Data Engineering for Machine Learning
This practical course focuses on the data pipelines necessary for robust ML workflows. Students will gain proficiency in data cleaning, feature stores, and high-performance ingestion techniques essential for modern ML practice.
£400
Certified ML Data Professional
- Pass mark 70%
- Certificate on completion
- Verifiable public certificate ID
- English · available globally
Data Engineering for Machine Learning: the short answers
- What is Data Engineering for Machine Learning?
- This practical course focuses on the data pipelines necessary for robust ML workflows. Students will gain proficiency in data cleaning, feature stores, and high-performance ingestion techniques essential for modern ML practice.
- Who is Data Engineering for Machine Learning for?
- It is pitched at Intermediate level for Data Engineers working in AI & Machine Learning Foundations, and is studied online from any country.
- How long does Data Engineering for Machine Learning take?
- Around 16 hours of study, plus the assessed assignments and one applied project.
- How is the certification assessed?
- Every assignment and the final project are assessed automatically against the published criteria. The pass mark is 70%, and an item that does not pass can be resubmitted.
- What do I receive when I pass?
- Certified ML Data Professional, issued as a certificate with a unique ID that employers can check in the public certificate register.
- How much does it cost?
- £400 once, with no subscription.
What you will be able to do
- Design scalable ingestion pipelines
- Implement feature engineering workflows
- Utilize distributed computing for data processing
- Optimize database queries for model training
- Ensure data quality and lineage documentation
Written by David Chen, Lead Data Engineer. Every submission is assessed automatically against the published criteria for Certified ML Data Professional, and the certificate is issued the moment the assessment is complete.
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