Data Engineering with Databricks
Master modern data engineering using Databricks' lakehouse platform, building ETL pipelines and implementing data transformations with Apache Spark.
Master modern data engineering using Databricks' lakehouse platform, building ETL pipelines and implementing data transformations with Apache Spark.
This comprehensive course teaches data engineering on the Databricks unified lakehouse platform. Students learn to create and manage Databricks clusters, develop ETL pipelines with Delta Lake, and implement advanced data processing techniques using Apache Spark. The curriculum covers essential skills including notebook analysis, data ingestion from diverse sources, complex data transformations, and production pipeline development. Through hands-on labs and real-world projects, participants master data quality management, workload scheduling, and security implementation using Unity Catalog.
Instructors:
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What you'll learn
Create and manage Databricks clusters for efficient workload processing
Build reliable ETL pipelines using Delta Lake and Apache Spark
Implement advanced data transformations with SQL and DataFrame operations
Develop production-ready pipelines with Delta Live Tables
Secure data access and manage permissions with Unity Catalog
Skills you'll gain
This course includes:
PreRecorded video
Labs, Projects, Assignments
Access on Mobile, Tablet, Desktop
Limited Access access
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There are 2 modules in this course
This course provides comprehensive training in modern data engineering using the Databricks platform. Students learn cluster management, ETL pipeline development, data transformation techniques, and production deployment strategies. The curriculum emphasizes hands-on practice with real-world scenarios and best practices for data lakehouse architecture.
Databricks Lakehouse Platform Fundamentals
Module 1
Data Transformation and Pipelines
Module 2
Fee Structure
Instructors
30 Courses
Pioneering Tech Leader & AI Educator Shaping the Future of Machine Learning
Noah Gift is a distinguished technology leader and founder of Pragmatic AI Labs with a remarkable 30-year career spanning film, TV, telecom, social networks, startups, and big data, currently serving as an Executive-in-Residence at Duke University. As an AWS ML Hero and Python Software Foundation Fellow, he has authored best-selling books through O'Reilly and Pearson on DevOps, MLOps, data engineering, and cloud computing that are widely adopted by major universities. His expertise in MLOps, data engineering, cloud architecture, and Rust programming has led him to teach thousands of students across prestigious institutions including Duke, Northwestern, UC Berkeley, University of San Francisco, and UC Davis, while also collaborating with Caltech and JPL on automated IT systems. Gift's impact extends beyond academia through his work as a startup CTO, his role in developing scalable distributed systems, and his contributions as a keynote speaker at conferences focused on cloud development and ethical AI use, holding certifications from AWS, Google, and Microsoft, and having published over 100 technical works while conducting workshops for organizations like NASA, PayPal, and PyCon.
20 Courses
A Technology Educator and Former Olympic Athlete Pioneering AI Innovation
Alfredo Deza embodies a unique combination of athletic excellence and technological expertise, transitioning from a distinguished career as Peru's first World Junior Champion in high jump and 2004 Olympian to becoming a leading voice in technology education and development. Currently serving as a Principal Cloud Advocate at Microsoft and Adjunct Assistant Professor at Duke University's Pratt School of Engineering, Deza has built an impressive career spanning nearly two decades in software engineering and education. His academic contributions extend through guest lectures at prestigious institutions including Oxford University, Georgia Tech, and Carnegie Mellon University, where he shares expertise in machine learning, cloud computing, and programming languages. As an accomplished author, he has co-authored several influential books with O'Reilly Media, including "Practical MLOps" and "Python for DevOps," while developing comprehensive courses on Coursera covering topics from large language models to Rust programming. His teaching portfolio at Duke includes graduate-level courses in machine learning operations and Python programming, reflecting his commitment to making complex technical concepts accessible. Deza's expertise encompasses a broad spectrum of technologies, including Azure, MLOps, DevOps, Python, Rust, and Databricks, which he leverages to bridge the gap between academic theory and industry practice. His unique perspective, shaped by his background as an Olympic athlete, influences his approach to teaching and technology, emphasizing the importance of continuous learning and knowledge sharing in the rapidly evolving field of artificial intelligence and cloud computing.
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