Fix merge conflicts

Author: gitName

.openpublishing.redirection.json

@@ -5,6 +5,16 @@ achievements:
 #  title: Module template
 #  summary: Module template badge.
 #  iconUrl: http://via.placeholder.com/120x120
+- uid: learn.visualize-data-workbooks.badge
+  type: badge
+  title: Visualize data combined from multiple data sources by using Azure Monitor Workbooks
+  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.
+  iconUrl: /training/achievements/generic-badge.svg
+- uid: learn.azure-security.configure-security-policies-to-manage-data.badge
+  type: badge
+  title: Configure security policies to manage data
+  summary: Learn how to configure security policies to manage data. 
+  iconUrl: /training/achievements/configure-security-policies-to-manage-data.svg
 - uid: learn.sql-server-2022-performance-enhancements.badge
   type: badge
   title: Understand the built-in query intelligence enhancements of SQL Server 2022
@@ -5800,3 +5810,58 @@ achievements:
   title: Create a mixed reality basketball player lineup with the Mixed Reality Toolkit
   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."
   iconUrl: /training/achievements/student-evangelism/create-mixed-reality-basketball-lineup-mixed-reality-toolkit.svg
+- uid: learn.student-evangelism.optimize-basketball-player-rest-breaks.badge
+  type: badge
+  title: Create a web app that uses data to make decisions on the basketball court
+  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."
+  iconUrl: /training/achievements/student-evangelism/optimize-basketball-player-rest-breaks.svg
+- uid: learn.student-evangelism.predict-basketball-player-efficiency-ratings.badge
+  type: badge
+  title: Predict basketball player efficiency ratings by using machine learning and Visual Studio Code
+  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."
+  iconUrl: /training/achievements/student-evangelism/predict-basketball-player-efficiency-ratings.svg
+- uid: learn.optimize-basketball-games-with-machine-learning.trophy
+  type: trophy
+  title: "Use basketball stats to optimize game play with Visual Studio Code, inspired by SPACE JAM: A NEW LEGACY"
+  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."
+  iconUrl: /training/achievements/student-evangelism/optimize-basketball-games-with-machine-learning.svg
+- uid: learn.sports-machine-learning.mixed-reality-for-sports-fans.badge
+  type: badge
+  title: Prepare to bring the basketball court into a Mixed Reality space
+  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*."
+  iconUrl: /training/achievements/mixed-reality-for-sports-fans.svg
+- uid: learn.machine-learning.predictive-maintenance-model-builder.badge
+  type: badge
+  title: Train a machine learning model for predictive maintenance by using ML.NET Model Builder
+  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.
+  iconUrl: /training/achievements/machine-learning/predictive-maintenance-model-builder.svg
+- uid: learn.machine-learning.introduction-clustering-models.badge
+  type: badge
+  title: Introduction to clustering models by using R and tidymodels
+  summary: Get an introduction to clustering models. Clustering is the process of grouping objects with similar objects.
+  iconUrl: /training/achievements/machine-learning/introduction-clustering-models.svg
+- uid: learn.machine-learning.introduction-regression-models.badge
+  type: badge
+  title: Introduction to regression models by using R and tidymodels
+  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.
+  iconUrl: /training/achievements/machine-learning/introduction-regression-models.svg
+- uid: learn.machine-learning.introduction-classification-models.badge
+  type: badge
+  title: Introduction to classification models by using R and tidymodels
+  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.
+  iconUrl: /training/achievements/machine-learning/introduction-classification-models.svg
+- uid: learn.machine-learning.machine-learning-with-r.trophy
+  type: trophy
+  title: Create machine learning models with R and tidymodels
+  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.
+  iconUrl: /training/achievements/machine-learning/machine-learning-with-r.svg
+- uid: learn.machine-learning.explore-analyze-data-r.badge
+  type: badge
+  title: Explore and analyze data with R
+  summary: In this module, you explore, analyze, and visualize data by using the R programming language.
+  iconUrl: /training/achievements/machine-learning/explore-analyze-data-r.svg
+- uid: learn.advocates.cv-classify-bird-species.badge
+  type: badge
+  title: Classify endangered bird species with Custom Vision
+  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!
+  iconUrl: /training/achievements/advocates/cv-classify-bird-species.svg