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 challenge
This mini-course is intended to apply foundational Python skills by implementing different techniques to collect and work with data. Assume the role of a Data Engineer and extract data from multiple file formats, transform it into specific datatypes, and then load it into a single source for ana...
interactive course, join instructor Deepak Goyal to practice performing a wide range of data engineering tasks in Python to boost your technical know-how, prepare for an interview, or land a new role. This course includes Code Challenges powered ...
Run-of-the-mill challenges that face data engineers are not dissimilar to the ones that data scientists experience. Processing data in its many forms is a key focus of attention for both of these professions. However, from the data engineering perspective, we concentrate more on the industrial ...
Data engineering provides the foundation for data science and analytics, and forms an important part of all businesses. This book will help you to explore various tools and methods that are used for understanding the data engineering process using Python. The book will show you how to tackle cha...
The full data workflow often involves many stages, from importing and processing the data to make it suitable for analysis, followed by some number crunching, and then presenting your insights. In this session, you'll see a full data workflow using some LIGO gravitational wave data (no physics...
Data Pipelines Pocket Reference: Moving and Processing Data for Analytics 1st Edition James Densmore著 格式:Kindle版 2021年2月发布 出版商:O 'Reilly Media, Inc. 这是我最喜欢的关于数据管道的书之一。在我的职业生涯中,一些Python和SQL代码片段对我非常有用。本书的Github存储库代码演示了如何从外部数据源...
Learners will also be proficient in detecting and addressing data inconsistencies, such as duplicates and errors. Learners will be able to treat data to make it suitable for further analysis. Upon completion of this module, Upon completion Feature Engineering By the end of this module, learners ...
But what makes Python such a good fit for data science? One of the main reasons whyPythonis so widely used in the scientific and research communities is its accessibility, ease of use, and simple syntax. Thanks to that, people who don’t have any engineering background find it generally ...
He is experienced in data engineering, data science, AWS solutions and engineering management, and has acted as a technical editor on a number of python and data science related publications. As a Data Scientist he helped develop a proprietary growth hacking machine learning algorithm for a start...