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Data Engineer in Python

4.0+
20 reviews

Advance your journey to becoming a Data Engineer with our Python-focused track, which is ideal for those with 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. Starting with an understanding of cloud computing, you'll progress through Python programming from basics to advanced topics, including data manipulation, cleaning, and analysis. Engage in hands-on projects to apply what you've learned in real-world scenarios. You'll explore efficient coding practices, software engineering principles, and version control with Git, preparing you for professional data engineering challenges. Introduction to data pipelines and Airflow will equip you with the skills to design, schedule, and monitor complex data workflows.

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1
Understanding Cloud Computing

A non-coding introduction to cloud computing, covering key concepts, terminology, and tools.

2 hours

Sara Billen Headshot

Sara Billen

Data Scientist at DataCamp

2
Introduction to Python for Developers

Master the fundamentals of programming in Python. No prior knowledge required!

3 hours

George Boorman Headshot

George Boorman

Curriculum Manager, DataCamp

3
Intermediate Python for Developers

Dive into the Python ecosystem, discovering modules and packages along with how to write custom functions!

2 hours

George Boorman Headshot

George Boorman

Curriculum Manager, DataCamp

4
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.

3 hours

Hugo Bowne-Anderson Headshot

Hugo Bowne-Anderson

Data Scientist

5
Intermediate Importing Data in Python

Improve your Python data importing skills and learn to work with web and API data.

2 hours

Hugo Bowne-Anderson Headshot

Hugo Bowne-Anderson

Data Scientist

6
Cleaning Data in Python

Learn to diagnose and treat dirty data and develop the skills needed to transform your raw data into accurate insights!

4 hours

Adel Nehme Headshot

Adel Nehme

VP of Media, DataCamp

7
Cleaning Bank Marketing Campaign Data

Tidy a bank marketing campaign dataset by splitting it into subsets, updating values, converting data types, and storing it as multiple csv files.

2 hours

George Boorman Headshot

George Boorman

Curriculum Manager, DataCamp

8
Writing Efficient Python Code

Learn to write efficient code that executes quickly and allocates resources skillfully to avoid unnecessary overhead.

4 hours

Logan Thomas Headshot

Logan Thomas

Scientific Software Technical Trainer, Enthought

9
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.

4 hours

Amany Mahfouz Headshot

Amany Mahfouz

Data scientist via spatial analytics and geography.

10
Introduction to Git

Familiarize yourself with Git for version control. Explore how to track, compare, modify, and revert files, as well as collaborate with colleagues using Git.

4 hours

George Boorman Headshot

George Boorman

Curriculum Manager, DataCamp

11
Software Engineering Principles in Python

Learn about modularity, documentation, and automated testing to help you solve data science problems more quickly and reliably.

4 hours

Adam Spannbauer Headshot

Adam Spannbauer

Machine Learning Engineer at Eastman

12
Performing a Code Review

Review a data analysis workflow for adherence to Python standards and best-practices.

2 hours

Jake Roach Headshot

Jake Roach

Data Engineer

13
ETL and ELT in Python

Learn to build effective, performant, and reliable data pipelines using Extract, Transform, and Load principles.

4 hours

Jake Roach Headshot

Jake Roach

Data Engineer

14
Introduction to Apache Airflow in Python

Learn how to implement and schedule data engineering workflows.

4 hours

Mike Metzger Headshot

Mike Metzger

Data Engineer Consultant @ Flexible Creations

15
Building a Retail Data Pipeline

Test your Data engineering skills by creating a data pipeline to analyze E-commerce business of Walmart!

2 hours

Anastasia Dvoryanchikova Headshot

Anastasia Dvoryanchikova

Final year Master's student in Statistics and Data Science, Co...

16

code-along

Cleaning Data in Python

In this live training, we will work on cleaning a dataset of audiobooks from audible.in

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Prerequisites

  • Associate Data Engineer

Instructors

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*4.0
from 20 reviews
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  • Wasiu S.
    about 1 month

    The certification exam was not an easy one but fulfilling.

  • Ghebremichael G.
    about 1 month

    I am most impressed with the richness of real world practical exercises that are important for aquiring the skillsets a python data engineer requires. Software development principles and effective coding are part of the track that every software developer has to learn. The availabilty of everyday practice exercises for every course give sense to the the learning process.

  • Lyndon H.
    6 months

    All you need for ETL, if you need to ask do the course.

  • Tracy N.
    6 months

    It is a beginner friendly and well structured track.

  • Carsten H.
    9 months

    Awesome learning experience: Every morning I‘ve done a chapter. It took some time to finish the whole learning track, but it‘s totally worth.

"The certification exam was not an easy one but fulfilling."

Wasiu S.

"All you need for ETL, if you need to ask do the course."

Lyndon H.

"It is a beginner friendly and well structured track."

Tracy N.

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