Generative AI for Business Leaders
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How Google does Machine Learning
دوراتنا
Tools for Data Science
In order to be successful in Data Science, you need to be skilled with using tools that Data Science professionals employ as part of their jobs. This course teaches you about the popular tools in Data Science and how to use them. You will become familiar with the Data Scientist’s tool kit which includes: Libraries & Packages, Data Sets, Machine Learning Models, Kernels, as well as the various Open source, commercial, Big Data and Cloud-based tools. Work with Jupyter Notebooks, JupyterLab, RStudio IDE, Git, GitHub, and Watson Studio.
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Course by
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Self Paced
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18 ساعات
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الإنجليزية
Mediation Analysis with R
In this project, you will learn to perform mediation analysis in RStudio. The project explains the theoretical concepts of mediation and illustrates the process with sample stress detection data. It covers the distinction between mediation and moderation process, explains the selection criteria for a suitable mediator. The project describes the mediation process with statistical models, diagnostic measures and conceptual diagram.
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Course by
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Self Paced
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2 ساعات
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الإنجليزية
RStudio for Six Sigma - Basic Descriptive Statistics
Welcome to RStudio for Six Sigma - Basic Description Statistics. This is a project-based course which should take approximately 2 hours to finish. Before diving into the project, please take a look at the course objectives and structure. By the end of this project, you will learn to perform Basic Descriptive Analysis (Six Sigma) tasks hands-on using RStudio. Both R language and RStudio tools are Open Source and can be used for most Six Sigma analysis tasks without needing commercial software.
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Course by
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Self Paced
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2 ساعات
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الإنجليزية
Financial Risk Management with R
This course teaches you how to calculate the return of a portfolio of securities as well as quantify the market risk of that portfolio, an important skill for financial market analysts in banks, hedge funds, insurance companies, and other financial services and investment firms. Using the R programming language with Microsoft Open R and RStudio, you will use the two main tools for calculating the market risk of stock portfolios: Value-at-Risk (VaR) and Expected Shortfall (ES). You will need a beginner-level understanding of R programming to complete the assignments of this course.
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Course by
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Self Paced
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15 ساعات
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الإنجليزية
RStudio for Six Sigma - Hypothesis Testing
Welcome to RStudio for Six Sigma - Hypothesis Testing. This is a project-based course which should take approximately 2 hours to finish.
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Course by
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Self Paced
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3 ساعات
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الإنجليزية
Reproducible Templates for Analysis and Dissemination
This course will assist you with recreating work that a previous coworker completed, revisiting a project you abandoned some time ago, or simply reproducing a document with a consistent format and workflow. Incomplete information about how the work was done, where the files are, and which is the most recent version can give rise to many complications. This course focuses on the proper documentation creation process, allowing you and your colleagues to easily reproduce the components of your workflow.
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Course by
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Self Paced
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20 ساعات
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الإنجليزية
Fundamentals of Data Analytics in the Public Sector with R
Gain a foundational understanding of key terms and concepts in public administration and public policy while learning foundational programming techniques using the R programming language. You will learn how to execute functions to load, select, filter, mutate, and summarize data frames using the tidyverse libraries with an emphasis on the dplyr package.
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Course by
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Self Paced
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15 ساعات
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الإنجليزية
RStudio for Six Sigma - Control Charts
Welcome to RStudio for Six Sigma - Control Charts. This is a project-based course which should take under 2 hours to finish. Before diving into the project, please take a look at the course objectives and structure. By the end of this project, you will learn to identify data types (Variables, Attribute Type I & II), understand the overview of Statistical Process Control, pick the right Control Chart based on the data type and other criteria, plot and interpret control charts.
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Course by
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Self Paced
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2 ساعات
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الإنجليزية
Data Analysis with R Programming
This course is the seventh course in the Google Data Analytics Certificate. In this course, you’ll learn about the programming language known as R. You’ll find out how to use RStudio, the environment that allows you to work with R, and the software applications and tools that are unique to R, such as R packages. You’ll discover how R lets you clean, organize, analyze, visualize, and report data in new and more powerful ways.
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Course by
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Self Paced
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37 ساعات
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الإنجليزية
The Data Scientist's Toolbox
In this course you will get an introduction to the main tools and ideas in the data scientist's toolbox. The course gives an overview of the data, questions, and tools that data analysts and data scientists work with. There are two components to this course. The first is a conceptual introduction to the ideas behind turning data into actionable knowledge. The second is a practical introduction to the tools that will be used in the program like version control, markdown, git, GitHub, R, and RStudio.
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Course by
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Self Paced
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18 ساعات
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الإنجليزية
Introduction to Probability and Data with R
This course introduces you to sampling and exploring data, as well as basic probability theory and Bayes' rule. You will examine various types of sampling methods, and discuss how such methods can impact the scope of inference. A variety of exploratory data analysis techniques will be covered, including numeric summary statistics and basic data visualization. You will be guided through installing and using R and RStudio (free statistical software), and will use this software for lab exercises and a final project.
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Course by
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Self Paced
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14 ساعات
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الإنجليزية
Linear Regression and Modeling
This course introduces simple and multiple linear regression models. These models allow you to assess the relationship between variables in a data set and a continuous response variable. Is there a relationship between the physical attractiveness of a professor and their student evaluation scores? Can we predict the test score for a child based on certain characteristics of his or her mother?
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Course by
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Self Paced
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10 ساعات
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الإنجليزية
Introduction to Business Analytics with R
Nearly every aspect of business is affected by data analytics. For businesses to capitalize on data analytics, they need leaders who understand the business analytic workflow. This course addresses the human skills gap by providing a foundational set of data processing skills that can be applied to many business settings. In this course you will use a data analytic language, R, to efficiently prepare business data for analytic tools such as algorithms and visualizations.
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Course by
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Self Paced
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17 ساعات
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الإنجليزية