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Data Engineering with Python
Essential foundational knowledge. For experienced professionals. Master Data Engineering with Python with hands-on projects and real-world applications.
2.3(3)
•2 Students Enrolled•advanced•1 week•EnglishCourse Overview
Essential foundational knowledge. For experienced professionals. Master Data Engineering with Python with hands-on projects and real-world applications. Curriculum Structure & Core Modules: • 1. Introduction to Data Engineering with Python • 2. Core Principles of Data...
What You'll Learn
- Master the core concepts and principles of Data Engineering with Python
- Apply practical skills through hands-on projects and real-world exercises
- Understand industry best practices and professional workflows in Data Engineering
- Build job-ready skills that employers in Data Engineering are looking for
- Develop problem-solving techniques specific to Data Engineering with Python
Requirements
- Basic computer literacy and a stable internet connection
- Willingness to learn and dedicate time to practice regularly
- No prior experience required — this course starts from the fundamentals
- A computer or laptop capable of running a modern web browser
Earn Your Certificate
Showcase your skills with a certificate! Complete the course, submit your project, and earn your certificate. Here's a sample of what you'll receive to show off your accomplishments.
Course Curriculum
Open-access academic curriculum. All foundational lectures available to read free.
8 Chapters
•32 Lecture
•0s
1. Introduction to Data Engineering with Python: Foundations & First Principles
Chapter 1: Data Engineering Foundations & Python Ecosystem ESTIMATED TIME: 35 min The Modern Data Stack & Data Engineering Lifecycle: Generation, Ingestion, Storage, and Serving Data Engineering with Python Professional Curriculum Aligned with Apache Spark, Airflow, Kafka, and Cloud Lakehouse Engineering Standards 1. The Data Engineering Lifecycle Framework Data engineering is the foundational dis...
2. Introduction to Data Engineering with Python: Core Concepts & Key Terminology
Chapter 1: Data Engineering Foundations & Python Ecosystem ESTIMATED TIME: 40 min Python Concurrency for Data Ingestion: Threading, Multiprocessing, Asyncio, and the GIL Data Engineering with Python Professional Curriculum Aligned with Apache Spark, Airflow, Kafka, and Cloud Lakehouse Engineering Standards 1. The Global Interpreter Lock (GIL) & Workload Bottlenecks CPython's memory management uses...
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3. Introduction to Data Engineering with Python: Practical Implementation Guide
Chapter 1: Data Engineering Foundations & Python Ecosystem ESTIMATED TIME: 35 min Robust Relational Extraction: SQLAlchemy 2.0 Core, Server-Side Cursors, and PostgreSQL COPY Data Engineering with Python Professional Curriculum Aligned with Apache Spark, Airflow, Kafka, and Cloud Lakehouse Engineering Standards 1. The Client-Side Memory Trap: Client vs. Server-Side Cursors When extracting 20,000,00...
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4. Introduction to Data Engineering with Python: Troubleshooting & Best Practices
Chapter 1: Data Engineering Foundations & Python Ecosystem ESTIMATED TIME: 40 min Schema Definition & Data Validation: Pydantic V2, Data Contracts, and Handling Corrupted Data Data Engineering with Python Professional Curriculum Aligned with Apache Spark, Airflow, Kafka, and Cloud Lakehouse Engineering Standards 1. The Need for Data Contracts at the Ingestion Boundary In analytical data platforms,...
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5. Chapter 1 Quiz
6. Assignment 1: Data Engineering with Python Fundamentals Project
Academic Ecosystem & Connected Pathways
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Instructor
PAMCET Learning Team
Institutional Course Curation · PAMCET
Qualifications:
PAMCET Learning Team — Institutional Course Curation, Digitpen Hub LtdMy Skills:
- Curriculum Curation
- Course Content Review
- Learning Outcome Design
- Course Publishing & Quality Assurance
- Platform Content Operations
Reviews
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Free$7.5100% Off
Certificate available separately for $20 after completionCourse Includes
8 Chapters
32 Lectures
1 week
Skill Level advanced
Taught in English
Lifetime Access
Certification of Completion
Category: Data Engineering
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