Data Engineering – Build Scalable Data Pipelines
Master the fundamentals of Data Engineering with this comprehensive course! Learn how to design, build, and maintain data pipelines, databases, and cloud infrastructures to process large-scale data efficiently.
🔹 Course Overview:
This course covers SQL, Python, Big Data Technologies, Cloud Platforms, and Data Warehousing, equipping you with practical skills to work with structured and unstructured data.
🔹 What You’ll Learn:
📌 Data Engineering Fundamentals
✔ Introduction to Data Engineering – Roles, Responsibilities & Industry Use Cases
✔ Data Architecture & ETL Pipelines – Extract, Transform & Load (ETL) Concepts
✔ Relational & NoSQL Databases – MySQL, PostgreSQL, MongoDB
✔ Data Modeling & Schema Design
📌 Big Data Technologies
✔ Hadoop & Spark – Distributed Data Processing
✔ Apache Kafka – Real-time Data Streaming
✔ Data Lake & Data Warehousing – Amazon S3, Google BigQuery, Snowflake
📌 Programming & Automation
✔ Python for Data Engineering – Pandas, NumPy, PySpark
✔ SQL for Data Processing – Writing efficient queries & data transformations
✔ Airflow for Workflow Automation – Scheduling & Managing Data Pipelines
📌 Cloud & DevOps for Data Engineering
✔ AWS, Azure, & GCP – Cloud-based Data Solutions
✔ Docker & Kubernetes – Containerization & Deployment
✔ CI/CD Pipelines – Automating Data Pipeline Deployments
🔹 Who Should Join?
✅ Aspiring Data Engineers looking to break into the field
✅ Software Developers & Data Analysts wanting to transition into Data Engineering
✅ IT & Cloud Professionals interested in data pipelines & cloud data solutions
🔹 Course Highlights:
⭐ Hands-on projects & real-world applications
⭐ Expert-led training with industry best practices
⭐ Certification upon completion
🚀 Start your Data Engineering journey today!
