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The Data Science & Big Data Overview | Tools, Tech & Modern Roles in the Data-Driven Enterprise is an introductory level course that introduces the entire multi-disciplinary Data Science team to the many evolving and related terms, with focus on Big Data, Data Science, Predictive Analytics, Artificial Intelligence, Data Mining, Data Warehousing.

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March 2, 2021

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This course provides a high-level view of a variety of core, current data science related technologies, strategies, skillsets, initiatives and supporting tools in common business enterprise practices. In this course you will learn about:

· Foundations: Grids & Virtualization; SOA, ESB / EMB, The Cloud

· The Hadoop Ecosystem: HDFS; Resource Navigators, MapReduce, Spark, Distributions

· Big Data, NOSQL, and ETL

· ETL: Exchange, Transform, Load

· Handling Data & a Survey of Useful tools

· Enterprise Integration Patterns and Message Busses

· Developing in Hadoop Ecosystem: R, Python, Java, Scala, Pig, and BPMN

· Artificial Intelligence and Business Systems

· Who’s on the Team? Evolving Roles and Functions in Data Science

· Growing your Infrastructure

Course Curriculum

    • Grids and Virtualization 00:00:00
    • Service-Oriented Architecture • Enterprise Service Bus • Enterprise Message Bus 00:00:00
    • The Cloud 00:00:00
    • HDFS: Hadoop Distributed File System 00:00:00
    • Resource Negotiators: YARN, Mesos, and Spark; ZooKeeper 00:00:00
    • Hadoop Map/Reduce 00:00:00
    • Spark 00:00:00
    • Hadoop Ecosystem Distributions: Cloudera, Hortonworks, OpenSource 00:00:00
    • Big Data vs. RDBMS 00:00:00
    • NOSQL: Not Only SQL 00:00:00
    • Relational Databases: Oracle, MariaDB, DB/2, SQL Server, PostGreSQL 00:00:00
    • Key/Value Databases: JBoss Infinispan, Terracotta, Dynamo, Voldemort 00:00:00
    • Columnar Databases: Cassandra, HBase, BigTable 00:00:00
    • Document Databases: MongoDB, CouchDB/CouchBase 00:00:00
    • Graph Databases: Giraph, Neo4J, GraphX 00:00:00
    • Apache Hive 00:00:00
    • Common Data Formats 00:00:00
    • Leveraging SQL and SQL variants 00:00:00
    • Data Ingestion, Transformation, and Loading 00:00:00
    • Exporting Data 00:00:00
    • Sqoop, Flume, Informatica, and other tools 00:00:00
    • Enterprise Integration Patterns: Apache Camel and Spring Integration 00:00:00
    • Enterprise Message Busses: Apache Kafka, ActiveMQ, and other tools 00:00:00
    • Languages: R, Python, Java, Scala, Pig, and BPMN 00:00:00
    • Libraries and Frameworks 00:00:00
    • Development, Testing, and Deployment 00:00:00
    • Artificial Intelligence: Myths, Legends, and Reality 00:00:00
    • The Math • Statistics • Probability • Clustering Algorithms, Mahout, MLLib, SciKit, and Madlib 00:00:00
    • Business Rule Systems: Drools, JRules, Pegasus 00:00:00
    • Agile Data Science 00:00:00
    • NOSQL Data Architects and Administrators 00:00:00
    • Developers 00:00:00
    • Grid Administrators 00:00:00
    • Business and Data Analysts 00:00:00
    • Management 00:00:00
    • Evolving your Team 00:00:00
    • Growing your Infrastructure 00:00:00

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