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DataCamp

Data Engineer in Python

via DataCamp

Overview

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## Advance Your Data Engineering Skills with Python Take your data engineering career to the next level with our Python-focused Track. Building upon the foundational SQL knowledge from our Associate Data Engineer Track, this Track dives deeper into the world of data engineering, emphasizing Python's role in automating and optimizing data processes. ## From Cloud Computing to Advanced Python Programming Your journey begins with an understanding of cloud computing concepts and terminology. From there, you'll progress through Python programming from the basics to advanced topics, including: * Data manipulation and cleaning using powerful libraries like pandas * Importing and exporting data from various sources (CSV, Excel, SQL, JSON, APIs) * Writing efficient, reusable code following best practices * Applying software engineering principles for reliable and maintainable projects Engage in hands-on projects to reinforce your learning and gain practical experience tackling real-world data engineering challenges. ## Master Data Pipelines and Workflow Automation Learn to design and implement ETL and ELT pipelines, automate workflows with Apache Airflow, and use Git for version control in collaborative development. Apply software engineering best practices to build scalable, reliable data pipelines, ensuring efficient data processing and quality management. ## Ideal for Aspiring and Experienced Data Engineers Whether you're an aspiring data engineer looking to break into the field or an experienced professional seeking to enhance your Python skills, this Track is designed to meet your needs. With a focus on hands-on learning and real-world applications, you'll gain the confidence and expertise to tackle diverse data engineering projects. ## Unlock New Career Opportunities As companies increasingly rely on data-driven decision making, the demand for skilled data engineers continues to grow. By completing this Track, you'll be well-positioned to: * Pursue data engineering roles across various industries * Collaborate effectively with data scientists and analysts * Contribute to the development of data-intensive applications * Drive business value through efficient data management and analysis Invest in your future and unlock new career opportunities with the Data Engineer in Python Track.

Syllabus

  • Understanding Cloud Computing
    • A non-coding introduction to cloud computing, covering key concepts, terminology, and tools.
  • Introduction to Python for Developers
    • Master the fundamentals of programming in Python. No prior knowledge required!
  • Intermediate Python for Developers
    • Dive into the Python ecosystem, discovering modules and packages along with how to write custom functions!
  • Introduction to Importing Data in Python
    • Learn to import data into Python from various sources, such as Excel, SQL, SAS and right from the web.
  • Intermediate Importing Data in Python
    • Improve your Python data importing skills and learn to work with web and API data.
  • Introduction to APIs in Python
    • Dive into the exciting world of APIs as we introduce you to the basics of consuming and working with Web APIs using Python.
  • Cleaning Data in Python
    • Learn to diagnose and treat dirty data and develop the skills needed to transform your raw data into accurate insights!
  • Cleaning Bank Marketing Campaign Data
  • Writing Efficient Python Code
    • Learn to write efficient code that executes quickly and allocates resources skillfully to avoid unnecessary overhead.
  • Streamlined Data Ingestion with pandas
    • Learn to acquire data from common file formats and systems such as CSV files, spreadsheets, JSON, SQL databases, and APIs.
  • Introduction to Git
    • Discover the fundamentals of Git for version control in your software and data projects.
  • Intermediate Git
    • Discover branches and remote repos for version control in collaborative software and data projects using Git!
  • Software Engineering Principles in Python
    • Learn about modularity, documentation, and automated testing to help you solve data science problems more quickly and reliably.
  • Performing a Code Review
  • ETL and ELT in Python
    • Learn to build effective, performant, and reliable data pipelines using Extract, Transform, and Load principles.
  • Introduction to Apache Airflow in Python
    • Learn how to implement and schedule data engineering workflows.
  • Building a Retail Data Pipeline
  • Cleaning Data in Python

Taught by

Hugo Bowne-Anderson, Adam Spannbauer, Logan Thomas, Amany Mahfouz, Mike Metzger, Adel Nehme, Sara Billen, Lis Sulmont, Jake Roach, and George Boorman

Reviews

4.1 rating at DataCamp based on 22 ratings

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