Course Content
Course Overview of Data Science
The basic data science course provides an introduction to the fundamental concepts and techniques used in the field of data science. It is designed for individuals who are new to data science or have some prior knowledge but want to strengthen their foundations.Throughout the course, students learn how to collect, clean, analyze, and interpret data to extract valuable insights and make informed decisions. They are introduced to various programming languages commonly used in data science, such as Python or R, and gain hands-on experience with relevant tools and libraries.
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Course Overview of Data Science
04:39
Data Types | Structure vs Non-Structure
The module "Data Types | Structure vs Non-Structure" explores the distinction between structured data, which follows a predefined format such as tables or arrays, and unstructured data, which lacks a fixed organization, like text or images. Students learn to work with both types, understanding their unique properties and suitable techniques for analysis.
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Data Types | Structure vs Non-Structure
04:40
Understanding the Data Processing | ETL Process
The "Understanding the Data Processing | ETL Process" module provides an overview of the Extract, Transform, Load (ETL) process used in data processing. Students learn how to extract data from various sources, transform it into a consistent format, and load it into a target system, gaining insights into the crucial steps involved in preparing data for analysis and decision-making.
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Understanding the Data Processing | ETL Process
07:06
Understanding of Relational Database (SQL) and SQL Query
The module "Understanding Relational Databases (SQL) and SQL Query" covers the fundamentals of relational databases and the SQL language. Students learn how to design and work with tables, define relationships between them, and use SQL queries to retrieve, manipulate, and analyze data. The module emphasizes the importance of structured data storage and retrieval, equipping students with essential skills for managing and querying data in relational database systems.
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Understanding of Relational Database (SQL) and SQL Query
08:30
Demo | Create SQL Database in Microsoft Azure Cloud
Demo | Create SQL Database in Microsoft Azure Cloud
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Demo | Create SQL Database in Microsoft Azure Cloud
05:16
Understanding Non-Relational Database | Azure Cosmos DB
The module "Understanding Non-Relational Databases | Azure Cosmos DB" provides an introduction to non-relational databases and focuses on Azure Cosmos DB, a popular distributed database service. Students learn about the benefits of non-relational databases, such as scalability and flexibility, and explore key concepts like document-oriented data models, partitioning, and global distribution. They gain hands-on experience with Cosmos DB, understanding its features, querying data using SQL-like queries, and designing efficient data models for different use cases. The module highlights the importance of non-relational databases in modern data-driven applications and prepares students to leverage Azure Cosmos DB for their data storage and retrieval needs.
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Understanding Non-Relational Database | Azure Cosmos DB
06:33
Hands-on | Azure Cosmos DB
Hands-on | Azure Cosmos DB
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Hands-on | Azure Cosmos DB
07:02
Understanding Big Data Concepts and Containers Type
The module "Understanding Big Data Concepts and Containers Type" introduces students to the fundamental concepts of big data and the different types of containers used in big data processing. Students learn about the three V's of big data (Volume, Velocity, and Variety) and explore various data storage and processing technologies like Hadoop, Spark, and NoSQL databases. They also gain an understanding of containerization technologies such as Docker and Kubernetes, and how they enable scalable and efficient deployment of big data applications. The module emphasizes the importance of handling large-scale data and equips students with the knowledge to effectively work with big data and leverage containerization for efficient data processing.
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Understanding Big Data Concepts and Containers Type
11:15
Demo | Azure Storage Account & BigData Container
Demo | Azure Storage Account & BigData Container
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Demo | Azure Storage Account & BigData Container
07:10
Understanding the Different Data Analytics Tools in Azure
The module "Understanding the Different Data Analytics Tools in Azure" provides an overview of the various data analytics tools available in the Azure ecosystem. Students learn about Azure Data Lake Analytics, Azure Databricks, Azure HDInsight, and Azure Synapse Analytics, among others. They gain insights into the capabilities and use cases of each tool, such as batch processing, real-time streaming, machine learning, and data warehousing. The module highlights the strengths and features of each tool, enabling students to make informed decisions when selecting the appropriate data analytics tool for their specific needs in Azure.
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Understanding the Different Data Analytics Tools in Azure
11:35
Walkthrough to Azure Data Analytics Tools
Walkthrough to Azure Data Analytics Tools
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Walkthrough to Azure Data Analytics Tools
03:51
Quiz
Quiz
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Quiz
00:10:00
Understanding the Concepts of Data Science | (DP-900 Azure Data Fundamentals) in HINDI

The basic data science course provides an introduction to the fundamental concepts and techniques used in the field of data science. It is designed for individuals who are new to data science or have some prior knowledge but want to strengthen their foundations.

Throughout the course, students learn how to collect, clean, analyze, and interpret data to extract valuable insights and make informed decisions. They are introduced to various programming languages commonly used in data science, such as Python or R, and gain hands-on experience with relevant tools and libraries.

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