obar1/0to100.gcloud

https://github.com/obar1/0to100 on https://www.cloudskillsboost.google/

map README.md, 219

sorted: False

legend:

footprints	completed
👣	💚

extra

quest	lab	template	game	course
🌀	💾	🐳	🐍	📌

1. BigQuery Architecture and Resource Provisioning here 💚📌

2. BigQuery Fundamentals for Redshift Professionals.BigQuery Data Definition Model here 💚📌

3. BigQuery Fundamentals for Redshift Professionals.BigQuery and Google Cloud IAM here 💚📌

4. Course Resources here 👣📌

5. PDE Prep: BigQuery Essentials here 💚💾

6. Introduction here 💚📌

7. PDE Prep: Cloud Dataproc Cluster Operations and Maintenance here 💚💾

8. Understanding the Professional Data Engineer Certification here 💚📌

9. Designing and building here 💚📌

10. Building data processing systems here 💚📌

11. Analyzing and modeling here 💚📌

12. Designing for Security and Compliance here 💚📌

13. Resources and next steps here 💚📌

14. Building Batch Data Pipelines on Google Cloud here 💚📌

15. MapReduce in Beam (Python) 2.5 here 💚💾

16. A Simple Dataflow Pipeline (Python) 2.5 here 💚💾

17. Running Apache Spark jobs on Cloud Dataproc here 💚💾

18. Serverless Data Analysis with Dataflow: Side Inputs (Python) here 💚💾

19. Building and Executing a Pipeline Graph with Data Fusion 2.5 here 💚💾

20. An Introduction to Cloud Composer 2.5 here 💚💾

21. Introduction here 💚📌

22. Introduction to Building Batch Data Pipelines here 💚📌

23. [Building Batch Data Pipelines on Google Cloud] Executing Spark on Dataproc here 💚📌

24. Serverless Data Processing with Dataflow here 💚📌

25. Course Introduction here 💚📌

26. Module introduction here 💚📌

27. [Building Batch Data Pipelines on Google Cloud].Course Summary here 💚📌

28. Data Warehouse Solutions on Google Cloud here 💚📌

29. Overview here 💚💾

30. Course Resources here 💚📌

31. Exploring and Creating an Ecommerce Analytics Pipeline with Cloud Dataprep v1.5 here 💚💾

32. Building Transformations and Preparing Data with Wrangler in Cloud Data Fusion here 💚💾

33. Course series introduction here 💚📌

34. Analytics challenges faced by data analysts here 💚📌

35. Data analyst tasks and challenges and Google Cloud data tools here 💚📌

36. Introduction to the Google Analytics ecommerce dataset here 💚📌

37. IRS public dataset overview here 💚📌

38. BigQuery jobs here 💚📌

39. 5 principles of dataset integrity here 💚📌

40. Course summary here 💚📌

41. Course Resources here 💚📌

42. Creating Permanent Tables and Access-Controlled Views in BigQuery v1.5 here 💚💾

43. Ingesting New Datasets into BigQuery v1.5 here 💚💾

44. Creating Date-Partitioned Tables in BigQuery v1.5 here 💚💾

45. Troubleshooting and Solving Data Join Pitfalls v1.5 here 💚💾

46. Data to Insights: Unioning and Joining Datasets v1.1 here 💚💾

47. Explore and Create Reports with Looker Studio v1.5 here 💚💾

48. Creating permanent tables here 💚📌

49. Course Introduction here 💚📌

50. Ingesting new data into BigQuery here 💚📌

51. Introducing JOINs and UNIONs here 💚📌

52. Overview of data visualization principles here 💚📌

53. Course summary here 💚📌

54. Modernizing Data Lakes and Data Warehouses with Google Cloud here 💚📌

55. Using BigQuery to do Analysis here 💚💾

56. Loading Taxi Data into Google Cloud SQL 2.5 here 💚💾

57. Loading data into BigQuery here 💚💾

58. Working with JSON and Array data in BigQuery 2.5 here 💚💾

59. Modernizing Data Lakes and Data Warehouses with Google Cloud here 💚📌

60. Module introduction here 💚📌

61. Module Introduction here 💚📌

62. Exploring a BigQuery Public Dataset here 💚💾

63. Course Summary here 💚📌

64. Module Introduction here 💚📌

65. Creating a Streaming Data Pipeline for a Real-Time Dashboard with Dataflow here 💚💾

66. Predicting Visitor Purchases with a Classification Model with BigQuery ML here 💚💾

67. Vertex AI: Predicting Loan Risk with AutoML here 💚💾

68. Meet the author here 💚📌

69. Introduction here 💚📌

70. Introduction here 💚📌

71. Introduction here 💚📌

72. Introduction here 💚📌

73. BigQuery Architecture and Resource Provisioning here 💚📌

74. Course summary here 💚📌

75. [BigQuery Fundamentals for Redshift Professionals].BigQuery Data Definition Model here 💚📌

76. BigQuery and Google Cloud IAM here 💚📌

77. Introduction here 💚📌

78. BigQuery Fundamentals for Redshift Professionals.Course Resources here 👣📌

79. BigQuery Fundamentals for Redshift Professionals.Monitoring BigQuery Workloads here 💚💾

80. Securing and Sharing BigQuery Datasets and Tables here 💚💾

81. [Data Lake Modernization on Google Cloud: Cloud Composer].Cloud Composer here 👣📌

82. Demo: Cloud Composer Code Walkthrough here 👣📌

83. Exploring and Preparing your Data with BigQuery here 💚🐳

84. BigQuery Fundamentals for Redshift Professionals here 👣🐳

85. Creating New BigQuery Datasets and Visualizing Insights here 💚🐳

86. Google Cloud Big Data and Machine Learning Fundamentals here 💚🐳

87. Cloud Composer here 👣🐳

88. Serverless Data Processing with Dataflow: Foundations here 👣🐳

89. Manage Data Models in Looker here 💚🐳

90. Modernizing Data Lakes and Data Warehouses with Google Cloud here 💚🐳

91. Building Batch Data Pipelines on Google Cloud here 💚🐳

92. Preparing for the Google Cloud Professional Data Engineer Exam here 💚🐳

93. Reinforcement Learning: Qwik Start here 👣📌

94. IAM Custom Roles here 👣📌

95. <https§§§www.cloudskillsboost.google§course_templates§78> here 👣🐳

96. Create and Manage Cloud Resources: Challenge Lab here 👣📌

97. Share Data Using Google Data Cloud here 👣🐳

98. Predict Soccer Match Outcomes with BigQuery ML here 💚🐳

99. Deploy to Kubernetes in Google Cloud: Challenge Lab here 👣📌

100. Build and Execute MySQL, PostgreSQL, and SQLServer to Data Catalog Connectors here 👣📌

101. Eventarc for Cloud Run here 👣📌

102. Entity and Sentiment Analysis with the Natural Language API here 👣📌

103. Cloud Functions: Qwik Start - Console here 👣📌

104. Looker Developer - Qwik Start here 👣📌

105. Vertex AI: Qwik Start here 👣📌

106. Google Cloud Storage - Bucket Lock here 👣📌

107. A Tour of Google Cloud Hands-on Labs here 👣📌

108. ETL Processing on Google Cloud Using Dataflow and BigQuery here 👣📌

109. Cloud Composer: Copying BigQuery Tables Across Different Locations here 👣📌

110. Creating a Virtual Machine here 👣📌

111. <https§§§www.cloudskillsboost.google§focuses§3642§parent=catalog> here 👣📌

112. Troubleshooting and Solving Data Join Pitfalls here 👣📌

113. APIs Explorer: Cloud Storage here 👣📌

114. Creating a Data Warehouse Through Joins and Unions here 👣📌

115. Creating Date-Partitioned Tables in BigQuery here 👣📌

116. Creating a Data Transformation Pipeline with Cloud Dataprep here 👣📌

117. Using BigQuery Omni with AWS here 💚📌

118. Orchestrating the Cloud with Kubernetes here 👣📌

119. Getting Started with Cloud Shell and gcloud here 👣📌

120. Cloud Natural Language API: Qwik Start here 👣📌

121. Cloud Storage: Qwik Start - CLI/SDK here 👣📌

122. <https§§§www.cloudskillsboost.google§focuses§609§parent=catalog> here 👣📌

123. Dataprep: Qwik Start here 👣📌

124. BigQuery: Qwik Start - Command Line here 👣📌

125. Get Started with Cloud Storage: Challenge Lab here 👣📌

126. Cloud Functions: Qwik Start - Command Line here 👣📌

127. Google Cloud Pub/Sub: Qwik Start - Command Line here 👣📌

128. Kubernetes Engine: Qwik Start here 👣📌

129. Get Started with Eventarc: Challenge Lab here 👣📌

130. Level 1: Data with Google Cloud here 💚🐍

131. Looker Data Explorer - Qwik Start here 💚💾

132. Looker Studio: Qwik Start here 💚💾

133. Get Started with Looker: Challenge Lab here 💚💾

134. Dataflow: Qwik Start - Python here 💚💾

135. Create a Streaming Data Lake on Cloud Storage: Challenge Lab here 💚💾

136. Stream Processing with Cloud Pub/Sub and Dataflow: Qwik Start here 💚💾

137. Dataplex: Qwik Start - Command Line here 💚💾

138. Dataplex: Qwik Start - Console here 💚💾

139. Tagging Dataplex Assets here 💚💾

140. Analyze Speech & Language with Google APIs: Challenge Lab here 💚💾

141. Get Started with Dataplex: Challenge Lab here 💚💾

142. Level 2: Cloud security here 💚🐍

143. Google Cloud Storage - Bucket Lock here 💚💾

144. Cloud Functions 2nd Gen: Qwik Start here 💚💾

145. Cloud IAM: Qwik Starthere 💚💾

146. Eventarc for Cloud Run here 💚💾

147. Create a Secure Data Lake on Cloud Storage: Challenge Lab here 💚💾

148. Cloud Monitoring: Qwik Start here 💚💾

149. Monitoring and Logging for Cloud Functions here 💚💾

150. Monitor a Compute Engine Virtual Machine: Qwik Start here 💚💾

151. Monitoring in Google Cloud: Challenge Lab here 💚💾

152. Cloud Functions: 3 Ways: Challenge Lab here 💚💾

153. Responding to Cloud Logging Messages with Cloud Functions here 💚💾

154. APIs Explorer: Qwik Start here 💚💾

155. Getting Started with BigQuery Machine Learning here 👣💾

156. Deploying a Python Flask Web Application to App Engine Flexible here 💚💾

157. Hosting a Web App on Google Cloud Using Compute Engine here 💚💾

158. Extract, Analyze, and Translate Text from Images with the Cloud ML APIs here 💚💾

159. Use Go Code to Work with Google Cloud Data Sources here 💚💾

160. Level 3: GenAI here 💚🐍

161. Generative AI with Vertex AI: Getting Started here 💚💾

162. Generative AI with Vertex AI: Prompt Design here 💚💾

163. Get Started with Generative AI Studio here 💚💾

164. Analyze Images with the Cloud Vision API: Challenge Lab here 💚💾

165. Level 1: Sports Data here 💚🐍

166. Troubleshooting Data Models in Looker here 💚💾

167. Modularizing LookML Code with Extends here 💚💾

168. BigQuery Soccer Data Analytical Insight here 💚💾

169. Employing Best Practices for Improving the Usability of LookML Projects here 💚💾

170. Caching and Datagroups with LookML here 💚💾

171. How to Build a BI Dashboard Using Google Looker Studio and BigQuery here 💚💾

172. Analytics as a Service for Data Sharing Partners here 💚💾

173. Level 2: BigQuery and BigLake Data Skills here 💚🐍

174. Creating and Populating a Bigtable Instance here 💚💾

175. Tag and Discover BigLake Data: Challenge Lab here 💚💾

176. Data Catalog: Qwik Start here 💚💾

177. Migrating On-premises MySQL Using a Continuous Database Migration Service Job here 💚💾

178. Troubleshooting Common SQL Errors with BigQuery here 👣💾

179. Building Demand Forecasting with BigQuery ML here 💚💾

180. Optical Character Recognition (OCR) with Document AI (Python) here 💚💾

181. Form Parsing with Document AI (Python) here 💚💾

182. <https§§§www.cloudskillsboost.google§games§4793§labs§31288> here 💚💾

183. Google Cloud Pub/Sub: Qwik Start - Console here 👣💾

184. Using Specialized Processors with Document AI (Python) here 💚💾

185. Data Engineer Learning Path here 👣📌

186. Create and Manage Cloud Resources here 💚🌀

187. obar1 here 👣📌

188. Deploy to Kubernetes in Google Cloud here 💚🌀

189. Data Engineering here 💚🌀

190. Get Started with Cloud Storage here 💚🌀

191. App Engine: 3 Ways here 💚🌀

192. Get Started with Looker here 💚🌀

193. Create a Streaming Data Lake on Cloud Storage here 💚🌀

194. Cloud Functions: 3 Ways here 💚🌀

195. Create a Secure Data Lake on Cloud Storage here 💚🌀

196. Get Started with Dataplex here 💚🌀

197. Monitoring in Google Cloud here 💚🌀

198. Analyze Speech and Language with Google APIs here 💚🌀

199. Get Started with Eventarc here 💚🌀

200. Baseline: Data, ML, AI here 💚🌀

201. BigQuery for Data Warehousing here 💚🌀

202. Develop an app with Duet AI here 💚💾

203. Exploring IAM here 👣💾

204. Cloud Storage here 👣💾

205. Generative AI: Hamburg Tour here 💚💾

206. Deploy Kubernetes Load Balancer Service with Terraform here 💚💾

207. HTTPS Content-Based Load Balancer with Terraform here 💚💾

208. Modular Load Balancing with Terraform - Regional Load Balancer here 💚💾

209. Cloud SQL with Terraform here 💚💾

210. Managing Cloud Infrastructure with Terraform here 💚🐳

211. Optimizing your BigQuery Queries for Performance 2.5 here 💚💾

212. Data Engineer Learning Path here 👣📌

213. Preparing for your Professional Data Engineer Journey here 👣🐳

214. Introduction to Docker here 💚💾

215. Google Kubernetes Engine: Qwik Start here 💚💾

216. <https§§§www.cloudskillsboost.google§course_templates§744§labs§408291> here 💚💾

217. Managing Deployments Using Kubernetes Engine here 👣💾

218. Kubernetes in Google Cloud here 💚🐳

219. Continuous Delivery with Jenkins in Kubernetes Engine here 💚💾