35 Apache courses delivered Live Online

APACHE TRAINING COURSE DESCRIPTION A hands on training course covering installation, configuration and management of the Apache web server. WHAT WILL YOU LEARN * Install Apache. * Configure Apache. * Manage Apache. * Build static and dynamic web sites with Apache. * Secure Apache. APACHE TRAINING COURSE DETAILS * Who will benefit: Technical staff working with Apache. * Prerequisites: TCP/IP foundation for engineers. UNIX fundamentals * Duration 3 days APACHE TRAINING COURSE CONTENTS * Installing Apache What is Apache? Apache versions, history, downloading Apache, source distribution, compilation, binary distribution, installation, platform considerations. Hands on Downloading and installing Apache. * Controlling the Apache server Running Apache, automatic Apache start, starting, stopping, restarting Apache. Checking Apache status. Hands on Server control. * Configuration Serving webpages, setting the document root, applying configuration changes, Configuration files, httpd.conf, syntax, directives, modules, utilities, turning features on/off. Hands on basic Apache configuration. * More configuration MIME, URL mapping, content negotiation, indexing, performance tuning. * Logging log file content, configuration, log file locations, error logging, browser errors, error page configuration, forbidden index pages. Hands on Log files. * Security File permissions, .htaccess, protecting files with passwords, password files, authentication, restricting access by IP address. * Secure HTTP HTTPS, installing mod_ssl, certificates, configuring mod_ssl, http and https coexistence * Virtual hosts Multiple sites on one server, separate configuration files, IP based, name based, port based, virtual host names, enabling, defining, configuring, aliases, testing, https virtual hosts. Hands on Virtual hosts. * Dynamic sites Dynamic sites, CGI, PHP, PERL, CGI programs, example CGI scripts, Apache and CGI, CGI parameters, CGI issues, PHP, mod_php, Perl and Apache, mod_perl, installing mod_perl. Hands on CGI, PHP and Perl with Apache. * Modules What are modules, standard modules, loading modules, mod_speling, mod_rewrite, other special purpose modules, URL rewriting, redirection, URL transformation, browser dependent pages. Hands on Working with modules.

Duration 2 Days 12 CPD hours This course is intended for This in an Introductory and beyond level course is geared for experienced Java developers seeking to be proficient in Apache Kafka. Attendees should be experienced developers who are comfortable with Java, and have reasonable experience working with databases. Overview Working in a hands-on learning environment, students will explore Overview of Streaming technologies Kafka concepts and architecture Programming using Kafka API Kafka Streams Monitoring Kafka Tuning / Troubleshooting Kafka Apache Kafka is a real-time data pipeline processor. It high-scalability, fault tolerance, execution speed, and fluid integrations are some of the key hallmarks that make it an integral part of many Enterprise Data architectures. In this lab intensive two day course, students will learn how to use Kafka to build streaming solutions. INTRODUCTION TO STREAMING SYSTEMS * Fast data * Streaming architecture * Lambda architecture * Message queues * Streaming processors INTRODUCTION TO KAFKA * Architecture * Comparing Kafka with other queue systems (JMS / MQ) * Kaka concepts : Messages, Topics, Partitions, Brokers, Producers, commit logs * Kafka & Zookeeper * Producing messages * Consuming messages (Consumers, Consumer Groups) * Message retention * Scaling Kafka PROGRAMMING WITH KAFKA * Configuration parameters * Producer API (Sending messages to Kafka) * Consumer API (consuming messages from Kafka) * Commits , Offsets, Seeking * Schema with Avro KAFKA STREAMS * Streams overview and architecture * Streams use cases and comparison with other platforms * Learning Kafka Streaming concepts (KStream, KTable, KStore) * KStreaming operations (transformations, filters, joins, aggregations) ADMINISTERING KAFKA * Hardware / Software requirements * Deploying Kafka * Configuration of brokers / topics / partitions / producers / consumers * Security: How secure Kafka cluster, and secure client communications (SASL, Kerberos) * Monitoring : monitoring tools * Capacity Planning : estimating usage and demand * Trouble shooting : failure scenarios and recovery MONITORING AND INSTRUMENTING KAFKA * Monitoring Kafka * Instrumenting with Metrics library * Instrument Kafka applications and monitor their performance

Duration 5 Days 30 CPD hours This course is intended for The CHFI course will benefit: Police and other laws enforcement personnel Defense and Military personnel e-Business Security professionals Systems administrators Legal professionals Banking, Insurance and other professionals Government agencies Overview At the end of this course, you will possess the skills needed to: Understand the fundamentals of computer forensics Understand the computer forensic investigation process Describe in detail different types of hard disks and file systems Understand data acquisition and duplication Counteract anti-forensic techniques Leverage forensic skills in Windows, Linux, and Mac Investigate web attacks Understand dark web forensics Deploy forensic techniques for databases, cloud, and networks Investigate email crimes including malware Perform forensics in mobile and IoT environments Every crime leaves a digital footprint, and you need the skills to track those footprints. In this course, students will learn to unravel these pieces of evidence, decode them and report them. From decoding a hack to taking legal action against the perpetrators, they will become an active respondent in times of cyber-breaches. COMPUTER FORENSICS IN TODAY?S WORLD * 1.1. Understand the Fundamentals of Computer Forensics * 1.2. Understand Cybercrimes and their Investigation Procedures * 1.3. Understand Digital Evidence * 1.4. Understand Forensic Readiness, Incident Response and the Role of SOC (Security * Operations Center) in Computer Forensics * 1.5. Identify the Roles and Responsibilities of a Forensic Investigator * 1.6. Understand the Challenges Faced in Investigating Cybercrimes * 1.7. Understand Legal Compliance in Computer Forensics * COMPUTER FORENSICS INVESTIGATION PROCESS * 2.1. Understand the Forensic Investigation Process and its Importance * 2.2. Understand the Pre-investigation Phase * 2.3. Understand First Response * 2.4. Understand the Investigation Phase * 2.5. Understand the Post-investigation Phase * UNDERSTANDING HARD DISKS AND FILE SYSTEMS * 3.1. Describe Different Types of Disk Drives and their Characteristics * 3.2. Explain the Logical Structure of a Disk * 3.3. Understand Booting Process of Windows, Linux and Mac Operating Systems * 3.4. Understand Various File Systems of Windows, Linux and Mac Operating Systems * 3.5. Examine File System Using Autopsy and The Sleuth Kit Tools * 3.6 Understand Storage Systems * 3.7. Understand Encoding Standards and Hex Editors * 3.8. Analyze Popular File Formats Using Hex Editor * DATA ACQUISITION AND DUPLICATION * 4.1. Understand Data Acquisition Fundamentals * 4.2. Understand Data Acquisition Methodology * 4.3. Prepare an Image File for Examination * DEFEATING ANTI-FORENSICS TECHNIQUES * 5.1. Understand Anti-forensics Techniques * 5.2. Discuss Data Deletion and Recycle Bin Forensics * 5.3. Illustrate File Carving Techniques and Ways to Recover Evidence from Deleted Partitions * 5.4. Explore Password Cracking/Bypassing Techniques * 5.5. Detect Steganography, Hidden Data in File System Structures, Trail Obfuscation, and File Extension Mismatch * 5.6. Understand Techniques of Artifact Wiping, Overwritten Data/Metadata Detection, and Encryption * 5.7. Detect Program Packers and Footprint Minimizing Techniques * 5.8. Understand Anti-forensics Countermeasures * WINDOWS FORENSICS * 6.1. Collect Volatile and Non-volatile Information * 6.2. Perform Windows Memory and Registry Analysis * 6.3. Examine the Cache, Cookie and History Recorded in Web Browsers * 6.4. Examine Windows Files and Metadata * 6.5. Understand ShellBags, LNK Files, and Jump Lists * 6.6. Understand Text-based Logs and Windows Event Logs * LINUX AND MAC FORENSICS * 7.1. Understand Volatile and Non-volatile Data in Linux * 7.2. Analyze Filesystem Images Using The Sleuth Kit * 7.3. Demonstrate Memory Forensics Using Volatility & PhotoRec * 7.4. Understand Mac Forensics * * NETWORK FORENSICS * 8.1. Understand Network Forensics * 8.2. Explain Logging Fundamentals and Network Forensic Readiness * 8.3. Summarize Event Correlation Concepts * 8.4. Identify Indicators of Compromise (IoCs) from Network Logs * 8.5. Investigate Network Traffic * 8.6. Perform Incident Detection and Examination with SIEM Tools * 8.7. Monitor and Detect Wireless Network Attacks * INVESTIGATING WEB ATTACKS * 9.1. Understand Web Application Forensics * 9.2. Understand Internet Information Services (IIS) Logs * 9.3. Understand Apache Web Server Logs * 9.4. Understand the Functionality of Intrusion Detection System (IDS) * 9.5. Understand the Functionality of Web Application Firewall (WAF) * 9.6. Investigate Web Attacks on Windows-based Servers * 9.7. Detect and Investigate Various Attacks on Web Applications * DARK WEB FORENSICS * 10.1. Understand the Dark Web * 10.2. Determine How to Identify the Traces of Tor Browser during Investigation * 10.3. Perform Tor Browser Forensics * DATABASE FORENSICS * 11.1. Understand Database Forensics and its Importance * 11.2. Determine Data Storage and Database Evidence Repositories in MSSQL Server * 11.3. Collect Evidence Files on MSSQL Server * 11.4. Perform MSSQL Forensics * 11.5. Understand Internal Architecture of MySQL and Structure of Data Directory * 11.6. Understand Information Schema and List MySQL Utilities for Performing Forensic Analysis * 11.7. Perform MySQL Forensics on WordPress Web Application Database * CLOUD FORENSICS * 12.1. Understand the Basic Cloud Computing Concepts * 12.2. Understand Cloud Forensics * 12.3. Understand the Fundamentals of Amazon Web Services (AWS) * 12.4. Determine How to Investigate Security Incidents in AWS * 12.5. Understand the Fundamentals of Microsoft Azure * 12.6. Determine How to Investigate Security Incidents in Azure * 12.7. Understand Forensic Methodologies for Containers and Microservices * INVESTIGATING EMAIL CRIMES * 13.1. Understand Email Basics * 13.2. Understand Email Crime Investigation and its Steps * 13.3. U.S. Laws Against Email Crime * MALWARE FORENSICS * 14.1. Define Malware and Identify the Common Techniques Attackers Use to Spread Malware * 14.2. Understand Malware Forensics Fundamentals and Recognize Types of Malware Analysis * 14.3. Understand and Perform Static Analysis of Malware * 14.4. Analyze Suspicious Word and PDF Documents * 14.5. Understand Dynamic Malware Analysis Fundamentals and Approaches * 14.6. Analyze Malware Behavior on System Properties in Real-time * 14.7. Analyze Malware Behavior on Network in Real-time * 14.8. Describe Fileless Malware Attacks and How they Happen * 14.9. Perform Fileless Malware Analysis - Emotet * MOBILE FORENSICS * 15.1. Understand the Importance of Mobile Device Forensics * 15.2. Illustrate Architectural Layers and Boot Processes of Android and iOS Devices * 15.3. Explain the Steps Involved in Mobile Forensics Process * 15.4. Investigate Cellular Network Data * 15.5. Understand SIM File System and its Data Acquisition Method * 15.6. Illustrate Phone Locks and Discuss Rooting of Android and Jailbreaking of iOS Devices * 15.7. Perform Logical Acquisition on Android and iOS Devices * 15.8. Perform Physical Acquisition on Android and iOS Devices * 15.9. Discuss Mobile Forensics Challenges and Prepare Investigation Report * IOT FORENSICS * 16.1. Understand IoT and IoT Security Problems * 16.2. Recognize Different Types of IoT Threats * 16.3. Understand IoT Forensics * 16.4. Perform Forensics on IoT Devices *

Duration 4 Days 24 CPD hours This course is intended for The primary audience for this course is data professionals, data architects, and business intelligence professionals who want to learn about data engineering and building analytical solutions using data platform technologies that exist on Microsoft Azure. The secondary audience for this course includes data analysts and data scientists who work with analytical solutions built on Microsoft Azure. In this course, the student will learn how to implement and manage data engineering workloads on Microsoft Azure, using Azure services such as Azure Synapse Analytics, Azure Data Lake Storage Gen2, Azure Stream Analytics, Azure Databricks, and others. The course focuses on common data engineering tasks such as orchestrating data transfer and transformation pipelines, working with data files in a data lake, creating and loading relational data warehouses, capturing and aggregating streams of real-time data, and tracking data assets and lineage. Prerequisites Successful students start this course with knowledge of cloud computing and core data concepts and professional experience with data solutions. AZ-900T00 Microsoft Azure Fundamentals DP-900T00 Microsoft Azure Data Fundamentals 1 - INTRODUCTION TO DATA ENGINEERING ON AZURE * What is data engineering * Important data engineering concepts * Data engineering in Microsoft Azure 2 - INTRODUCTION TO AZURE DATA LAKE STORAGE GEN2 * Understand Azure Data Lake Storage Gen2 * Enable Azure Data Lake Storage Gen2 in Azure Storage * Compare Azure Data Lake Store to Azure Blob storage * Understand the stages for processing big data * Use Azure Data Lake Storage Gen2 in data analytics workloads 3 - INTRODUCTION TO AZURE SYNAPSE ANALYTICS * What is Azure Synapse Analytics * How Azure Synapse Analytics works * When to use Azure Synapse Analytics 4 - USE AZURE SYNAPSE SERVERLESS SQL POOL TO QUERY FILES IN A DATA LAKE * Understand Azure Synapse serverless SQL pool capabilities and use cases * Query files using a serverless SQL pool * Create external database objects 5 - USE AZURE SYNAPSE SERVERLESS SQL POOLS TO TRANSFORM DATA IN A DATA LAKE * Transform data files with the CREATE EXTERNAL TABLE AS SELECT statement * Encapsulate data transformations in a stored procedure * Include a data transformation stored procedure in a pipeline 6 - CREATE A LAKE DATABASE IN AZURE SYNAPSE ANALYTICS * Understand lake database concepts * Explore database templates * Create a lake database * Use a lake database 7 - ANALYZE DATA WITH APACHE SPARK IN AZURE SYNAPSE ANALYTICS * Get to know Apache Spark * Use Spark in Azure Synapse Analytics * Analyze data with Spark * Visualize data with Spark 8 - TRANSFORM DATA WITH SPARK IN AZURE SYNAPSE ANALYTICS * Modify and save dataframes * Partition data files * Transform data with SQL 9 - USE DELTA LAKE IN AZURE SYNAPSE ANALYTICS * Understand Delta Lake * Create Delta Lake tables * Create catalog tables * Use Delta Lake with streaming data * Use Delta Lake in a SQL pool 10 - ANALYZE DATA IN A RELATIONAL DATA WAREHOUSE * Design a data warehouse schema * Create data warehouse tables * Load data warehouse tables * Query a data warehouse 11 - LOAD DATA INTO A RELATIONAL DATA WAREHOUSE * Load staging tables * Load dimension tables * Load time dimension tables * Load slowly changing dimensions * Load fact tables * Perform post load optimization 12 - BUILD A DATA PIPELINE IN AZURE SYNAPSE ANALYTICS * Understand pipelines in Azure Synapse Analytics * Create a pipeline in Azure Synapse Studio * Define data flows * Run a pipeline 13 - USE SPARK NOTEBOOKS IN AN AZURE SYNAPSE PIPELINE * Understand Synapse Notebooks and Pipelines * Use a Synapse notebook activity in a pipeline * Use parameters in a notebook 14 - PLAN HYBRID TRANSACTIONAL AND ANALYTICAL PROCESSING USING AZURE SYNAPSE ANALYTICS * Understand hybrid transactional and analytical processing patterns * Describe Azure Synapse Link 15 - IMPLEMENT AZURE SYNAPSE LINK WITH AZURE COSMOS DB * Enable Cosmos DB account to use Azure Synapse Link * Create an analytical store enabled container * Create a linked service for Cosmos DB * Query Cosmos DB data with Spark * Query Cosmos DB with Synapse SQL 16 - IMPLEMENT AZURE SYNAPSE LINK FOR SQL * What is Azure Synapse Link for SQL? * Configure Azure Synapse Link for Azure SQL Database * Configure Azure Synapse Link for SQL Server 2022 17 - GET STARTED WITH AZURE STREAM ANALYTICS * Understand data streams * Understand event processing * Understand window functions 18 - INGEST STREAMING DATA USING AZURE STREAM ANALYTICS AND AZURE SYNAPSE ANALYTICS * Stream ingestion scenarios * Configure inputs and outputs * Define a query to select, filter, and aggregate data * Run a job to ingest data 19 - VISUALIZE REAL-TIME DATA WITH AZURE STREAM ANALYTICS AND POWER BI * Use a Power BI output in Azure Stream Analytics * Create a query for real-time visualization * Create real-time data visualizations in Power BI 20 - INTRODUCTION TO MICROSOFT PURVIEW * What is Microsoft Purview? * How Microsoft Purview works * When to use Microsoft Purview 21 - INTEGRATE MICROSOFT PURVIEW AND AZURE SYNAPSE ANALYTICS * Catalog Azure Synapse Analytics data assets in Microsoft Purview * Connect Microsoft Purview to an Azure Synapse Analytics workspace * Search a Purview catalog in Synapse Studio * Track data lineage in pipelines 22 - EXPLORE AZURE DATABRICKS * Get started with Azure Databricks * Identify Azure Databricks workloads * Understand key concepts 23 - USE APACHE SPARK IN AZURE DATABRICKS * Get to know Spark * Create a Spark cluster * Use Spark in notebooks * Use Spark to work with data files * Visualize data 24 - RUN AZURE DATABRICKS NOTEBOOKS WITH AZURE DATA FACTORY * Understand Azure Databricks notebooks and pipelines * Create a linked service for Azure Databricks * Use a Notebook activity in a pipeline * Use parameters in a notebook ADDITIONAL COURSE DETAILS: Nexus Humans DP-203T00 Data Engineering on Microsoft Azure training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the DP-203T00 Data Engineering on Microsoft Azure course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 1 Days 6 CPD hours This course is intended for The course is appropriate for IT managers, architects or anyone who wants to understand the big picture of what Apache Hadoop brings to the enterprise. All levels of technology knowledge are welcome. In this course, students unveil Apache Hadoop, giving themselves a thorough understanding of what the technology is and how it would impact their organizations. In this course, students unveil Apache Hadoop, giving themselves a thorough understanding of what the technology is and how it would impact their organizations.

Duration 1 Days 6 CPD hours This course is intended for The primary audience for this course is data professionals who are familiar with data modeling, extraction, and analytics. It is designed for professionals who are interested in gaining knowledge about Lakehouse architecture, the Microsoft Fabric platform, and how to enable end-to-end analytics using these technologies. Job role: Data Analyst, Data Engineer, Data Scientist Overview Describe end-to-end analytics in Microsoft Fabric Describe core features and capabilities of lakehouses in Microsoft Fabric Create a lakehouse Ingest data into files and tables in a lakehouse Query lakehouse tables with SQL Configure Spark in a Microsoft Fabric workspace Identify suitable scenarios for Spark notebooks and Spark jobs Use Spark dataframes to analyze and transform data Use Spark SQL to query data in tables and views Visualize data in a Spark notebook Understand Delta Lake and delta tables in Microsoft Fabric Create and manage delta tables using Spark Use Spark to query and transform data in delta tables Use delta tables with Spark structured streaming Describe Dataflow (Gen2) capabilities in Microsoft Fabric Create Dataflow (Gen2) solutions to ingest and transform data Include a Dataflow (Gen2) in a pipeline This course is designed to build your foundational skills in data engineering on Microsoft Fabric, focusing on the Lakehouse concept. This course will explore the powerful capabilities of Apache Spark for distributed data processing and the essential techniques for efficient data management, versioning, and reliability by working with Delta Lake tables. This course will also explore data ingestion and orchestration using Dataflows Gen2 and Data Factory pipelines. This course includes a combination of lectures and hands-on exercises that will prepare you to work with lakehouses in Microsoft Fabric. INTRODUCTION TO END-TO-END ANALYTICS USING MICROSOFT FABRIC * Explore end-to-end analytics with Microsoft Fabric * Data teams and Microsoft Fabric * Enable and use Microsoft Fabric * Knowledge Check GET STARTED WITH LAKEHOUSES IN MICROSOFT FABRIC * Explore the Microsoft Fabric Lakehouse * Work with Microsoft Fabric Lakehouses * Exercise - Create and ingest data with a Microsoft Fabric Lakehouse USE APACHE SPARK IN MICROSOFT FABRIC * Prepare to use Apache Spark * Run Spark code * Work with data in a Spark dataframe * Work with data using Spark SQL * Visualize data in a Spark notebook * Exercise - Analyze data with Apache Spark WORK WITH DELTA LAKE TABLES IN MICROSOFT FABRIC * Understand Delta Lake * Create delta tables * Work with delta tables in Spark * Use delta tables with streaming data * Exercise - Use delta tables in Apache Spark INGEST DATA WITH DATAFLOWS GEN2 IN MICROSOFT FABRIC * Understand Dataflows (Gen2) in Microsoft Fabric * Explore Dataflows (Gen2) in Microsoft Fabric * Integrate Dataflows (Gen2) and Pipelines in Microsoft Fabric * Exercise - Create and use a Dataflow (Gen2) in Microsoft Fabric

Duration 4 Days 24 CPD hours This course is intended for This course is best suited to systems administrators and IT managers. Overview Skills gained in this training include:Determining the correct hardware and infrastructure for your clusterProper cluster configuration and deployment to integrate with the data centerConfiguring the FairScheduler to provide service-level agreements for multiple users of a clusterBest practices for preparing and maintaining Apache Hadoop in productionTroubleshooting, diagnosing, tuning, and solving Hadoop issues Cloudera University?s four-day administrator training course for Apache Hadoop provides participants with a comprehensive understanding of all the steps necessary to operate and maintain a Hadoop cluster. THE CASE FOR APACHE HADOOP * Why Hadoop? * Core Hadoop Components * Fundamental Concepts HDFS * HDFS Features * Writing and Reading Files * NameNode Memory Considerations * Overview of HDFS Security * Using the Namenode Web UI * Using the Hadoop File Shell GETTING DATA INTO HDFS * Ingesting Data from External Sources with Flume * Ingesting Data from Relational Databases with Sqoop * REST Interfaces * Best Practices for Importing Data YARN & MAPREDUCE * What Is MapReduce? * Basic MapReduce Concepts * YARN Cluster Architecture * Resource Allocation * Failure Recovery * Using the YARN Web UI * MapReduce Version 1 PLANNING YOUR HADOOP CLUSTER * General Planning Considerations * Choosing the Right Hardware * Network Considerations * Configuring Nodes * Planning for Cluster Management HADOOP INSTALLATION AND INITIAL CONFIGURATION * Deployment Types * Installing Hadoop * Specifying the Hadoop Configuration * Performing Initial HDFS Configuration * Performing Initial YARN and MapReduce Configuration * Hadoop Logging INSTALLING AND CONFIGURING HIVE, IMPALA, AND PIG * Hive * Impala * Pig HADOOP CLIENTS * What is a Hadoop Client? * Installing and Configuring Hadoop Clients * Installing and Configuring Hue * Hue Authentication and Authorization CLOUDERA MANAGER * The Motivation for Cloudera Manager * Cloudera Manager Features * Express and Enterprise Versions * Cloudera Manager Topology * Installing Cloudera Manager * Installing Hadoop Using Cloudera Manager * Performing Basic Administration Tasks Using Cloudera Manager ADVANCED CLUSTER CONFIGURATION * Advanced Configuration Parameters * Configuring Hadoop Ports * Explicitly Including and Excluding Hosts * Configuring HDFS for Rack Awareness * Configuring HDFS High Availability HADOOP SECURITY * Why Hadoop Security Is Important * Hadoop?s Security System Concepts * What Kerberos Is and How it Works * Securing a Hadoop Cluster with Kerberos MANAGING AND SCHEDULING JOBS * Managing Running Jobs * Scheduling Hadoop Jobs * Configuring the FairScheduler * Impala Query Scheduling CLUSTER MAINTAINENCE * Checking HDFS Status * Copying Data Between Clusters * Adding and Removing Cluster Nodes * Rebalancing the Cluster * Cluster Upgrading CLUSTER MONITORING & TROUBLESHOOTING * General System Monitoring * Monitoring Hadoop Clusters * Common Troubleshooting Hadoop Clusters * Common Misconfigurations ADDITIONAL COURSE DETAILS: Nexus Humans Cloudera Administrator Training for Apache Hadoop training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Cloudera Administrator Training for Apache Hadoop course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 1 Days 6 CPD hours This course is intended for The audience for this course is individuals who want to learn the fundamentals of database concepts in a cloud environment, get basic skilling in cloud data services, and build their foundational knowledge of cloud data services within Microsoft Azure. Overview Describe core data concepts Identify considerations for relational data on Azure Describe considerations for working with non-relational data on Azure Describe an analytics workload on Azure In this course, students will gain foundational knowledge of core data concepts and related Microsoft Azure data services. Students will learn about core data concepts such as relational, non-relational, big data, and analytics, and build their foundational knowledge of cloud data services within Microsoft Azure. Students will explore fundamental relational data concepts and relational database services in Azure. They will explore Azure storage for non-relational data and the fundamentals of Azure Cosmos DB. Students will learn about large-scale data warehousing, real-time analytics, and data visualization. 1 - EXPLORE CORE DATA CONCEPTS * Identify data formats * Explore file storage * Explore databases * Explore transactional data processing * Explore analytical data processing 2 - EXPLORE DATA ROLES AND SERVICES * Explore job roles in the world of data * Identify data services 3 - EXPLORE FUNDAMENTAL RELATIONAL DATA CONCEPTS * Understand relational data * Understand normalization * Explore SQL * Describe database objects 4 - EXPLORE RELATIONAL DATABASE SERVICES IN AZURE * Describe Azure SQL services and capabilities * Describe Azure services for open-source databases 5 - EXPLORE AZURE STORAGE FOR NON-RELATIONAL DATA * Explore Azure blob storage * Explore Azure DataLake Storage Gen2 * Explore Azure Files * Explore Azure Tables 6 - EXPLORE FUNDAMENTALS OF AZURE COSMOS DB * Describe Azure Cosmos DB * Identify Azure Cosmos DB APIs 7 - EXPLORE FUNDAMENTALS OF LARGE-SCALE DATA WAREHOUSING * Describe data warehousing architecture * Explore data ingestion pipelines * Explore analytical data stores 8 - EXPLORE FUNDAMENTALS OF REAL-TIME ANALYTICS * Understand batch and stream processing * Explore common elements of stream processing architecture * Explore Azure Stream Analytics * Explore Apache Spark on Microsoft Azure 9 - EXPLORE FUNDAMENTALS OF DATA VISUALIZATION * Describe Power BI tools and workflow * Describe core concepts of data modeling * Describe considerations for data visualization

Duration 5 Days 30 CPD hours This course is intended for This intermediate and beyond level course is geared for experienced technical professionals in various roles, such as developers, data analysts, data engineers, software engineers, and machine learning engineers who want to leverage Scala and Spark to tackle complex data challenges and develop scalable, high-performance applications across diverse domains. Practical programming experience is required to participate in the hands-on labs. Overview Working in a hands-on learning environment led by our expert instructor you'll: Develop a basic understanding of Scala and Apache Spark fundamentals, enabling you to confidently create scalable and high-performance applications. Learn how to process large datasets efficiently, helping you handle complex data challenges and make data-driven decisions. Gain hands-on experience with real-time data streaming, allowing you to manage and analyze data as it flows into your applications. Acquire practical knowledge of machine learning algorithms using Spark MLlib, empowering you to create intelligent applications and uncover hidden insights. Master graph processing with GraphX, enabling you to analyze and visualize complex relationships in your data. Discover generative AI technologies using GPT with Spark and Scala, opening up new possibilities for automating content generation and enhancing data analysis. Embark on a journey to master the world of big data with our immersive course on Scala and Spark! Mastering Scala with Apache Spark for the Modern Data Enterprise is a five day hands on course designed to provide you with the essential skills and tools to tackle complex data projects using Scala programming language and Apache Spark, a high-performance data processing engine. Mastering these technologies will enable you to perform a wide range of tasks, from data wrangling and analytics to machine learning and artificial intelligence, across various industries and applications.Guided by our expert instructor, you?ll explore the fundamentals of Scala programming and Apache Spark while gaining valuable hands-on experience with Spark programming, RDDs, DataFrames, Spark SQL, and data sources. You?ll also explore Spark Streaming, performance optimization techniques, and the integration of popular external libraries, tools, and cloud platforms like AWS, Azure, and GCP. Machine learning enthusiasts will delve into Spark MLlib, covering basics of machine learning algorithms, data preparation, feature extraction, and various techniques such as regression, classification, clustering, and recommendation systems. INTRODUCTION TO SCALA * Brief history and motivation * Differences between Scala and Java * Basic Scala syntax and constructs * Scala's functional programming features INTRODUCTION TO APACHE SPARK * Overview and history * Spark components and architecture * Spark ecosystem * Comparing Spark with other big data frameworks BASICS OF SPARK PROGRAMMING SPARKCONTEXT AND SPARKSESSION * Resilient Distributed Datasets (RDDs) * Transformations and Actions * Working with DataFrames SPARK SQL AND DATA SOURCES * Spark SQL library and its advantages * Structured and semi-structured data sources * Reading and writing data in various formats (CSV, JSON, Parquet, Avro, etc.) * Data manipulation using SQL queries BASIC RDD OPERATIONS * Creating and manipulating RDDs * Common transformations and actions on RDDs * Working with key-value data BASIC DATAFRAME AND DATASET OPERATIONS * Creating and manipulating DataFrames and Datasets * Column operations and functions * Filtering, sorting, and aggregating data INTRODUCTION TO SPARK STREAMING * Overview of Spark Streaming * Discretized Stream (DStream) operations * Windowed operations and stateful processing PERFORMANCE OPTIMIZATION BASICS * Best practices for efficient Spark code * Broadcast variables and accumulators * Monitoring Spark applications INTEGRATING EXTERNAL LIBRARIES AND TOOLS, SPARK STREAMING * Using popular external libraries, such as Hadoop and HBase * Integrating with cloud platforms: AWS, Azure, GCP * Connecting to data storage systems: HDFS, S3, Cassandra, etc. INTRODUCTION TO MACHINE LEARNING BASICS * Overview of machine learning * Supervised and unsupervised learning * Common algorithms and use cases INTRODUCTION TO SPARK MLLIB * Overview of Spark MLlib * MLlib's algorithms and utilities * Data preparation and feature extraction LINEAR REGRESSION AND CLASSIFICATION * Linear regression algorithm * Logistic regression for classification * Model evaluation and performance metrics CLUSTERING ALGORITHMS * Overview of clustering algorithms * K-means clustering * Model evaluation and performance metrics COLLABORATIVE FILTERING AND RECOMMENDATION SYSTEMS * Overview of recommendation systems * Collaborative filtering techniques * Implementing recommendations with Spark MLlib INTRODUCTION TO GRAPH PROCESSING * Overview of graph processing * Use cases and applications of graph processing * Graph representations and operations * Introduction to Spark GraphX * Overview of GraphX * Creating and transforming graphs * Graph algorithms in GraphX BIG DATA INNOVATION! USING GPT AND GENERATIVE AI TECHNOLOGIES WITH SPARK AND SCALA * Overview of generative AI technologies * Integrating GPT with Spark and Scala * Practical applications and use cases Bonus Topics / Time Permitting INTRODUCTION TO SPARK NLP * Overview of Spark NLP Preprocessing text data * Text classification and sentiment analysis PUTTING IT ALL TOGETHER * Work on a capstone project that integrates multiple aspects of the course, including data processing, machine learning, graph processing, and generative AI technologies.

UNIX NETWORKING TRAINING COURSE DESCRIPTION A course covering the complete range of standard UNIX networking products from the basic TCP/IP configuration through DNS, NIS, NFS and Samba. Hands-on exercises follow most theory sessions. WHAT WILL YOU LEARN * Install and configure fundamental network services. * Describe TCP/IP, Apache, DNS, NIS, NIS+, NFS, Samba and sendmail. * Configure and administrate TCP/IP. * Install and administrate a DNS server. * Configure and administrate a NIS+ network. * Administrate NFS. * Setup a sendmail server. UNIX NETWORKING TRAINING COURSE DETAILS * Who will benefit: System Administrators. Network Administrators. * Prerequisites: Linux engineer certification 1 (LPIC-2) * Duration 5 days UNIX NETWORKING TRAINING COURSE CONTENTS * Organizing Email Services The UNIX Mail System, Mail Transfer Agent, Mail Delivery Agent, Mail User Agent, Email Protocols, SMTP, POP, IMAP, Using Email Servers, Sendmail, Postfix, Local Email Delivery, Procmail Basics, Sieve, Remote Email Delivery, Courier, Dovecot. * DNS DNS and BIND, Configuring a DNS Server, Starting, Stopping, and Reloading BIND, Configuring BIND Logging, Creating and Maintaining DNS Zones, BIND Zone Files, Managing BIND Zones, Securing a DNS Server, ailing BIND, DNSSEC, TSIG, Employing DANE. * Offering Web Services Web Servers, HTTP, The Apache Web Server, Installing and configuring Apache, Hosting Dynamic Web Applications, Secure Web Servers, Proxy Servers, Installing and configuring Squid, Configuring Clients, Nginx Server, Installing Nginx, Configuring Nginx. * Sharing Files Samba, Configuring Samba, Troubleshooting Samba, NFS, Configuring NFS, Securing NFS, Troubleshooting NFS, FTP Servers, Configuring vsftpd, Configuring Pure-FTPd. * Managing Network Clients Assigning Network Addresses, DHCP, UNIX DHCP Software, Installing and configuring a DHCP Server and clients, Authentication Service, PAM Basics, Configuring PAM, PAM Application Files, Network Directories, LDAP Basics, OpenLDAP Server, LDAP Clients. * Setting Up System Security Server Network Security, Port Scanning, Intrusion Detection Systems, External Network Security, iptables, Routing in UNIX, Connecting Securely to a Server, OpenSSH, OpenVPN, Security Resources, US-CERT, SANS Institute, Bugtraq.