Gain proficiency in the mastery of Geographic Information Systems (GIS) via ArcGIS Desktop
Pre-process and Analyze Satellite Remote Sensing Data with Free Software
Start your data science journey with this carefully constructed comprehensive course and get hands-on experience with Python for data science. Gain in-depth knowledge about core Python and essential mathematical concepts in linear algebra, probability, and statistics. Complete data science training with 13+ hours of content.
In this course, we will process massive streams of real-time data using Spark Streaming and create Spark applications using the Scala programming language (v2.12). We will also get our hands-on with some real live Twitter data, simulated streams of Apache access logs, and even data used to train machine learning models.
Elasticsearch and Elastic Stack are important tools for managing massive data. You need to know the problems it solves and how it works to design the best systems and be the most valuable engineer you can be. Explore Elasticsearch 8 and learn to manage operations on your Elastic Stack with this comprehensive course. This course covers it all, from installation to operations.
Take your basic cyber security knowledge to a new level with this exciting course that promises to be educational, informative, and fun-filled. Build upon a basic foundation in cyber security with a strong focus on networking, privacy and anonymity, malware, email security, backups and encryption, and Windows 10 Hardening.
This is a comprehensive and practical Apache Spark course. In this course, you will learn and master the art of framing data analysis problems as Spark problems through 20+ hands-on examples, and then scale them up to run on cloud computing services. Explore Spark 3, IntelliJ, Structured Streaming, and a stronger focus on the DataSet API.
This course will show you why Hadoop is one of the best tools to work with big data. With the help of some real-world data sets, you will learn how to use Hadoop and its distributed technologies, such as Spark, Flink, Pig, and Flume, to store, analyze, and scale big data.