Data Mastery: Unifying Big Data and Cloud Technologies
A Comprehensive Guide to Scala, Spark, MongoDB, AWS, and Azure for Data Processing, Storage, and Cloud Mastery
Updated on May, 2024
Language - English
IT & Software,Other IT & Software,AWS Glue
Lectures -407
Duration -33.5 hours
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Course Description
This course amalgamates four comprehensive modules, each dedicated to a key technology in the realm of Big Data and Cloud Computing. From Scala & Spark for data processing to MongoDB Mastery, AWS Essentials, and Azure Cloud Mastery, this merged course provides a holistic understanding and hands-on experience in these crucial domains.
Module 1: Scala & Spark for Big Data
Section 1: Scala Fundamentals
Introduction to Scala
Variables, Flow Statements, Functions
Classes, Data Structures
Scala Spark Project Overview
Section 2: Spark Essentials
Hadoop & Spark Overview
Setting up Spark & Databricks
Spark RDDs, DFs
ETL Pipeline with Spark
Module 2: Mastering MongoDB
Section 1: MongoDB Basics
MongoDB Fundamentals
CRUD Operations
Query & Projection Operators
Update Operators
Section 2: Integrations & Projects
MongoDB with Node.js & Python
Building a Django App with MongoDB
ETL Using Spark with MongoDB
Module 3: AWS Cloud Essentials
Section 1: Introduction to AWS
AWS Account Setup & Services Overview
Compute and Storage Services
Infrastructure as Code & Automation
Section 2: Networking & Database Services
Networking Essentials
RDS, Redshift, DynamoDB
Advanced Topics & Integration Services
Section 3: Hands-on Exercise
Real-world Deployment Project with AWS Services
Module 4: Azure Cloud Mastery
Section 1: Azure Cloud Basics
Introduction to Azure Cloud
Azure Account Setup & Pricing
Azure Service Overview
Section 2: Azure Service Mastery
Azure Databricks & Apache Spark
Azure Blob Storage
Azure Data Factory
Section 3: Security & Key Vaults
Azure Key Vaults Implementation
Secure Key Management Practices
Conclusion:
This merged course offers a comprehensive understanding of Scala & Spark for data processing, MongoDB for database management, AWS for cloud computing, and Azure for cloud data services. By the end, learners gain practical experience and proficiency in utilizing these technologies in real-world scenarios.
This course caters to a broad spectrum of learners, ranging from beginners with minimal exposure to these technologies to professionals seeking to enhance their expertise and proficiency in Big Data and cloud computing.
Who this course is for:
- Aspiring Data Professionals: Those aiming to enter the field of data analytics, data engineering, or data science.
- Developers Seeking Data Skills: Developers looking to augment their skill set with proficiency in Big Data tools and cloud technologies.
- Professionals Transitioning to Cloud: Individuals from diverse professional backgrounds interested in transitioning or upskilling in cloud computing.
- Data Enthusiasts and Learners: Anyone passionate about learning Big Data tools, cloud computing, and database management for personal or professional development.
- Tech Professionals Exploring New Horizons: Professionals are curious about exploring new technologies, especially in the realms of data processing, storage, and cloud solutions.
Goals
What will you learn in this course:
Scala & Spark Mastery: Complete understanding of Scala and Spark for efficient data processing.
MongoDB Expertise: Proficiency in MongoDB for robust database management.
AWS & Azure Proficiency: Mastery in essential cloud computing skills across AWS and Azure.
Real-world Application Development: Hands-on experience building practical applications using cloud tools.
Data Transformation & Integration: Ability to perform data transformations and integrate data across cloud platforms.
Prerequisites
What are the prerequisites for this course?
A fundamental understanding of programming concepts will be helpful, although the course is designed to accommodate beginners.
Curriculum
Check out the detailed breakdown of what’s inside the course
Scala & Spark-Master Big Data with Scala and Spark
142 Lectures
-
Introduction: Scala Applications
03:27
03:27
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Introduction: Why Scala
04:56
04:56
-
Introduction: About the Instructor
00:50
00:50
-
Introduction: Introduction to Course
03:30
03:30
-
Introduction: Projects Overview
02:55
02:55
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Overview: What is Scala
02:02
02:02
-
Overview: Scala Setup (Local Machine)
09:46
09:46
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Overview: Scala Setup (Online)
05:05
05:05
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Overview: Variables in Scala
09:18
09:18
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Overview: Arithamatic Operations on Variables-1
05:55
05:55
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Overview: Arithamatic Operations on Variables-2
09:39
09:39
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Overview: Quiz (Arithmatic Operations)
00:55
00:55
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Overview: Solution (Arithmatic Operations)
08:17
08:17
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Overview: Quiz (Strings)
00:42
00:42
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Overview: Solution (Strings)
07:06
07:06
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Overview: Type Casting
11:23
11:23
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Overview: Taking input from User
05:47
05:47
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Overview: Quiz (User Input and Type Casting)
00:29
00:29
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Overview: Solution (User Input and Type Casting)
03:50
03:50
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Flow Control: Overview of Control Statements
03:49
03:49
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Flow Control: If else statements
06:29
06:29
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Flow Control: Conditions in If
06:10
06:10
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Flow Control: Quiz (if statement)
01:27
01:27
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Flow Control: Solution (if statement)
04:17
04:17
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Flow Control: Nested if else
07:37
07:37
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Flow Control: Quiz (nested if else)
01:06
01:06
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Flow Control: Solution (nested if else)
05:15
05:15
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Flow Control: Logical operators
10:27
10:27
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Flow Control: Quiz (Logical operators)
00:43
00:43
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Flow Control: Solution (Logical operators)
06:27
06:27
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Flow Control: If else if
07:01
07:01
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Flow Control: Quiz (if else if)
01:00
01:00
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Flow Control: Solution(if else if)
07:54
07:54
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Flow Control: Overview of Loops
01:52
01:52
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Flow Control: Overview of While Loop
05:34
05:34
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Flow Control: While Loop
08:17
08:17
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Flow Control: Quiz (while loop)
01:18
01:18
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Flow Control: Solution 1 (while loop)
12:00
12:00
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Flow Control: Solution 2 (while loop)
04:31
04:31
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Flow Control: Do While Loop
05:23
05:23
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Flow Control: For Loop
09:21
09:21
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Flow Control: Quiz (For Loop)
01:13
01:13
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Flow Control: Solution (For Loop)
06:53
06:53
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Flow Control: Quiz(For Loop)
01:20
01:20
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Flow Control: Solution(For Loop)
12:26
12:26
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Flow Control: Break
07:30
07:30
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Flow Control: Break Fix
03:45
03:45
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Flow Control: Project Overview
04:19
04:19
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Flow Control: Project Solution Design
05:58
05:58
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Flow Control: Project Solution Code 1
08:07
08:07
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Flow Control: Project Solution Code 2
05:11
05:11
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Flow Control: Project Solution Code 3
08:18
08:18
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Flow Control: Project Solution Code 4
07:34
07:34
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Functions: Overview of Functions
05:57
05:57
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Functions: Writing addition function
08:10
08:10
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Functions: Quiz (Basic Function)
00:52
00:52
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Functions: Solution (Basic Function)
05:18
05:18
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Functions: Functions common issues
05:24
05:24
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Functions: Named Arguments
05:11
05:11
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Functions: Quiz (String Concatination Function)
00:46
00:46
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Functions: Solution (String Concatination Function)
03:08
03:08
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Functions: Quiz (Dividing Code in Functions)
01:12
01:12
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Functions: Solution (Dividing Code in Functions)
09:55
09:55
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Functions: Default Arguments
07:08
07:08
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Functions: Quiz(Default Arguments)
01:44
01:44
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Functions: Solution(Default Arguments)
10:00
10:00
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Functions: Anonymous Functions
05:15
05:15
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Functions: Quiz(Anonymous Functions)
01:11
01:11
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Functions: Solution(Anonymous Functions)
04:55
04:55
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Functions: Scopes
10:43
10:43
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Functions: Project Overview
04:04
04:04
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Functions: Checking Credentials
07:12
07:12
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Functions: Prompting the menu
07:50
07:50
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Functions: Baisc Functions
08:12
08:12
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Functions: Breaking code in more functions
12:28
12:28
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Functions: Final Run
05:11
05:11
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Classes: Introduction to Classes
01:59
01:59
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Classes: Creating Class
06:46
06:46
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Classes: Class Constructor
04:29
04:29
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Classes: Functions and Classes
13:24
13:24
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Classes: Project Overview
02:32
02:32
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Classes: Basic Strucuture
06:20
06:20
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Classes: Final Run
03:30
03:30
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Data Structures: Introduction of Data Structures
02:46
02:46
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Data Structures: Lists introduction
04:59
04:59
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Data Structures: Lists Create and Delete Elements
06:08
06:08
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Data Structures: Lists Take
03:38
03:38
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Data Structures: ListBuffer Introduction
04:38
04:38
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Data Structures: Add data in ListBuffer
03:43
03:43
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Data Structures: Remove data from ListBuffer
03:13
03:13
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Data Structures: Take data from ListBuffer
02:32
02:32
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Data Structures: Project Overview
03:35
03:35
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Data Structures: Project Architecture Discussion
04:52
04:52
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Data Structures: Project Architecture Implementation
10:17
10:17
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Data Structures: User Input for Objects
05:34
05:34
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Data Structures: Implementing the control flow
06:11
06:11
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Data Structures: Creating Required Functions inside Class
07:24
07:24
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Data Structures: Overview of Maps
02:53
02:53
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Data Structures: Creating Maps
04:00
04:00
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Data Structures: Check Key in Map
03:15
03:15
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Data Structures: Update Value in Map
03:04
03:04
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Data Structures: Add and Remove items from Maps
05:04
05:04
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Data Structures: Iterating on Maps
03:12
03:12
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Data Structures: Project Overview
01:57
01:57
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Data Structures: Project Architecture
05:54
05:54
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Data Structures: Project Structure Code
03:26
03:26
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Data Structures: Using Maps for word count
07:05
07:05
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Data Structures: Final Run
07:46
07:46
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Data Structures: Sets Overview
05:01
05:01
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Data Structures: Add and Remove Item from the Set
03:23
03:23
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Data Structures: Set Operations
03:41
03:41
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Data Structures: Overview of Stack
01:59
01:59
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Data Structures: Push and Pop in Stack
03:58
03:58
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Data Structures: Stack Attributes
05:23
05:23
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Data Structures: Project Overview
02:41
02:41
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Data Structures: Project Architecture
10:47
10:47
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Data Structures: Extra Closing Bracket Use Case
10:25
10:25
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Data Structures: Extra Starting Bracket Use Case
08:29
08:29
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Project: Project Introduction
00:56
00:56
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Project: Why Spark
05:05
05:05
-
Project: Hadoop EcoSystem
05:22
05:22
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Project: Spark Architecture
02:29
02:29
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Project: Spark EcoSystem
03:07
03:07
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Project: DataBricks Account
03:16
03:16
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Project: Setting up DataBricks Cluster
04:14
04:14
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Project: Spark Local Setup
04:23
04:23
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Project: Spark Hadoop Setup
04:02
04:02
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Project: Spark RDDs
01:55
01:55
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Project: Spark RDDs (textFile, collect)
15:36
15:36
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Project: Spark Local Run
02:37
02:37
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Project: Understanding Map
06:06
06:06
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Project: Understanding Flat Map
09:54
09:54
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Project: Understanding Reduce By Key
05:25
05:25
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Project: Word Count Example
14:52
14:52
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Project: Spark DFs
03:13
03:13
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Project: Spark DF Read Data
06:24
06:24
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Project: Spark Print Schema, Select
03:30
03:30
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Project: Spark GroupBy
04:22
04:22
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Project: Spark DF Write
11:27
11:27
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Project: Creating S3 bucket
04:12
04:12
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Project: Creating Database in RDS
04:15
04:15
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Project: Performing ETL
19:38
19:38
MongoDB Mastery: Your Essential Guide to Dominating Database
169 Lectures
AWS Essentials: Master Cloud Computing from Scratch - AWS
43 Lectures
Azure Cloud Mastery: Elevate Your Azure Cloud Data Skills
53 Lectures
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