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          Opleidingen - Data Engineer - SimpliLearn Subscription bij SimpliLearn

          Data Engineer - SimpliLearn Subscription

          • InstituutSimpliLearn
          • SoortE-Learning
          • Totale lesduur1 dagen
          • Kosten€1.500 excl. BTW

          Gratis brochure

          🗂 10 online trainingen | 🇬🇧 Taal: Engels | 🗓 Abonnement: year | 🎯 Vakgebieden: IT,  data, marketing

          The Data Engineer Track allow you to become an expert in Data . During this Learning Track you will follow 10 different trainings to develop your knowledges and skills in the field.
          For each training completed, receive a certification and continue your progress to become expert in Data.

          Big Data for Data Engineering

          This introductory course from IBM will teach you the basic concepts and terminologies of Big Data, and its real-life applications across multiple industries. You will gain insights on how to improve business productivity by processing large volumes of data and extract valuable information from them.

          Key Learning Objectives

          • Understand what Big Data is sources of Big Data, and real-life examples
          • Learn about the key difference between Big Data and Data Science
          • Master how to use Big Data for operational analysis and better customer service
          • Know the Ecosystem of Big Data and Hadoop framework

          Data Engineering with Hadoop

          Apache Hadoop is one of the most in-demand technologies for analyzing Big Data. This introductory Hadoop course by IBM will give you an overview of what Hadoop is and its components, such as MapReduce and HDFS. Additionally, this course will teach you to explore with large data sets and use Hadoop’s method of distributed processing.

          Key Learning Objectives

          • Understand Hadoop’s architecture and primary components, such as MapReduce and Hadoop Distributed File System (HDFS)
          • Add and remove nodes from Hadoop clusters, check the available disk space on each node, and modify configuration parameters
          • Learn about Apache projects that are part of the Hadoop ecosystem, including Pig, Hive, HBase, ZooKeeper, Oozie, Sqoop, Flume, and more.

          Data Engineering with Scala

          Kickstart your learning of Scala with this introductory course and familiarize yourself with Scala programming. Carefully crafted by IBM, upon completion of this course you will be able to write your Scala codes, perform Big Data analysis using Scala , and create your own Scala projects.

          Key Learning Objectives

          • Create your own Scala Project
          • Understand basic object-oriented programming methodologies in Scala
          • Work with data in Scala such as pattern matching, applying synthetic methods, handling options, failures, and futures

          Big Data Hadoop and Spark Developer

          Simplilearn’s Big Data Hadoop Training Course helps you master Big Data and Hadoop Ecosystem tools, such as HDFS, YARN, MapReduce, Hive, Impala, Pig, HBase, Spark, Flume, Sqoop, Hadoop Frameworks, and more concepts of Big Data processing life cycle. Throughout this online instructor-led Hadoop Training, you will be working on real-time projects on Retail, Tourism, Finance, etc. This Big Data Course also prepares you for Cloudera’s CCA175 Big Data certification.

          Key Learning Objectives

          • Learn how to navigate the Hadoop Ecosystem and understand how to optimize its use
          • Ingest data using Sqoop, Flume, and Kafka
          • Implement partitioning, bucketing, and indexing in Hive
          • Work with RDD in Apache Spark
          • Process real-time streaming data
          • Perform DataFrame operations in Spark using SQL queries
          • Implement User-Defined Functions (UDF) and User-Defined Attribute Functions (UDAF) in Spark

          Python for Data Science

          Kickstart your learning of Python for Data Science with this introductory course and familiarize yourself with programming. Carefully crafted by IBM, upon completion of this course you will be able to write your Python scripts, perform fundamental hands-on data analysis using the Jupyterbased lab environment, and create your own Data Science projects using IBM Watson.

          Key Learning Objectives

          • Write your first Python program by implementing concepts of variables, strings, functions, loops, conditions
          • Understand the nuances of lists, sets, dictionaries, conditions and branching, objects and classes
          • Work with data in Python such as reading and writing files, loading, working, and saving data with Pandas

          Pyspark Training

          Pyspark Training will provide an in-depth overview of Apache Spark, the open-source query engine for processing large datasets, and how to integrate it with Python using the PySpark interface. The course will show you how to build and implement data-intensive applications as you dive into the world of high-performance machine learning leveraging Spark RDD, Spark SQL, Spark MLlib, Spark Streaming, HDFS, Sqoop, Flume, Spark GraphX, and Kafka.

          Key Learning Objectives

          • Understand how to leverage the functionality of Python as you deploy it in the Spark ecosystem
          • Master Apache Spark architecture and how to set up a Python environment for Spark
          • Learn about various techniques for collecting data, RDDs and contrast them with DataFrames, how to read data from files and HDFS, and how to work with schemas
          • Obtain a comprehensive knowledge of various tools that fall under the Spark ecosystem such as Spark SQL, Spark MlLib, Sqoop, Kafka, Flume and Spark Streaming
          • Create and explore various APIs to work with Spark DataFrames, and learn how to aggregate, transform, filter, and sort data with DataFrames.

          Big Data and Hadoop Administrator

          This Big Data and Hadoop Administrator training course will furnish you with the aptitudes and methodologies necessary to excel in the Big Data Analytics industry. With this Hadoop Admin training, you’ll learn to work with the adaptable, versatile frameworks based on the Apache Hadoop ecosystem, including Hadoop installation and configuration, cluster management with Sqoop, Flume, Pig, Hive, Impala, and Cloudera. You’ll learn Big Data implementations that have security, speed, and scale..

          Key Learning Objectives

          • Understand the fundamentals and characteristics of Big Data and various scalability options available to help manage huge quantities of data
          • Master the concepts of the Hadoop framework, including architecture, Hadoop distributed file system, and deployment of Hadoop clusters using core or vendor-specific distributions
          • Use Cloudera manager for setup, deployment, maintenance, and monitoring of Hadoop clusters
          • Work with Hadoop clients, nodes for clients and web interfaces like HUE to work with Hadoop Cluster
          • Use cluster planning and tools for data ingestion into Hadoop clusters, and cluster monitoring activities
          • Understand security implementation to secure data and clusters

          MongoDB Developer and Administrator

          Become an expert MongoDB developer and administrator by gaining an in-depth knowledge of NoSQL and mastering skills of data modeling, ingestion, query, sharding, and data replication. The course includes industry-based projects in e-learning and telecom domains. It is best suited for database administrators, software developers, system administrators, and analytics professionals.

          Key Learning Objectives

          • Develop expertise in writing Java and NodeJS applications using MongoDB
          • Master the skills of Replication and Sharding of data in MongoDB to optimize read/write performance
          • Perform installation, configuration, and maintenance of MongoDB environment
          • Get hands-on experience in creating and managing different types of indexes in MongoDB for query execution
          • Proficiently store unstructured data in MongoDB Develop skill sets in processing huge amounts of data using MongoDB tools
          • Gain proficiency in MongoDB configuration, backup methods as well as monitoring and operational strategies
          • Acquire an in-depth understanding of managing DB Notes, Replica set & Master-Slave concepts

          Apache Cassandra

          This Apache Cassandra certification training will develop your expertise in working with high-volume Cassandra database management system as part of the Big Data Hadoop framework. With this Cassandra training, you will learn Cassandra concepts, features, architecture and data model, and how to install, configure and monitor open-source databases. The Casandra course is ideal for software developers and analytics professionals who wish to further their careers in the Big Data field.

          Key Learning Objectives

          • Describe the need for Big Data and NoSQL
          • Explain the fundamental concepts of Cassandra and its architecture
          • Describe the architecture of Cassandra
          • Demonstrate data model creation in Cassandra Use Cassandra database interfaces
          • Demonstrate Cassandra database configuration

          Apache Spark and Scala

          This Apache Spark and Scala certification training is designed to advance your expertise working with the Big Data Hadoop Ecosystem. You will master essential skills of the Apache Spark open source framework and the Scala programming language, including Spark Streaming, Spark SQL, Machine Learning Programming, GraphX programming and Shell Scripting Spark. This Scala and Spark certification course will give you vital skill sets and a competitive advantage for an exciting career as a Hadoop Developer.

          Key Learning Objectives

          • Understand the limitations of MapReduce and the role of Spark in overcoming these limitations
          • Understand the fundamentals of the Scala programming language and its features
          • Explain and master the process of installing Spark as a standalone cluster
          • Develop expertise in using Resilient Distributed Datasets (RDD) for creating applications in Spark
          • Master Structured Query Language (SQL) using SparkSQL
          • Gain a thorough understanding of Spark streaming features
          • Master and describe the features of Spark ML programming and GraphX programming

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