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HomeCoursesData Science & AnalyticsAI Data Engineering Foundations Professional Certificate

AI Data Engineering Foundations Professional Certificate

By edX with Pragmatic AI Labs

Data Science & Analytics

6.6
•1 verified reviewTrustScore
Our ratings use a 10-star system for more precise quality assessment
Certificate Program
320 hours
Intermediate
Certificate Included
Visit Provider
Write a ReviewWrite a Story
TrustCourse Rating
Verified
C+
TRUST·SCORE
6.6
OUT OF 10
1 verified review
Good
Rating Distribution% of reviews
9-10
0%
8-9
0%
7-8
0%
6-7
100%
0-6
0%

DETAILED RATINGS

Content Quality
7.0
Instructor Delivery
8.0
Platform Experience
7.0
Value For Money
5.0
Learning Outcome
6.0
All reviews are verified by TrustCourse

Course Syllabus

1

Course 1 • Linux and Bash for Data Engineering

2

Course 2 • Scripting with Python and SQL for Data Engineering

3

Course 3 • Python and Pandas for Data Engineering

4

Course 4 • Web Applications and Command-Line Tools for Data Engineering

5

Course 5 • Virtualization, Docker, and Kubernetes for Data Engineering

6

Course 6 • Spark, Hadoop, and Snowflake for Data Engineering

7

Course 7 • Advanced Data Engineering

8

Course 8 • Rust Data Engineering

TrustCourse AI AnalysisAI Generated
Based on public data analysis
•
Updated May 28, 2025
6.6/10
Good

Course Goal

Master Python, Bash, and SQL for data engineering. Build scalable data pipelines, automate workflows, and gain hands-on experience with cutting-edge tools like Spark, Hadoop, Snowflake, Docker, and Kubernetes.

One-Minute Verdict

Comprehensive 8-course program from experienced instructors, but premium pricing and limited student feedback make it hard to assess real-world value.

PROS

  • Comprehensive 8-course curriculum covering modern data engineering stack
  • Created by Duke University professors with industry experience
  • Includes cutting-edge tools like Rust, Kubernetes, and MLflow

CONS

  • Very expensive at over $3,000 even with discount
  • Limited verified student feedback and outcomes
  • 8-month commitment may be too lengthy for some learners

DETAILED AI RATINGS

Content Quality
7.0/10

Covers modern data engineering stack comprehensively. Created by Duke professors but lacks verified student outcomes data.

Instructor Delivery
8.0/10

Led by experienced Duke faculty with industry partnerships. Strong academic credentials but teaching style unclear.

Platform Experience
7.0/10

Standard edX platform reliability. 8-month timeline provides structure but may feel lengthy for some learners.

Value For Money
5.0/10

High cost at $3,233 (discounted) for 8 courses. Claims master's-level content but lacks market validation.

Learning Outcome
6.0/10

Promises industry-relevant skills with hands-on labs. Limited graduate success stories available for verification.

DECISION GUIDE

Take This Course If

You have significant budget and want comprehensive, university-level data engineering education

The academic credentials and comprehensive curriculum justify the investment for serious career changers with resources.

Skip This Course If

You're budget-conscious or prefer learning from proven student outcomes

Free alternatives like DataTalks Club DE Zoomcamp offer similar skills with verified community success stories.

SOURCES & REFERENCES

  • https://www.edx.org/certificates/professional-certificate/ai-data-engineering-foundations
  • https://www.reddit.com/r/dataengineering/comments/18uffjq/professional_certificate_in_data_engineering/
  • https://www.linkedin.com/posts/noahgift_dataengineering-edx-pragmaticailabs-activity-7207391377540665344-00Bj
  • https://www.edx.org/school/ai
  • https://paiml.com

About this AI Summary

This summary is generated by AI based on public internet data, including social networks and available articles.

Powered by AI

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