Introduction to Data Engineering
This program dives deep into the foundational principles of
building and maintaining robust data infrastructure, essential for empowering
analytics and machine learning initiatives. Participants will gain mastery in
designing and implementing efficient data pipelines, executing ETL processes,
optimizing database structures, and leveraging cloud platforms to ensure
seamless and reliable data flow from diverse sources to actionable insights.
₦400,000
Nigeria
$266.67
International
6 Weeks
Duration
- Virtual Classes (specific days/times to be confirmed upon registration).
Curriculum Breakdown
Develop in-demand skills to build the backbone of
modern data-driven organizations. Gain practical expertise in managing large
datasets and contributing to scalable data solutions.
1
Foundations of Data Engineering
- Introduction to Data Engineering concepts and ecosystem
- Data Sources and Types (Structured, Semi-structured, Unstructured)
- Understanding Data Lifecycle
- Introduction to Cloud Computing for Data (AWS/Azure/GCP overview)
2
Database Management and SQL
- Relational Databases (e.g., PostgreSQL, MySQL)
- Advanced SQL for Data Engineering (DDL, DML, performance tuning)
- NoSQL Databases (e.g., MongoDB, Cassandra) basics
- Data Warehousing Concepts (OLAP vs. OLTP)
3
Data Integration and ETL Processes
- Introduction to ETL/ELT
- Data Ingestion Techniques (Batch vs. Streaming)
- Working with Apache Airflow (or similar orchestrator)
- Data Transformation Techniques (e.g., using Python/Pandas)
4
Big Data Technologies and Cloud Services
- Introduction to Big Data concepts (Hadoop, Spark)
- Cloud Data Lakes (e.g., S3, ADLS)
- Cloud Data Warehouses (e.g., Snowflake, BigQuery, Redshift)
- Introduction to Data Streaming (e.g., Kafka, Kinesis)
5
Data Governance, Monitoring & Advanced Topics
- Data Quality and Data Governance principles
- Data Security and Privacy in Data Engineering
- Monitoring and Alerting Data Pipelines
- Introduction to DataOps and MLOps principles for data pipelines
6
Capstone Project & Deployment
- Designing and implementing an end-to-end Data Engineering Project
- Deployment strategies for data pipelines
- Troubleshooting and optimization
- Final Project Presentation
Job Opportunities
- Data Engineer
- ETL Developer
- Cloud Data Engineer
- Data Architect
- Big Data Engineer
Enroll Now to get Started
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