Elasticsearch is a powerful tool not only for powering search on big websites but also for analyzing big data sets in a matter of milliseconds. It’s an increasingly popular technology, and a valuable skill to have in today’s job market. This comprehensive course covers it all, from installation to operations, with 60 lectures including 8 hours of video. Elasticsearch is positioning itself to be a much faster alternative to Hadoop, Spark, and Flink for many common data analysis requirements. It’s an important tool to understand, and it’s easy to use! Dive in and see what it’s all about.

1,814 positive ratings from 11,737 students enrolled

• Access 96 lectures & 8 hours of content 24/7
• Set up search indices on an Elasticsearch cluster & querying that data in many ways
• Import data into an Elasticsearch index
• Stream data into Elasticsearch using Logstash & Filebeat
• Bucket & analyze data & visualize it using the Elastic Stack’s web UI, Kibana
• Manage operations on your Elastic Stack using X-Pack to monitor your cluster’s health

“The course is detailed and very well structured. It provides necessary insights and kick-starts your experience with the elastic stack.” – Deepanshu Galyan

This is a full 3-hour Python Keras Neural Network & Deep Learning Boot Camp that will help you learn basic machine learning, neural networks and deep learning using one of the most important Deep Learning frameworks—Keras. This course is your complete guide to the practical machine and deep learning using the Keras framework in Python. This means, this course covers the important aspects of Keras (Google’s powerful Deep Learning framework) and if you take this course, you can do away with taking other courses or buying books on Python Keras based data science.

4.8/5 rating on Udemy!

• Access 35 lectures & 3 hours of content 24/7
• Get started w/ Jupyter notebooks for implementing data science techniques in Python
• Understand the basics of Keras syntax
• Create artificial neural networks & deep learning structures w/ Keras

Note: Software not included

The concept of AI and ML can be a little bit intimidating for beginners, and specifically for people without a substantial background in complex math and programming. This training is a soft starting point to walk you through the fundamental theoretical concepts. You’ll be familiar with the basic definition of concepts then gradually move on to the most basic applications.

256 positive ratings from 20,567 students enrolled

• Access 25 lectures & 2 hours of content 24/7
• Understand what AI, Machine Learning & Deep Learning are
• Differentiate Applied AI from Generalized AI
• Learn about clustering & dimensions reduction

“The course is focusing more on the concept which is good rather than diving to solving big regression sums and computing slopes of lines of least squares.” – Kalyan Mukherjee

Big Data analysis is an essential component of any company organization that works with mass amounts of data, and it’s a constantly adapting and innovating field. Spark Streaming is a new and quickly developing technology for processing mass data sets in real-time. Whether it’s clickstream data from a major website, sensor data from an Internet of Things deployment, financial data, or any other large stream of data, Spark Streaming has the capability to transform and analyze that data as it is created. The professional applications of this technology are obvious, and this course will get you up to speed not just in Spark Streaming, but in Big Data generally, so you can confidently start looking for high-paying Big Data jobs.

2,584 positive ratings from 18,655 students enrolled

• Access 35 lectures & 6 hours of content 24/7
• Get a crash course in the Scala programming language
• Learn how Apache Spark operates on a cluster
• Set up discretized streams w/ Spark Streaming & transform them as data is received
• Analyze streaming data over sliding windows of time
• Maintain stateful information across streams of data
• Connect Spark Streaming w/ highly scalable source of data, including Kafka, Flume, & Kinesis
• Dump streams of data in real-time to NoSQL databases such as Cassandra

Machine Learning and artificial intelligence (AI) is everywhere; if you want to know how companies like Google, Amazon, and even Udemy extract meaning and insights from massive data sets, this data science course will give you the fundamentals you need. If you’ve got some programming or scripting experience, this course will teach you the techniques used by real data scientists and machine learning practitioners in the tech industry – and prepare you for a move into this hot career path.

20,813 positive ratings from 126,185 students enrolled

• Access 104 lectures & 14 hours of content 24/7
• Build artificial neural networks w/ Tensorflow & Keras
• Make predictions using linear regression, polynomial regression, & multivariate regression
• Implement machine learning at massive scale w/ Apache Spark’s MLLib
• Design and evaluate A/B tests using T-Tests and P-Values

“Very comprehensive course on the basics of data science and ML. The instructor explains everything in a clear yet accurate way.” – Gabriel Alfranca Ramón

“Big data” analysis is a hot and highly valuable skill – and this course will teach you the hottest technology in big data: Apache Spark. Employers including Amazon, eBay, NASA JPL, and Yahoo all use Spark to quickly extract meaning from massive data sets across a fault-tolerant Hadoop cluster. You’ll learn those same techniques, using your own Windows system right at home. It’s easier than you might think, and you’ll be learning from an ex-engineer and senior manager from Amazon and IMDb.

10,873 positive ratings from 55,513 students enrolled

• Access 52 lectures & 7 hours of content 24/7
• Frame big data analysis problems as Apache Spark scripts
• Optimize Spark jobs through partitioning, caching, & other techniques
• Process continula streams of data w/ Spark Streaming
• Develop distributed code using the Scala programming language

The world of Hadoop and “Big Data” can be intimidating – hundreds of different technologies with cryptic names form the Hadoop ecosystem. With this Hadoop tutorial, you’ll not only understand what those systems are and how they fit together – but you’ll go hands-on and learn how to use them to solve real business problems! Learn and master the most popular big data technologies in this comprehensive course, taught by a former engineer and senior manager from Amazon and IMDb. We’ll go way beyond Hadoop itself, and dive into all sorts of distributed systems you may need to integrate with.

19,912 positive ratings from 107,065 students enrolled

• Access 98 lectures & 14 hours of content 24/7
• Design distributed systems that manage “big data” using Hadoop a& related technologies
• Use Pig & Spark to create scripts to process data on a Hadoop cluster in more complex ways
• Analyze non-relational data using HBase, Cassandra, & MongoDB
• Use HDFS & MapReduce for storing and analyzing data at scale

“Excellent introduction to the big data technologies delivered in a very professional manner. Frank is an amazing instructor. I would highly recommend this course to anyone who wants to dive in the world of big data.” – Sangam Batra

Big data is hot, and data management and analytics skills are your ticket to a fast-growing, lucrative career. This course will quickly teach you two technologies fundamental to big data: MapReduce and Hadoop. Learn and master the art of framing data analysis problems as MapReduce problems with over 10 hands-on examples. Write, analyze, and run real code along with the instructor– both on your own system, and in the cloud using Amazon’s Elastic MapReduce service. By course’s end, you’ll have a solid grasp of data management concepts.

2,337 positive ratings from 19,533 students enrolled

• Access 51 lectures & 4 hours of content 24/7
• Run MapReduce jobs quickly using Python & MRJob
• Translate complex analysis problems into multi-stage MapReduce jobs
• Scale up to larger data sets using Amazon’s Elastic MapReduce service
• Understand how Hadoop distributes MapReduce across computing clusters
• Complete projects to get hands-on experience: analyze social media data, movie ratings & more
• Learn about other Hadoop technologies, like Hive, Pig & Spark

“This course is excellent! It is the clearest explanation for the map reduce concept that I have ever heard.” – Philip Solvyev

Have you ever wondered how major companies and organizations manage all of the massive amounts of data they collect? The answer is Big Data technology, and Big Data engineers are in big-time demand. Major employers like Amazon, eBay, and NASA JPL use Apache Spark to extract data sets across a fault-tolerant Hadoop cluster. Sound complicated? That’s why you should take this course, to learn these techniques and more, using your own system at home.

8,281 positive raitngs from 46,796 students enrolled

• Access 48 lectures & 5 hours of content 24/7
• Learn the concepts of Spark’s Resilient Distributed Datastores
• Develop & run Spark jobs quickly using Python
• Translate complex analysis problems into iterative or multi-stage Spark scripts
• Scale up to larger data sets using Amazon’s Elastic MapReduce
• Understand how Hadoop YARN distributes Spark across computing clusters
• Learn about other Spark technologies, like Spark SQL, Spark Streaming, & GraphX

This course is your complete guide to the practical machine and deep learning using the Tensorflow and Keras frameworks in Python. In the age of Big Data, companies across the globe use Python to sift through the avalanche of information at their disposal and the advent of Tensorflow and Keras is revolutionizing deep learning. This course will help you break into this booming field.

344 positive ratings from 9,994 students enrolled

• Access 62 lectures & 5 hours of content 24/7
• Get a full introduction to Python Data Science
• Get started w/ Jupyter notebooks for implementing data science techniques in Python
  Learn about Tensorflow & Keras installation
• Understand the workings of Pandas & Numpy
• Cover the basics of the Tensorflow syntax & graphing environment and Keras syntax
• Discover how to create artificial neural networks & deep learning structures w/ Tensorflow & Keras

Note: Software not included