What you will learn
- Master the fundamentals of data engineering, including ETL (Extract, Transform, Load) processes.
- Learn to work with SQL, Python, and Apache Spark for data management.
- Gain hands-on experience with IBM Cloud and data pipeline tools.
- Understand big data processing, data lakes, and data warehousing.
- Develop skills in database management, data modeling, and automation.
- Work on real-world projects to solidify your expertise in data engineering.
Program Overview
Introduction to Data Engineering
⏱️4-6 weeks
- Learn core concepts of data engineering and its role in modern businesses.
- Understand structured vs. unstructured data and database fundamentals.
Working with SQL & Databases
⏱️ 6-8 weeks
- Master SQL queries, database design, and normalization.
- Work with relational databases and NoSQL databases.
Python for Data Engineering
⏱️ 8-12 weeks
- Learn data manipulation with Python (Pandas, NumPy, and APIs).
- Develop scripts for automating data processing workflows.
Big Data & Cloud Technologies
⏱️ 10-12 weeks
- Understand Hadoop, Spark, and cloud computing (IBM Cloud, AWS, Azure).
- Learn how to store and process large-scale datasets efficiently.
Capstone Project
⏱️ 12-15 weeks
- Apply learned concepts to build and optimize a data pipeline.
- Work on real-world datasets to create an end-to-end data engineering solution.
Get certificate
Job Outlook
- Data Engineer roles are in high demand, with salaries ranging from $90K – $150K+ per year.
- Industries like tech, finance, healthcare, and e-commerce are actively hiring data engineers.
- Employers seek expertise in SQL, Python, cloud platforms, and big data technologies.
- Data engineering opens pathways to Machine Learning and AI roles.
Specification: IBM Data Engineering Professional Certificate
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