Data Engineering
- Master Data Engineering (Python, SQL, ETL, Data Warehousing & Big Data)
- Hands-on training with real-time data pipeline projects
- Learn tools like Apache Spark, Hadoop, Airflow & Kafka
- Data Processing, Transformation & Workflow Automation
- Cloud Data Platforms (AWS, Azure, Google Cloud)
- Build scalable data pipelines & real-time streaming systems
- Placement support with interview preparation & career guidance
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Course Curriculum
- Introduction to Data Engineering & Data Lifecycle
- SQL & NoSQL Databases (MySQL, MongoDB)
- ETL/ELT Processes & Data Pipelines
- Big Data Technologies (Hadoop, Spark)
- Data Warehousing (Redshift, Snowflake)
- Cloud Data Platforms (AWS, Azure, GCP)
- Data Processing, Streaming & Workflow Automation
- Introduction to Cloud Computing & AWS Infrastructure
- Identity and Access Management (IAM)
- Amazon EC2 & Virtual Servers
- Amazon S3 Storage & Data Management
- Virtual Private Cloud (VPC)
- Load Balancing & Auto Scaling
- Database Services (RDS, DynamoDB)
- Azure Fundamentals & Cloud Concepts
- Azure Active Directory (Azure AD)
- Role-Based Access Control (RBAC)
- Virtual Machines & Compute Services
- Storage Accounts & Data Services
- Virtual Networks & Security
- Monitoring & Backup Services
- Introduction to Google Cloud Platform
- Projects, Billing & Resource Hierarchy
- Identity & Access Management (IAM)
- Compute Engine & Virtual Machines
- Kubernetes Engine (GKE)
- Cloud Storage Services
- Cloud Databases (SQL & NoSQL)
- CI/CD Pipeline Concepts
- Git Version Control
- Jenkins Build Automation
- Docker Containerization
- Kubernetes Orchestration
- Infrastructure as Code (Terraform)
- Automation & Monitoring Tools
- Career Guidance & Job Roles
- Resume Building
- LinkedIn Optimization
- Mock Interviews (Tech & HR)
- Interview Q&A Preparation
- Soft Skills & Communication
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