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Learn Data Processing, earn certificates with paid and free online courses from MIT, University of Michigan, Johns Hopkins, Duke and other top universities around the world. Read reviews to decide if a class is right for you.
Learn Python programming from basics to advanced concepts, including data structures, web APIs, and databases. Create your own data applications in the final project.
Aprende a programar con Python desde cero. Comienza conociendo variables, bucles y funciones y llega a manejar ficheros de texto.
Master essential techniques for parsing and writing tabular data in TXT and CSV formats, developing practical skills for handling structured scientific datasets effectively.
Master efficient techniques for handling large datasets, from compressed file management to batch processing of NumPy arrays and CSV files, enabling you to work effectively with data at scale.
This free course, Data and processes in computing, will help you to understand the forms of data that are handled by software and look at the various processes that can be applied to the data. ...
Unlock advanced data processing techniques using AI-assisted tools. Generate synthetic data, optimize datasets, and address ethical considerations in data handling for improved analysis efficiency.
Learn advanced data filtering techniques in Python, including category-based filtering, handling multiple datasets, and optimizing code with inline methods for efficient data processing.
Learn Python data processing techniques including data loading, reading, and value-based filtering. Gain practical skills in handling and manipulating datasets efficiently.
Explore the development of a PCI DSS compliant data platform on Kubernetes, addressing challenges in the UK payments infrastructure and discussing key considerations for fintech scalability.
Explore how table formats revolutionize data processing without altering existing systems. Learn about their impact on efficiency, interoperability, and scalability in modern data architectures.
Exploring data processing frameworks beyond Pandas, challenging assumptions about speed, and emphasizing practical considerations for choosing tools that best serve data practitioners.
Introducing Variant data type for efficient semi-structured data processing in lakehouse architecture, offering schema flexibility and improved performance over string parsing.
Explore Meta's Velox query execution engine, its architecture, and its role in modern data processing systems. Learn about its features and performance optimizations.
Discover how IBM leverages Ray for massive-scale data processing, focusing on the Data Prep Kit's capabilities in AI training and scientific research applications.
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