHow to use machine learning to make decisions and predictions in an embedded system

4.88

Understand the process to establish a repeatable process that delivers rigor and repeatabilityArticulate the business value of any data sprint by capturing the KPI's the sprint will deliverUnderstand how to enable the organization's business, develop...

4.8

How to describe data with statistical summaries, and how to explore your data using advanced visualizations. Understand statistical intervals, hypothesis tests and how to calculate sample size. How to fit, evaluate and interpret linear and...

4.49

Gain hands-on, working knowledge of a step-by-step approach to planning, collecting, analyzing, and reporting dataLearn to evaluate and choose appropriate web analytics tools and techniquesUtilize tools to collect data using today’s most important on...

4.62

How to apply a framework for medical data miningEthical use of data in healthcare decisionsHow to make use of data that may be inaccurate in systematic waysWhat makes a good research question and how to...

4.46

Manipulate primitive data types in the R programming language using RStudio or Jupyter Notebooks. Control program flow with conditions and loops, write functions, perform character string and date operations, and generate regular expressions. Constru...

4.73

This course introduces you to one of the main types of modelling families of supervised Machine Learning: Regression. You will learn how to train regression models to predict continuous outcomes and how to use error...

4.8

Accounting has always been about analytical thinking. From the earliest days of the profession, Luca Pacioli emphasized the importance of math and order for analyzing business transactions. The skillset that accountants have needed to perform...

4.67

In this course, you learn more about SAS Visual Analytics and the SAS Viya platform, how to access and investigate data in SAS Visual Analytics, and how to prepare data for analysis using SAS Data...

4.28

This course is designed to provide you with an understanding of the role of data and technology in human capital management. Every topic in the course will be covered in the most practical way so...

4.83

In this course, you will: a) Learn neural style transfer using transfer learning: extract the content of an image (eg. swan), and the style of a painting (eg. cubist or impressionist), and combine the content...

4.75

Distinguish operational from analytic databases, and understand how these are applied in big dataUnderstand how database and table design provides structures for working with dataAppreciate how differences in volume and variety of data affects your...

4.61

Describe how machine learning is different than descriptive statisticsCreate and evaluate data clustersExplain different approaches for creating predictive modelsBuild features that meet analysis needs

4.58

Store and manage machine learning features using a feature storeDebug, profile, tune and evaluate models while tracking data lineage and model artifacts

4.64

Want to scale your data analysis efforts without managing database hardware? Learn the best practices for querying and getting insights from your data warehouse with this interactive collection of BigQuery Google Cloud Labs Series. BigQuery...