Big Data and Hadoop Framework Tutorial: Data analytics, Apache spark, hive, pig, Data Science, MapReduce, Machine learning, Aws EMR, Azure Machine learning
This course is focusing on Big data and Hadoop technologies, hands on demos,
Section 1 - Big data
1.1 Big data introduction
1.2 Big data history
1.3 Big data technologies
1.4 Big data characteristics
1.5 Big data Applications
1.6 Data Lake
1.7 Data Science and Data scientist
Section 2 - Hadoop
2.1 - Hadoop introduction
2.2 - HDFS-Overview
2.3 - Hadoop Architecture
2.3a - Hadoop Architecture - assumptions and goals
2.4 - Demo-Hadoop install - sw download verify integrity
2.5 - Demo-Hadoop install - Java ssh configure
2.6 - Demo hadoop access by browser
Section 3 - Machine Learning
3.1 Machine learning introduction
3.2 Machine learning algorithms
3.3 Machine learning softwares
Module 4 - AWS Machine Learning
4.1 AWS and Machine learning introduction
Below will be added soon.
4.2 Bigdata and aws
4.3 Hadoop on Amazon Elastic Map Reduce (emr)
4.4 What is EMR
4.5 EMR Architecutre
4.6 Demo - launch EMR cluster
2.6 - Hadoop single node cluster setup
2.7 - Hadoop single node - Pseudo-Distributed Operation
2.8 - Hadoop multi node cluster setup
2.9 - MapReduce
2.10 - Azure HDInsight
2.11 - HDFS-Operations
2.12 - Apache Spark and Big data analytics
2.15 - Hadoop, Hive and Pig
What you'll learn
In this article, see the role of big data in healthcare and look at the new healthcare dynamics. Big Data is creating a revolution in healthcare, providing better outcomes while eliminating fraud and abuse, which contributes to a large percentage of healthcare costs.
We need no rocket science in understanding that every business, irrespective of their size in the modern-day business world, needs data insights for its expansion. Big data analytics is essential when it comes to understanding the needs and wants of a significant section of the audience.
Even though Big data is into main stream of operations as of 2020, there are still potential issues or challenges the researchers.
A data expert discusses the three different types of data lakes and how data lakes can be used with data sets not considered 'big data.'
Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments. Our latest survey report suggests that as the overall Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments, data scientists and AI practitioners should be aware of the skills and tools that the broader community is working on. A good grip in these skills will further help data science enthusiasts to get the best jobs that various industries in their data science functions are offering.