Program profile · official sources
IBM Data Engineering Professional Certificate
The IBM Data Engineering Professional Certificate program on Coursera is a beginner-level series of 16 courses offered by IBM. The curriculum covers foundational data engineering skills including Python programming, SQL, relational databases, NoSQL, Apache Spark, and building data pipelines. Students learn to use tools like MongoDB, Hadoop, and Airflow. Instructed by the IBM Skills Network Team, the self-paced online program has a provider estimate of less than 5 months to complete, while the headline states 6 months at 10 hours a week. Earning the shareable provider-issued course certificate requires completing the hands-on labs and projects throughout the program. As captured on 3 October 2026, the program is taught in English.
Facts checked 3 Oct 2026
- Price
- See pricing
No specific total price is stated. The FAQ describes subscribing to a course or Certificate; financial aid is available. No numeric course-completion total or ISO currency is established from the saved page.
- Time
- 6 months at 10 hours a week
- Level
- Beginner level
- Credential
- Provider-issued course certificate
Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.
- Prerequisites
- Required: Basic IT literacy, knowledge of IT infrastructure, and familiarity working with Windows, Linux, or MacOS. Recommended: Prior computer programming experience and high school math.
- Format
- Completely online, flexible schedule, learn at your own pace
Commercial status: no commercial relationship is documented for this page. The verification link goes directly to the official provider source.
Sources ↗
No accepted numeric price in this registry. See the sourced pricing details below.
See the full registry price landscape. Prices retain their stated payment scope; they are not comparable completion costs.
What’s covered
- Introduction to Data Engineering
- Python for Data Science, AI & Development
- Python Project for Data Engineering
- Introduction to Relational Databases (RDBMS)
- Databases and SQL for Data Science with Python
- Hands-on Introduction to Linux Commands and Shell Scripting
- Relational Database Administration (DBA)
- ETL and Data Pipelines with Shell, Airflow and Kafka
- Data Warehouse Fundamentals
- BI Dashboards with IBM Cognos Analytics and Google Looker
- Introduction to NoSQL Databases
- Introduction to Big Data with Spark and Hadoop
- Machine Learning with Apache Spark
- Data Engineering Capstone Project
- Generative AI: Elevate your Data Engineering Career
- Data Engineering Career Guide and Interview Preparation
Prerequisites: Required: Basic IT literacy, knowledge of IT infrastructure, and familiarity working with Windows, Linux, or MacOS. Recommended: Prior computer programming experience and high school math.
What you actually do
- Introduction to Data Engineering : 14 hours; Course 1 · Source
- Python for Data Science, AI & Development : 24 hours; Course 2 · Source
- Python Project for Data Engineering : 10 hours; Course 3 · Source
- Introduction to Relational Databases (RDBMS) : 16 hours; Course 4 · Source
- Databases and SQL for Data Science with Python : 18 hours; Course 5 · Source
- Hands-on Introduction to Linux Commands and Shell Scripting : 17 hours; Course 6 · Source
- Relational Database Administration (DBA) : 21 hours; Course 7 · Source
- ETL and Data Pipelines with Shell, Airflow and Kafka : 18 hours; Course 8 · Source
- Data Warehouse Fundamentals : 16 hours; Course 9 · Source
- BI Dashboards with IBM Cognos Analytics and Google Looker : 12 hours; Course 10 · Source
- Introduction to NoSQL Databases : 18 hours; Course 11 · Source
- Introduction to Big Data with Spark and Hadoop : 20 hours; Course 12 · Source
- Machine Learning with Apache Spark : 16 hours; Course 13 · Source
- Data Engineering Capstone Project : 18 hours; Course 14 · Source
- Generative AI: Elevate your Data Engineering Career : 13 hours; Course 15 · Source
- Data Engineering Career Guide and Interview Preparation : 11 hours; Course 16 · Source
What the credential is
- Credential type
- Provider-issued course certificate · www.coursera.org / ibm-data-engineer
- Credential
- Shareable certificate · www.coursera.org / ibm-data-engineer
- Issuer
- IBM · www.coursera.org / ibm-data-engineer
- Sharing
- Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review. · www.coursera.org / ibm-data-engineer
- Exam requirement
- The page describes completing hands-on labs and projects to earn a certificate; it does not explicitly establish whether a formal exam is required. · www.coursera.org / ibm-data-engineer
Who should skip it
Alternatives in the registry
Related by topic or level.
- IBM Data Science Professional Certificate : Check official price; 4 months at 10 hours a week.
- AI Product Management Specialization : Check official price; Overview: 4 months at 5 hours a week. FAQ: 15 weeks at 3–5 hours a week, with courses listed as 6, 5 and 4 weeks respectively. These are separate provider estimates..
- Mathematics for Machine Learning Specialization : Check official price; Overview: 4 weeks at 10 hours a week. FAQ: 3/4 hours a week for 3 to 4 months. These are separate provider estimates; no combined completion promise is inferred..