Azure Mastery: DP-100| AI-900| DP-900| DP-300| AI Chatbot

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EDUCBA Bridging the Gap

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1 - DP100 Microsoft Azure DS Exam

1 - Introduction to Course.mp4

02:11

2 - Exam Requirements.mp4

06:56

3 - Create an Azure Machine Learning Workspace.mp4

07:27

4 - Azure ML Workspace Settings Portal.mp4

05:10

5 - Azure ML Studio Settings.mp4

06:03

6 - Data Stores and Datasets.mp4

10:10

7 - Create Additional Datasets.mp4

09:19

8 - Create an Experiment Compute Instance.mp4

06:35

9 - Manage Multiple Compute Instances.mp4

05:38

10 - Create Compute Targets and Clusters.mp4

06:46

11 - Creating our First ML Pipeline.mp4

09:28

12 - Submitting Pipeline.mp4

08:31

13 - Custom Code in Pipeline.mp4

04:33

14 - Understanding Complicated Pipeline.mp4

10:49

15 - Evaluating Execution Results.mp4

06:13

16 - Errors in Azure ML Designer.mp4

03:30

17 - Various Modules of Azure ML Designer.mp4

10:18

18 - Setup SDK.mp4

08:38

19 - Create ML Workspace using SDK.mp4

08:01

20 - Simple Program in Python.mp4

14:27

21 - Train Model using SDK.mp4

10:43

22 - Submit Experiment using SDK.mp4

05:00

23 - Create a Pipeline by using SDK.mp4

11:03

24 - AutoML Overview.mp4

11:24

25 - AutoML with SDK.mp4

02:47

26 - Understanding what is Hyper drive.mp4

07:51

27 - Register a Trained Model.mp4

04:57

28 - Create Production Compute Targets.mp4

07:43

29 - Deploy AutoML.mp4

11:42

30 - Create an AutoML Endpoint.mp4

03:32

31 - Deploy ML Designer for Real Time.mp4

04:52

32 - Deploy SDK Models.mp4

05:22

33 - Publish a Pipeline for Batch Inference.mp4

03:25

34 - Conclusion.mp4

01:17

2 - AI900 MS Azure AI Fundamentals

35 - Introduction to Course.mp4

05:03

36 - What is Artificial Intelligence.mp4

06:09

37 - Machine Learning Model.mp4

10:23

38 - AI900 Exam Requirements.mp4

05:31

39 - Common AI workloads.mp4

09:45

40 - Guiding principles for Responsible AI.mp4

06:53

41 - Privacy and Security.mp4

05:28

42 - Transparence and Accountability.mp4

05:53

43 - MS Official website for AI Principles.mp4

02:03

44 - Common ML Types.mp4

07:12

45 - Dataset Features and Labels.mp4

04:28

46 - Training and Validation Dataset.mp4

07:55

47 - FPR and AUC.mp4

07:17

48 - Auto ML.mp4

05:50

49 - DemoCreate Azure ML Workspace.mp4

06:49

50 - Use AutoML to Build a noCode Model.mp4

07:26

51 - ML Designer.mp4

05:01

52 - ML Designer to Build a noCode Model.mp4

14:38

53 - Common types of Computer Vision Workloads.mp4

04:45

54 - Computer Vision Services in Microsoft Azure.mp4

08:10

55 - Using Computer Vision Service.mp4

06:10

56 - Using Custom Vision Service.mp4

07:17

57 - NLP Workloads.mp4

07:13

58 - NLP Services.mp4

05:08

59 - Common Types of Conversational AI workloads.mp4

04:50

60 - Conversational AI Services in Azure.mp4

02:50

61 - Conclusion.mp4

00:48

3 - DP900 Azure Data Fundamentals

62 - Introduction to Course.mp4

04:34

63 - Exam Requirements.mp4

04:56

64 - Describe Ways to Represent Data.mp4

11:53

65 - Identify Options For Data Storage.mp4

10:23

66 - Describe Common Data Workloads.mp4

11:41

67 - Responsibilities For Data Workloads.mp4

04:50

68 - Identify Features of Relational Data.mp4

08:48

69 - Describe Normalization.mp4

08:00

70 - Three Normal Forms.mp4

06:36

71 - Demo Sample Database.mp4

13:10

72 - Identify Common Structured Query Language.mp4

06:58

73 - Demo Create A Database View.mp4

05:33

74 - Demo Create A Stored Procedure.mp4

09:24

75 - Demo Create An Index.mp4

11:12

76 - Relational DBs Introduction.mp4

07:02

77 - Azure Relational DB Options.mp4

09:18

78 - Creating Azure SQL Database.mp4

11:10

79 - Arm Templates to Manage SQL Databases.mp4

07:32

80 - SQL Database Security.mp4

04:36

81 - Relational Query Tools.mp4

05:30

82 - Introduction to Non Relational DBs.mp4

08:41

83 - Non Relational Data Types.mp4

07:27

84 - Choose A NoSQL Database.mp4

06:50

85 - Azure Non Relational DB Options.mp4

06:14

86 - Creation Cosmos DB.mp4

06:46

87 - Query Cosmos DB.mp4

08:54

88 - Use Arm Templates to Manage Cosmos DB.mp4

03:09

89 - Cosmos DB Security.mp4

03:23

91 - Modern Data Warehouse.mp4

06:36

92 - Azure Data Factory.mp4

06:43

93 - Data Visualization.mp4

06:33

94 - Power Bi Content Workflow.mp4

02:31

95 - Conclusion.mp4

00:41

4 - DP300 Azure Relational DBA

96 - Introduction to Course.mp4

06:25

97 - Exam Requirements.mp4

05:08

98 - Azure Free Account.mp4

03:47

99 - Azure Relational Databases Covered in Exam.mp4

04:36

100 - SQL Database Options Overview.mp4

08:24

101 - Creating Azure VM and Installing SQL Server.mp4

09:39

102 - Connect Database Through Port 1433.mp4

04:55

103 - Deploying SQL Server from the Azure Marketplace.mp4

04:44

104 - Maintenance Window.mp4

01:32

105 - Install Azure SQL Database.mp4

07:35

106 - Using Sample Database.mp4

01:56

107 - How to Choose an Azure Relational Database.mp4

10:53

108 - Evaluate Functional Requirements.mp4

06:56

109 - Evaluate Scaling Requirements.mp4

04:29

110 - Availability and Backup Requirements.mp4

10:24

111 - Security Requirements.mp4

06:50

112 - Scaling Azure SQL Database.mp4

02:21

113 - Using Elastic Pool Database to Scale.mp4

06:23

114 - Scaling SQL VM.mp4

06:31

115 - Using SQL DB Replicas and Sharding.mp4

06:27

116 - SQL Data Sync.mp4

08:49

117 - Prepare a Migration Strategy.mp4

08:18

118 - Prepare an Upgrade Strategy.mp4

02:54

119 - Run a Migration Assessment.mp4

11:57

120 - Perform a Database Migration.mp4

08:09

5 - Microsoft Azure Basics

121 - What is Cloud Computing.mp4

12:01

122 - Basic of azure cloud.mp4

12:01

123 - Basic of azure cloud Continues.mp4

11:11

124 - Disadvatge of azure cloud.mp4

09:48

125 - Disadvatge of azure cloud Continues.mp4

04:38

126 - Azure cloud component and use.mp4

05:40

127 - Azure portal and price of services.mp4

12:01

128 - App services.mp4

07:59

129 - Mobile services.mp4

05:38

130 - Full calculator.mp4

10:42

131 - Web application service.mp4

10:42

132 - Web application service Continues.mp4

06:19

133 - Azure virtual network.mp4

10:06

134 - DNS Servers and VPN Connectivity.mp4

08:51

135 - IBM Cloud Network.mp4

05:18

136 - Azure virtual machine.mp4

08:23

137 - How to create virtual machine.mp4

08:32

138 - Other things in virtual machine.mp4

04:26

139 - How to access virtual machine.mp4

06:00

140 - Azure virtual storage.mp4

08:34

141 - Azure Virtual Storage Continues.mp4

10:29

142 - Configuring vm networking in azure.mp4

07:00

143 - Configuring vm networking in azure Continues.mp4

08:20

144 - What is vm networking.mp4

11:48

145 - Perform configuration management.mp4

08:36

146 - Creating a network in cloud.mp4

11:25

147 - Subnetting.mp4

09:53

148 - Subnetting Continues.mp4

05:52

149 - Increase and decrease in the number of machines.mp4

09:27

150 - How to create sharepoint machine in azure with image.mp4

07:21

151 - How to create sharepoint machine in azure with image Continues.mp4

07:01

152 - How to create windows vm and linux vm.mp4

09:13

153 - What is end point.mp4

11:14

154 - Public port and private port.mp4

09:00

155 - How to create windows and linux machine using portal.mp4

07:15

156 - How to make autoscaling of machine.mp4

12:00

157 - Adding weband web job applcation to web site.mp4

11:07

158 - How to implemnent web site.mp4

08:28

159 - How to implemnent web site Continues.mp4

08:04

160 - Adding machine to availibilty set.mp4

11:07

161 - Brief introduction to virtual machines.mp4

10:55

162 - What is the scalibility.mp4

06:12

163 - Creating a web application.mp4

11:39

164 - Database configuration.mp4

10:10

165 - Connecting azure to on site network.mp4

10:52

166 - Cloud services.mp4

06:37

167 - Scaling facilities.mp4

06:42

168 - What is a networking.mp4

06:03

169 - What is a virtual network.mp4

10:10

170 - Virtual area network address.mp4

03:21

171 - What is a Webjob.mp4

09:47

172 - Creating a virtual machine.mp4

05:51

173 - Monitoring.mp4

11:09

174 - Server manager dashboard.mp4

05:58

175 - Components.mp4

08:25

176 - Local area network.mp4

09:59

177 - Reports.mp4

08:13

178 - SQL Database.mp4

06:45

179 - Recovery Services.mp4

11:58

180 - Remote desktop service azure provsion.mp4

02:08

181 - Desktop services.mp4

11:51

182 - Storsimple.mp4

07:52

183 - Cdnremote appmedia service.mp4

06:06

184 - How to migarte on premise to azure cloud.mp4

11:36

185 - How to migarte on premise to azure cloud Continues.mp4

08:34

186 - How to purchase additional subscrption.mp4

05:47

187 - Billing of azure.mp4

05:07

188 - Planing how to migarte on premise work load to azure cloud.mp4

10:24

189 - Planing how to Migarte on premise work load to azure cloud Continues.mp4

05:00

190 - Azure Hdmi.mp4

07:02

191 - Azure Machine Learning.mp4

11:37

192 - Biztalk Service.mp4

11:40

193 - Traffic Manager.mp4

11:28

194 - Select a Runbook.mp4

10:26

195 - HD Insight.mp4

03:02

6 - Azure Practical Cognitive Services

196 - Introduction to Azure Cognitive.mp4

11:16

197 - Azure Free Tier Account Creation.mp4

05:28

198 - Vision API and Computer Vision Overview.mp4

07:15

199 - Computer Vision Hands on.mp4

08:10

200 - Computer Vision Hands on Continued.mp4

05:52

201 - Face API.mp4

06:42

202 - Face API Handson.mp4

09:26

203 - Custom Vision.mp4

05:10

204 - Custom Vision Handson.mp4

11:36

205 - Form and Ink Recognizer Overview.mp4

05:03

206 - Video Indexer Handson.mp4

08:02

207 - Form Recognizer Hands on.mp4

10:55

208 - Cognitive Speech Api.mp4

01:24

209 - Speech to Text Service.mp4

02:14

210 - Speech to Text Service Handson.mp4

06:37

211 - Text to Speech Service.mp4

02:03

212 - Text to Speech Service Handson.mp4

08:10

213 - Speech Translation Service Overview.mp4

03:45

214 - Speech Translation Service Handson.mp4

12:37

215 - Speech Recognise Overview.mp4

02:24

216 - Speech Recognise REST Api Usage.mp4

10:37

217 - Language Service.mp4

02:28

218 - Sentiment Analysis and Handson.mp4

11:33

219 - Language Translator Service and Handson.mp4

10:24

220 - Understanding Service.mp4

01:56

221 - Understanding Service Handson Part 1.mp4

09:52

222 - Understanding Service Handson Part 2.mp4

13:36

223 - Understanding Service Handson Part 3.mp4

06:38

224 - Understand Services in Action.mp4

03:06

225 - Entity Recognition.mp4

00:46

226 - Entity Recognition Handson.mp4

08:41

227 - Entity Recognition in Action.mp4

04:39

228 - QnA Maker Overview.mp4

01:33

229 - QnA Maker Handson.mp4

06:05

230 - QnA Maker in Action.mp4

05:54

231 - Cognitive Decision Service.mp4

00:52

232 - Content Moderator Overview.mp4

03:42

233 - Image Moderator Application.mp4

12:36

234 - Image Moderator Application Continued.mp4

06:22

235 - Text Moderation.mp4

08:16

236 - Moderation Application in Action.mp4

02:56

237 - Anomaly Detection Overview.mp4

04:01

238 - Anomaly Detection Handson Dependecies Import.mp4

05:30

239 - Anomaly Azure Conection.mp4

09:11

240 - Graph Ploting.mp4

05:30

241 - Anomaly Detection Function.mp4

06:50

242 - Anomaly Application in Action.mp4

01:54

243 - Decision Personalizer Overview.mp4

02:28

244 - Decision Personalizer Application Dependency.mp4

11:50

245 - Decision Personalizer Application.mp4

08:16

246 - Personalizer Service in Action.mp4

01:52

247 - Cognitive Web Search Overview.mp4

02:04

248 - Cognitive Web Search Subparts.mp4

03:45

249 - Cognitive Websearch Application Creation.mp4

10:56

250 - Cognitive Websearch Application Creation Continued.mp4

06:15

251 - Cognitive Websearch Application in Action.mp4

02:42

7 - Azure Cognitive Services Creating an AI Based Chatbot

252 - Introduction to Course.mp4

03:09

253 - QnA Service.mp4

11:55

254 - Java Application Creation.mp4

09:36

255 - Resolving Issues from Application.mp4

06:27

256 - Running Java Aaplication.mp4

07:23

257 - Service Cleanup.mp4

03:35

8 - Microsoft Azure Essentials

258 - Introduction to Microsoft Azure Essentials.mp4

00:50

259 - Five Principles of Cloud.mp4

10:37

260 - History of Cloud Computing.mp4

02:54

261 - Key Types of Cloud Services.mp4

06:26

262 - Cloud Deployment Models.mp4

03:46

263 - Why Microsoft Azure.mp4

04:45

264 - What is Microsoft Azure.mp4

05:49

265 - Microsoft Azure Architecture.mp4

07:39

266 - Register for free Azure Account.mp4

02:43

267 - Demo Microsoft ARM Portal.mp4

09:43

268 - Demo ASM Portal.mp4

08:06

269 - Enterprise Account.mp4

11:11

270 - Azure Subscriptions and Account.mp4

11:15

271 - Tools for Azure.mp4

04:28

272 - Installing Azure Powershell.mp4

07:03

273 - Installing Azure CLI.mp4

04:09

274 - Azure CLI Getting Started.mp4

07:42

275 - Azure PowerShell ASM.mp4

07:08

276 - Azure Powershell ARM Basics.mp4

01:34

277 - Azure Virtual Machines.mp4

03:35

278 - What is Azure VM.mp4

06:13

279 - Azure VM Status.mp4

03:26

280 - Azure VM Billing.mp4

03:57

281 - Azure VM sizes.mp4

04:21

282 - Azure VM deployment Options.mp4

04:27

283 - Azure VM Architecture Classic.mp4

05:57

284 - Azure VM Architecture ARM.mp4

05:15

285 - Azure VM Pricing Tiers.mp4

06:10

286 - Create a Windows VM.mp4

11:06

287 - Create a Windows VM Continues.mp4

09:50

288 - Connecting to a Windows VM.mp4

07:06

289 - Create a Linux VM.mp4

06:47

290 - Connecting to a Linux VM.mp4

05:11

291 - Azure VM Disks.mp4

11:08

292 - Attaching Data Disk to a Windows VM.mp4

07:34

293 - Attaching Data Disk to a Linux VM.mp4

07:48

294 - High Availability in Azure.mp4

08:42

295 - High Availability in Azure Continues.mp4

08:35

296 - VM Availability Sets.mp4

08:08

297 - Creating an Availability Set.mp4

03:31

298 - Joining VM into an Availability Set.mp4

03:31

299 - Azure Virtual Network.mp4

04:00

300 - Azure Network Options.mp4

05:59

301 - Components of Virtual Networks.mp4

04:43

302 - Address Spaces and Subnets.mp4

03:15

303 - Network Security Groups.mp4

05:19

304 - Azure Load Balancers.mp4

06:50

305 - Azure Load Balancers Continues.mp4

06:41

306 - Azure HYbrid Connectivity Options.mp4

11:19

307 - Azure Traffic Manager.mp4

05:05

308 - Creating a Virtual Network and Subnets.mp4

04:49

309 - Creating VM in a VNet and Adding NSG Rules.mp4

10:41

310 - Azure storage.mp4

02:48

311 - Azure Blob Storage.mp4

04:28

312 - Azure Disk Storage.mp4

02:05

313 - Azure File Storage.mp4

03:15

314 - Azure Table Storage.mp4

03:01

315 - Azure Queue Storage.mp4

03:58

316 - Creating a Storage Account and Uploading a Blob.mp4

06:49

317 - Azure Web Apps.mp4

10:31

9 - Microsoft Azure Data Lake

318 - Introduction to Azure Data Lake.mp4

07:17

319 - Introduction to Azure Data Lake Continue.mp4

06:22

320 - Creating Analytics Account.mp4

07:09

321 - Services in Azure Data Lake.mp4

06:34

322 - Processing Data Lake Store.mp4

04:23

323 - Concept of USQL Language.mp4

10:36

324 - Defining Analytics Units.mp4

04:27

325 - Adding Filter Operation.mp4

09:12

326 - Stages of Job.mp4

04:37

327 - Brief on USQL Language.mp4

04:52

328 - Extracitng a Row.mp4

12:36

329 - Schema on Read.mp4

02:19

330 - Aggregating the Data.mp4

03:55

331 - Changing the Group By.mp4

06:55

332 - Injesting Multiple Files.mp4

05:32

333 - Processing the Multiple Files.mp4

03:49

334 - Arranging the Data.mp4

10:14

335 - Distributing the Data.mp4

10:14

336 - Data from Data Lake.mp4

07:13

337 - Checking the Status Update.mp4

06:52

338 - Creating the View.mp4

12:12

339 - Table Valued Functions.mp4

07:56

340 - Script for Table Valued Functions.mp4

08:01

341 - Creating a Store Procedure.mp4

06:38

342 - Running Store Procedure.mp4

04:40

343 - How to use Inline cSharp.mp4

05:56

344 - Azure Portal to Visual Studio.mp4

03:56

345 - Creating New Project.mp4

09:23

346 - Services in Azure Account.mp4

08:48

347 - Submitting SQL Job.mp4

06:09

348 - Analyzing the Job.mp4

07:38

349 - Creating Project Function.mp4

04:46

350 - Monitoring the Status.mp4

08:43

351 - Job Comparison Tool.mp4

03:43

352 - Understanding Job Graph.mp4

05:06

353 - Understanding Job Graph Continues.mp4

07:47

354 - Executing the Job File.mp4

05:54

355 - Concept of Heat Map.mp4

05:12

356 - Vertex Execution View.mp4

06:18

357 - Concept of Job Effeciency.mp4

05:08

358 - Options in Diagnostics Tab.mp4

11:16

359 - Ways of Accessing Azure Data.mp4

03:56

360 - Creating Data Store Accounts.mp4

09:55

361 - Confirming Through Portal.mp4

07:13

362 - Creating a Directory Structure.mp4

04:43

363 - Uploading the Data.mp4

12:20

364 - Using the Powershell.mp4

10:34

365 - Commands for Azure CLI.mp4

07:17

366 - Data Lake Store Account.mp4

08:27

367 - Uploading Data with Azure CLI.mp4

07:58

368 - Renaming the File.mp4

10:26

369 - Deleting Data Lake Account.mp4

01:53

370 - Pricing of Azure Data Lake.mp4

06:37

371 - Summary on Azure Data Lake.mp4

04:58

Description

Master Microsoft Azure and elevate your career with our comprehensive, hands-on course. Prepare for exams too.

What You'll Learn?

Create and manage Azure Machine Learning workspaces.
Develop and submit machine learning pipelines using Azure ML Designer and SDK.
Understand AI concepts and explore common AI workloads.
Utilize Azure Cognitive Services for computer vision and natural language processing (NLP).
Learn data representation and storage options in Azure, including SQL and Cosmos DB.
Set up and manage Azure SQL databases, ensuring security and scalability.
Understand the fundamentals of cloud computing and Azure's core services.
Create and manage virtual machines, storage solutions, and virtual networks in Azure.
Implement high availability and scaling solutions for Azure resources.
Create and manage Azure Data Lake, including data processing and analytics.

Who is this for?

Aspiring Data Scientists: Individuals aiming to build a career in data science and machine learning using Microsoft Azure.

Data Engineers: Professionals involved in designing and managing data processing systems who want to incorporate machine learning capabilities.

AI Engineers: Those interested in developing AI solutions on the Azure platform.

IT Professionals: System administrators or IT managers looking to understand Azure's capabilities for machine learning and data analytics.

Students and Graduates: Those pursuing studies in computer science, data science, or related fields seeking practical knowledge of Azure's data science offerings.

Professionals Transitioning to Data Science: Individuals from non-technical backgrounds looking to transition into data science and AI roles.

Technology Enthusiasts: Anyone passionate about exploring advanced data analytics and machine learning in the cloud environment.

What You Need to Know?

Basic Understanding of Cloud Concepts: Familiarity with cloud computing principles.

Fundamental Knowledge of Machine Learning: Basic understanding of machine learning concepts and terminology.

Programming Experience: Proficiency in at least one programming language, preferably Python.

Azure Basics: Prior experience or knowledge of Microsoft Azure's core services.

More details

Description
Welcome to the Microsoft Azure Mastery Course, a comprehensive learning journey designed to equip you with the knowledge and skills needed to excel in the rapidly evolving field of cloud computing and data science. This course covers a wide array of topics, from foundational principles to advanced applications, ensuring a well-rounded understanding of Microsoft Azure's extensive capabilities.
Microsoft Azure is one of the leading cloud platforms, offering a vast range of services that support various business needs, including data storage, machine learning, AI, and database management. With the increasing demand for cloud-based solutions, proficiency in Azure has become a valuable asset for IT professionals, data scientists, and developers.
Our course is structured into distinct sections, each focusing on a specific aspect of Azure. You will start with an introduction to Azure's data science capabilities and progress through foundational AI concepts, data fundamentals, and relational database management. Practical sections on cognitive services and AI-based chatbot creation will enhance your hands-on experience, while sections on Azure essentials and data lake management will solidify your foundational knowledge.
Whether you are preparing for Microsoft certification exams or seeking to expand your practical skills, this course offers a blend of theoretical knowledge and practical application. You will engage with interactive lessons, real-world scenarios, and step-by-step guides, ensuring a robust learning experience.
By the end of this course, you will be well-prepared to leverage Microsoft Azure's powerful tools and services, ready to tackle complex challenges and drive innovation in your organization. Welcome to your journey towards Azure mastery!
Section 1: DP-100 Microsoft Azure Data Science Exam
In this section, you will gain comprehensive knowledge and hands-on experience with Microsoft Azure's data science capabilities. Starting with an introduction to the course and exam requirements, you will learn how to create and manage an Azure Machine Learning workspace, including its settings through the portal and Azure ML Studio. The section covers the creation and management of datasets, compute instances, and clusters, and takes you through building and submitting machine learning pipelines. You'll delve into custom code, error handling, and understanding complex pipelines, ensuring a thorough grasp of Azure ML Designer and SDK setup. The section also introduces AutoML, model registration, deployment strategies, and production compute targets, preparing you for real-world applications of Azure's machine learning tools.
Section 2: AI-900 MS Azure AI Fundamentals
This section is designed to provide a foundational understanding of artificial intelligence (AI) and its applications within Microsoft Azure. Beginning with an introduction to AI and the AI-900 exam requirements, you will explore common AI workloads, responsible AI principles, and privacy and security considerations. The section covers various machine learning types, dataset features, and the training and validation process. You'll gain practical experience with AutoML, machine learning designer tools, and common computer vision and natural language processing (NLP) workloads, using Azure's services to build and deploy models without extensive coding. This section is perfect for those new to AI and seeking to understand its fundamentals and applications.
Section 3: DP-900 Azure Data Fundamentals
Section 3 focuses on the basics of data representation, storage options, and data workloads within Azure. You'll start with an introduction to the DP-900 exam requirements, followed by an exploration of relational and non-relational databases, including normalization, SQL, and NoSQL databases. Practical demos will guide you through creating databases, views, stored procedures, and indexes, as well as deploying and managing Azure SQL and Cosmos DB. This section also covers modern data warehousing, Azure Data Factory, and data visualization tools like Power BI, providing a comprehensive overview of Azure's data services and their practical applications.
Section 4: DP-300 Azure Relational DBA
This section prepares you for managing relational databases in Azure. After an introduction and overview of the DP-300 exam requirements, you'll learn about Azure's SQL database options, creating and managing Azure VMs, and deploying SQL servers. Topics include functional and scaling requirements, availability and backup strategies, and security measures for SQL databases. You will explore scaling techniques, SQL database replicas, sharding, and data synchronization. The section also covers migration and upgrade strategies, ensuring you are well-equipped to handle Azure SQL database management and optimization.
Section 5: Microsoft Azure - Basics
In Section 5, you will explore the fundamentals of Microsoft Azure and cloud computing. Starting with an overview of cloud computing principles and the history of Azure, you'll learn about key cloud services, deployment models, and the architecture of Microsoft Azure. The section covers account registration, the Azure portal, and various tools for managing Azure services, including PowerShell and CLI. You will gain practical knowledge of Azure virtual machines, storage options, and networking configurations, preparing you to leverage Azure's capabilities for various cloud-based applications and services.
Section 6: Azure Practical - Cognitive Services
Section 6 provides an in-depth look at Azure's cognitive services, focusing on practical applications. You'll begin with an introduction to Azure Cognitive Services and the creation of a free tier account. The section covers vision APIs, computer vision, face API, custom vision, form recognizer, and video indexer, with hands-on exercises for each service. You'll also explore speech APIs, including speech-to-text, text-to-speech, and translation services. Additionally, the section covers language services, sentiment analysis, entity recognition, and the QnA Maker, providing a comprehensive understanding of how to implement cognitive services in real-world scenarios.
Section 7: Azure Cognitive Services - Creating an AI-Based Chatbot
In this section, you will learn how to create an AI-based chatbot using Azure Cognitive Services. Starting with an introduction to the course, you'll explore the QnA service, Java application creation, and resolving issues within the application. The section provides practical steps for running and deploying the chatbot application, ensuring you have the skills to develop and manage AI-based chatbots effectively.
Section 8: Microsoft Azure - Essentials
Section 8 covers the essential principles and services of Microsoft Azure. Beginning with an introduction to Azure essentials, you will learn about the five principles of cloud computing, the history of cloud computing, and key types of cloud services. The section also covers cloud deployment models, Azure's architecture, and account registration. Practical demos will guide you through the Azure Resource Manager (ARM) and Azure Service Manager (ASM) portals, subscription management, and the installation and usage of Azure PowerShell and CLI. This section provides a solid foundation for understanding and utilizing Microsoft Azure's core services.
Section 9: Microsoft Azure - Data Lake
The final section focuses on Azure Data Lake, offering an introduction and overview of its components and services. You will learn how to create analytics accounts, process data within the Data Lake Store, and use the USQL language for data manipulation. The section covers defining analytics units, job stages, data ingestion, and processing multiple files. You'll also explore Azure Data Lake's integration with Visual Studio, monitoring and analyzing jobs, and using PowerShell and CLI for data management. The section concludes with a summary of Azure Data Lake's pricing and capabilities, equipping you with the knowledge to leverage this powerful data storage and processing solution.
Conclusion
By the end of this comprehensive course, you will have a deep understanding of Microsoft Azure's data science, AI, data fundamentals, relational database management, cognitive services, and cloud computing basics. Each section provides practical knowledge and hands-on experience, preparing you for various Azure certification exams and real-world applications of Azure's services. Whether you are a beginner or an experienced professional, this course will enhance your skills and help you leverage Azure's capabilities to their fullest potential.
Who this course is for:
Aspiring Data Scientists: Individuals aiming to build a career in data science and machine learning using Microsoft Azure.
Data Engineers: Professionals involved in designing and managing data processing systems who want to incorporate machine learning capabilities.
AI Engineers: Those interested in developing AI solutions on the Azure platform.
IT Professionals: System administrators or IT managers looking to understand Azure's capabilities for machine learning and data analytics.
Students and Graduates: Those pursuing studies in computer science, data science, or related fields seeking practical knowledge of Azure's data science offerings.
Professionals Transitioning to Data Science: Individuals from non-technical backgrounds looking to transition into data science and AI roles.
Technology Enthusiasts: Anyone passionate about exploring advanced data analytics and machine learning in the cloud environment.

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