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Data is multi-disciplinary.

A data driven organization needs to be able to work on a number of fronts simultaneously.

Data Science and Analytics.

Data Science is an emerging discipline at the intersection of statistics, analytics, programming, and machine learning.

Programming and Software Development.

Learning to code involves learning a language, mastering new ways of expression, and becoming immersed in a culture. It enables you to express data-driven ideas and accomplish entirely new things.

DevOps.

DevOps (a mashup of "development" and "operations") is the convergence of everything. As companies seek to deliver software more rapidly, DevOps tools and practices can help in that endeavor.

Infrastructure and Big Data.

Data is powered by tools such as databases (MySQL, PostgreSQL, Oracle), NoSQL storages (Cassandra, MongoDB, Neo4j), search engines (ElasticSearch), distributed computational engines (Apache Spark, Dask), and distributed storage (HDFS, Ceph, MinIO). To be successful they must integrate and work in concert.

DevOps and Infrastructure
Data Science and Big Data

Modern DevOps with Docker and Kubernetes

Software is remaking the world and containers are remaking how we run and manage software. This course introduces two of the most powerful container technologies -- Docker and Kubernetes -- and how they can be used by software Developers.

Length: 3 Days
Audience: Developers, system architects, technical team leads, systems administrators, and DevOps professionals

Continuous Integration With Docker

From development to deployment, containers significantly improve the way we build systems and applications. This online course introduces containers and Docker, a powerful technology for their management.

Highest rated Docker course on Udemy!

Length: 2.2 hours of video content
Audience: Developers interested in using Docker for software development

Data Science Foundations with Python

In a deeply connected world, data can help us to inform and empower. In this course, you will learn to use the Python programming language to gain insight from your information.

Length: 5 days
Audience: Software engineers seeking to understand analytics and work with data in Python

Apache Spark for Data Analytics

Apache Spark is the computation engine that powers big data. In this course, you will learn how to use Apache Spark to work with data, gain insight using Machine Learning, and analyze streams at scale.

Length: 3 days
Audience: Software engineers seeking to understand Spark and Big data analytics, database professionals looking to add analytics skills in a big data environment

Build Skills for Success

Develop skills using cutting edge technologies.

Loading

No results found

Data is multi-disciplinary.

Data Science and Analytics.

Programming and Software Development.

DevOps.

Infrastructure and Big Data.

DevOps and Infrastructure

Data Science and Big Data

Modern DevOps with Docker and Kubernetes

Continuous Integration With Docker

Data Science Foundations with Python

Apache Spark for Data Analytics

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