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Data Engineering

Duration : 1 Month
Category :Data Engineering, Data

The objective of the Data Engineering Training program is to equip learners with the technical expertise and practical skills required to design, build, and manage scalable data pipelines and modern data infrastructure. This course provides a comprehensive foundation in data modeling, ETL/ELT processes, distributed systems, cloud data platforms, and best practices for handling large-scale data in enterprise environments.

Learners will gain hands-on experience working with SQL and NoSQL databases, data warehousing concepts, batch and real-time data processing frameworks, workflow orchestration, version control, and cloud-based services. The training emphasizes building reliable data pipelines, ensuring data quality, optimizing performance, and implementing secure and compliant data architectures aligned with industry standards.

By the end of the course, learners will be able to design end-to-end data engineering solutions, automate data workflows, support analytics and machine learning teams, and manage production-grade data ecosystems—preparing them for roles such as Data Engineer, ETL Developer, Big Data Engineer, and Cloud Data Engineer in modern data-driven organizations.

  • Introduction to SQL &Database Concepts
  • Normalization & Entity Relationship Model
  • SQL Operators & Query Optimization
  • Joins, Tables, and Variables in SQL
  • Deep Dive into SQL Functions & Subqueries
  • SQL Views, Stored Procedures, & User-Defined Functions
  • Managing Database Concurrency & SQL Parsing
  • Python Basics & OOPs Concepts
  • NumPy & Pandas for Data Processing
  • Data Visualization Techniques
  • File & Exception Handling
  • Regular Expressions for Data Manipulation
  • Linux Basics & File System Navigation
  • File/Text Manipulation & Process Management
  • User & Group Management
  • Networking, System Monitoring, & Logging
  • Shell Scripting & Security Best Practices
  • Core Concepts of Data Modeling
  • Entity, Class, and Attribute Relationships
  • Conceptual, Logical & Physical Data Modeling
  • Data Modeling Tools & Documentation
  • AWS Basics & Cloud Data Engineering
  • AWS Glue for Data Transformation
  • Amazon EMR, S3, Glacier & DynamoDB
  • AWS Redshift, Athena & QuickSight
  • Amazon Kinesis & Managed Streaming for Apache Kafka
  • Introduction to Microsoft Azure
  • Azure Synapse Analytics & Databricks
  • Azure Stream Analytics & Service Bus
  • Data Storage, Integration & Security
  • Introduction to Airflow
  • Airflow Operators & Workflow Automation
  • Introduction to Apache Spark & PySpar
  • Kafka, Flume & Streaming with PySpark
  • PySpark Machine Learning Basics
  • PySpark SQL & DataFrames
  • Introduction to DevOps & CI/CD
  • Jenkins Automation
  • Git, Docker & Kubernetes for Data Pipelines
  • Data Extraction, Transformation & Modeling
  • Power BI Cloud, Direct Connectivity & API Integration
  • Power BI Premium & Advanced Features
  • What Our Learners Have
  • Data Visualization & Analytics

Alexzender Alex

CSE Teacher

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Nathaniel Bustos

Manager

Latanya Kinard

Web Designer

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