Skip to content

Commit 2d3fec3

Browse files
author
gitName
committed
Fix merge conflict
2 parents ba686cb + 3345a0a commit 2d3fec3

File tree

1,350 files changed

+6167
-26333
lines changed

Some content is hidden

Large Commits have some content hidden by default. Use the searchbox below for content that may be hidden.

1,350 files changed

+6167
-26333
lines changed

.openpublishing.redirection.json

Lines changed: 918 additions & 70 deletions
Large diffs are not rendered by default.

learn-pr/achievements.yml

Lines changed: 75 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -5,6 +5,21 @@ achievements:
55
# title: Module template
66
# summary: Module template badge.
77
# iconUrl: http://via.placeholder.com/120x120
8+
- uid: learn.azure.characterize-dataset-azure-data-explorer.badge
9+
type: badge
10+
title: Characterize an unfamiliar dataset with Azure Data Explorer
11+
summary: Learn how to characterize an unfamiliar dataset using Azure Data Explorer.
12+
iconUrl: /training/achievements/azure-data-explore-web.svg
13+
- uid: learn.visualize-data-workbooks.badge
14+
type: badge
15+
title: Visualize data combined from multiple data sources by using Azure Monitor Workbooks
16+
summary: Use Azure Workbooks to query data from multiple data sources and use visualizations such as graphs, charts, and grids to build visual reports for data analysis and reporting.
17+
iconUrl: /training/achievements/generic-badge.svg
18+
- uid: learn.azure-security.configure-security-policies-to-manage-data.badge
19+
type: badge
20+
title: Configure security policies to manage data
21+
summary: Learn how to configure security policies to manage data.
22+
iconUrl: /training/achievements/configure-security-policies-to-manage-data.svg
823
- uid: learn.sql-server-2022-performance-enhancements.badge
924
type: badge
1025
title: Understand the built-in query intelligence enhancements of SQL Server 2022
@@ -5805,3 +5820,63 @@ achievements:
58055820
title: Get started with React
58065821
summary: React.js is the most popular front-end JavaScript framework. Developers use JSX, a combination of HTML and JavaScript, to create views in a natural way. Developers can also create components for blocks that can be reused across their applications. This module introduces React and the core skills developers need to use this powerful framework.
58075822
iconUrl: /training/achievements/react/react-get-started.svg
5823+
- uid: learn.sports-machine-learning.use-mixed-reality-toolkit.badge
5824+
type: badge
5825+
title: Create a mixed reality basketball player lineup with the Mixed Reality Toolkit
5826+
summary: "Use C#, Visual Studio, Unity, and the Mixed Reality Toolkit to create an interactive virtual reality experience compatible with the HoloLens. Inspired by *Space Jam: A New Legacy*, you create an experience for coaches and fans to learn more about the Tune Squad."
5827+
iconUrl: /training/achievements/student-evangelism/create-mixed-reality-basketball-lineup-mixed-reality-toolkit.svg
5828+
- uid: learn.student-evangelism.optimize-basketball-player-rest-breaks.badge
5829+
type: badge
5830+
title: Create a web app that uses data to make decisions on the basketball court
5831+
summary: "Use JavaScript, Azure, GitHub, and Visual Studio Code to write a web app that helps the Tune Squad coach make data-based decisions on the basketball court, inspired by SPACE JAM: A NEW LEGACY."
5832+
iconUrl: /training/achievements/student-evangelism/optimize-basketball-player-rest-breaks.svg
5833+
- uid: learn.student-evangelism.predict-basketball-player-efficiency-ratings.badge
5834+
type: badge
5835+
title: Predict basketball player efficiency ratings by using machine learning and Visual Studio Code
5836+
summary: "By using anonymized data from real and animated basketball players in the upcoming film *Space Jam: A New Legacy*, create a machine learning model to cleanse data to be used during games. Also explore bimodal data distributions by using Python in Visual Studio Code."
5837+
iconUrl: /training/achievements/student-evangelism/predict-basketball-player-efficiency-ratings.svg
5838+
- uid: learn.optimize-basketball-games-with-machine-learning.trophy
5839+
type: trophy
5840+
title: "Use basketball stats to optimize game play with Visual Studio Code, inspired by SPACE JAM: A NEW LEGACY"
5841+
summary: "Inspired by the new film _Space Jam: A New Legacy_, this learning path shows basketball fans how an understanding of data science and coding can support their passions, create opportunities, and even open doors to possible careers. Develop skills in Visual Studio Code, Azure, GitHub, JavaScript, and Python, to gain insights into how individual moments throughout a player's history can lead to a critical game decision in the finals."
5842+
iconUrl: /training/achievements/student-evangelism/optimize-basketball-games-with-machine-learning.svg
5843+
- uid: learn.sports-machine-learning.mixed-reality-for-sports-fans.badge
5844+
type: badge
5845+
title: Prepare to bring the basketball court into a Mixed Reality space
5846+
summary: "Discover the fundamentals of Mixed Reality and prepare the resources you need to create an interactive experience for basketball fans and coaches inspired by *Space Jam: A New Legacy*."
5847+
iconUrl: /training/achievements/mixed-reality-for-sports-fans.svg
5848+
- uid: learn.machine-learning.predictive-maintenance-model-builder.badge
5849+
type: badge
5850+
title: Train a machine learning model for predictive maintenance by using ML.NET Model Builder
5851+
summary: Train a machine learning model in Visual Studio with ML.NET by using Model Builder, which uses sensor data to detect whether a manufacturing device is broken.
5852+
iconUrl: /training/achievements/machine-learning/predictive-maintenance-model-builder.svg
5853+
- uid: learn.machine-learning.introduction-clustering-models.badge
5854+
type: badge
5855+
title: Introduction to clustering models by using R and tidymodels
5856+
summary: Get an introduction to clustering models. Clustering is the process of grouping objects with similar objects.
5857+
iconUrl: /training/achievements/machine-learning/introduction-clustering-models.svg
5858+
- uid: learn.machine-learning.introduction-regression-models.badge
5859+
type: badge
5860+
title: Introduction to regression models by using R and tidymodels
5861+
summary: Get an introduction to regression models. In machine learning, the goal of regression is to create a model that can predict a numeric, quantifiable value.
5862+
iconUrl: /training/achievements/machine-learning/introduction-regression-models.svg
5863+
- uid: learn.machine-learning.introduction-classification-models.badge
5864+
type: badge
5865+
title: Introduction to classification models by using R and tidymodels
5866+
summary: Classification is a form of machine learning in which you train a classification model to predict which category an item belongs to. In this module, you learn how to use the R programming language and tidymodels framework to train classification models.
5867+
iconUrl: /training/achievements/machine-learning/introduction-classification-models.svg
5868+
- uid: learn.machine-learning.machine-learning-with-r.trophy
5869+
type: trophy
5870+
title: Create machine learning models with R and tidymodels
5871+
summary: Learn how to explore and analyze data by using R. Get an introduction to regression models, classification models, and clustering models by using tidymodels and R.
5872+
iconUrl: /training/achievements/machine-learning/machine-learning-with-r.svg
5873+
- uid: learn.machine-learning.explore-analyze-data-r.badge
5874+
type: badge
5875+
title: Explore and analyze data with R
5876+
summary: In this module, you explore, analyze, and visualize data by using the R programming language.
5877+
iconUrl: /training/achievements/machine-learning/explore-analyze-data-r.svg
5878+
- uid: learn.advocates.cv-classify-bird-species.badge
5879+
type: badge
5880+
title: Classify endangered bird species with Custom Vision
5881+
summary: As an ornithologist, you study the behavior, physiology, and conservation of birds and bird habitat. Your work often involves surveying, recording, and reporting on bird activity. You want to build a machine learning model that will identify a bird in an image by species, to help with gathering data. In this module, you use Azure AI Custom Vision to create a model to identify species of birds!
5882+
iconUrl: /training/achievements/advocates/cv-classify-bird-species.svg
468 KB
Loading

0 commit comments

Comments
 (0)