IBM Data Engineering Professional Certificate Course Syllabus

Overview: This IBM Data Engineering Professional Certificate is a comprehensive, beginner-friendly program designed to equip learners with foundational and advanced data engineering skills. Through hands-on projects and real-world applications, you'll master SQL, Python, Apache Spark, and cloud technologies on IBM Cloud. The course is self-paced but requires a significant time commitment, with an estimated total duration of 4–6 months at 5–7 hours per week. Modules progress from core concepts to a capstone project, ensuring job-ready skills in data pipelines, ETL, and big data processing.

Module 1: Introduction to Data Engineering

Estimated time: 15 hours

• Core concepts of data engineering
• Role of data engineering in modern businesses
• Understanding structured vs. unstructured data
• Database fundamentals and data lifecycle

Module 2: Working with SQL & Databases

Estimated time: 20 hours

• Mastering SQL queries for data retrieval
• Database design and normalization techniques
• Working with relational databases
• Introduction to NoSQL databases

Module 3: Python for Data Engineering

Estimated time: 30 hours

• Data manipulation using Pandas and NumPy
• Working with APIs for data integration
• Automating data workflows with Python scripts
• Handling data formats (JSON, CSV, XML)

Module 4: Big Data & Cloud Technologies

Estimated time: 35 hours

• Introduction to Hadoop and distributed computing
• Processing big data with Apache Spark
• Cloud computing fundamentals on IBM Cloud
• Storing and managing large-scale datasets
• Overview of AWS and Azure integration

Module 5: ETL and Data Pipeline Development

Estimated time: 25 hours

• Understanding ETL (Extract, Transform, Load) processes
• Building data pipelines for automation
• Data warehousing and data lake concepts
• Optimizing data flow and transformation

Module 6: Final Project

Estimated time: 40 hours

• Design and build an end-to-end data pipeline
• Work with real-world datasets using SQL, Python, and Spark
• Deploy and optimize pipeline on IBM Cloud

Prerequisites

• No prior experience required
• Basic computer literacy
• Access to a computer with internet connection

What You'll Be Able to Do After

• Design and manage relational and NoSQL databases
• Write complex SQL queries and Python scripts for data processing
• Build and optimize ETL pipelines for big data
• Utilize Apache Spark and IBM Cloud for scalable data solutions
• Demonstrate job-ready skills for data engineering roles