Duke University
Applied Python Data Engineering Specialization
Duke University

Applied Python Data Engineering Specialization

Elevate your coding skills with data engineering. Use big data for decision-making, analysis, AI and machine learning

Taught in English

Kennedy Behrman
Matt Harrison
Noah Gift

Instructors: Kennedy Behrman

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Specialization - 3 course series

Get in-depth knowledge of a subject

3.4

(16 reviews)

Intermediate level

Recommended experience

5 months at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Create scalable big data pipelines (Hadoop, Spark, Snowflake, Databricks) for efficient data handling.

  • Build machine learning workflows (PySpark, MLFlow) on Databricks for seamless model development and deployment.

  • Implement DataOps/DevOps to streamline data engineering processes.

  • Formulate and communicate data-driven insights and narratives through impactful visualizations with Python and data storytelling

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Recently updated!

January 2024

Specialization - 3 course series

Get in-depth knowledge of a subject

3.4

(16 reviews)

Intermediate level

Recommended experience

5 months at 10 hours a week
Flexible schedule
Learn at your own pace

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  • Master a subject or tool with hands-on projects
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Specialization - 3 course series

Spark, Hadoop, and Snowflake for Data Engineering

Course 129 hours3.6 (21 ratings)

What you'll learn

  • Create scalable data pipelines (Hadoop, Spark, Snowflake, Databricks) for efficient data handling.

  • Optimize data engineering with clustering and scaling to boost performance and resource use.

  • Build ML solutions (PySpark, MLFlow) on Databricks for seamless model development and deployment.

  • Implement DataOps and DevOps practices for continuous integration and deployment (CI/CD) of data-driven applications, including automating processes.

Skills you'll gain

Category: Big Data
Category: Python Programming
Category: Information Engineering
Category: Apache Hadoop
Category: Apache Spark

What you'll learn

  • Master virtualization, containerization, and Docker, including Dockerfile creation and multi-container orchestration with Compose and Airflow.

  • Develop expertise in Kubernetes core concepts, cluster architecture, and deployment using cloud environments, GitHub Codespaces, and AI-driven tools.

  • Navigate data scenarios mastering containerization, deploying apps, and addressing production issues with cloud orchestration and SRE practices.

Skills you'll gain

Category: Cloud-Based Integration
Category: containerization
Category: virtualization
Category: Kubernetes
Category: Docker (Software)

What you'll learn

  • Apply Python, spreadsheets, and BI tooling proficiently to create visually compelling and interactive data visualizations.

  • Formulate and communicate data-driven insights and narratives through impactful visualizations and data storytelling.

  • Assess and select the most suitable visualization tools and techniques to address organizational data needs and objectives.

Skills you'll gain

Category: Business Communication
Category: Data Analysis
Category: Python Programming
Category: Cloud Applications
Category: Data Visualization

Instructors

Kennedy Behrman
Duke University
7 Courses37,219 learners

Offered by

Duke University

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