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Data Engineering Course
The Data Engineering Course teaches how to design, build, and manage data pipelines and architectures.
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Updated 11/2025
Hinglish
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Course Description
This Data Engineering course is ideal for professionals and equips you with Python, SQL, NoSQL, Big Data, Snowflake, AWS, Azure & GCP fundamentals. Prepare for in-demand certifications (AWS, Azure & Snowflake) and build your portfolio using the Capstone project.
1. Introduction to Data Engineering
4 Lectures
Overview of Data Engineering and Its Role in Data Ecosystems
Data Pipelines: Concepts, Architecture, and Workflow
ETL Processes: Extract, Transform, Load Explained
Data Storage Solutions: Databases, Data Lakes, and Warehouses
2. Programming for Data Engineering (Python & SQL)
4 Lectures
Introduction to Python and SQL for Data Engineering
Python Basics: Data Structures, Functions, and Libraries
SQL Fundamentals: Queries, Joins, and Data Retrieval
Data Manipulation and Transformation with Python and SQL
3. Data Modeling and Database Design
4 Lectures
Introduction to Data Modeling and Its Importance
Conceptual, Logical, and Physical Data Models
Entity-Relationship (ER) Modeling and Normalization
Designing Relational Databases for Scalability and Performance
4. Data Warehousing Concepts
4 Lectures
Introduction to Data Warehousing and Its Role in Analytics
Architecture of a Data Warehouse: Components and Layers
ETL Processes: Extract, Transform, Load for Warehousing
Data Modeling for Warehouses: Star, Snowflake, and Fact-Dimension Schemas
5. ETL (Extract, Transform, Load) and Data Pipelines
4 Lectures
Introduction to ETL and Data Pipeline Concepts
Extract: Collecting Data from Multiple Sources
Transform: Cleaning, Standardizing, and Enriching Data
Load: Storing Data into Databases and Data Warehouses
6. Big Data Technologies
4 Lectures
Introduction to Big Data and Its Ecosystem
Big Data Storage Solutions: HDFS, NoSQL, and Cloud Storage
Big Data Processing Frameworks: Hadoop and Spark
Streaming and Real-Time Data Processing Technologies
7. Cloud Data Engineering
4 Lectures
Introduction to Cloud Data Engineering and Its Advantages
Cloud Data Storage Solutions: Data Lakes, Warehouses, and Databases
Building and Managing Data Pipelines in the Cloud
Cloud-Based ETL, Orchestration, and Automation Tools
8. Data Integration and APIs
4 Lectures
Introduction to Data Integration and Its Importance
Understanding APIs: REST, SOAP, and GraphQL
Connecting and Integrating Multiple Data Sources
Data Transformation and Synchronization Across Systems
9. Data Transformation and Processing
4 Lectures
Introduction to Data Transformation and Processing Concepts
Data Cleaning, Normalization, and Standardization Techniques
Aggregating, Filtering, and Enriching Data for Analysis
Batch vs. Stream Processing: Concepts and Use Cases
10. Data Governance, Security, and Quality
4 Lectures
Introduction to Data Governance and Its Importance
Ensuring Data Quality: Accuracy, Consistency, and Completeness
Data Security Principles: Access Control, Encryption, and Compliance
Regulatory Frameworks and Standards (GDPR, HIPAA, etc.)
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Frequently Asked Questions
This course provides comprehensive knowledge with practical examples for
beginners and professionals.
No prior experience required. We start with basics and progress to
advanced topics.
₹30,000
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