28182 Courses delivered Online

Duration 3 Days 18 CPD hours This course is intended for Data Analysts, Business Analysts, Business Intelligence professionals Cloud Data Engineers who will be partnering with Data Analysts to build scalable data solutions on Google Cloud Platform Overview This course teaches students the following skills: Derive insights from data using the analysis and visualization tools on Google Cloud Platform Interactively query datasets using Google BigQuery Load, clean, and transform data at scale Visualize data using Google Data Studio and other third-party platforms Distinguish between exploratory and explanatory analytics and when to use each approach Explore new datasets and uncover hidden insights quickly and effectively Optimizing data models and queries for price and performance Want to know how to query and process petabytes of data in seconds? Curious about data analysis that scales automatically as your data grows? Welcome to the Data Insights course! This four-course accelerated online specialization teaches course participants how to derive insights through data analysis and visualization using the Google Cloud Platform. The courses feature interactive scenarios and hands-on labs where participants explore, mine, load, visualize, and extract insights from diverse Google BigQuery datasets. The courses also cover data loading, querying, schema modeling, optimizing performance, query pricing, and data visualization. This specialization is intended for the following participants: Data Analysts, Business Analysts, Business Intelligence professionals Cloud Data Engineers who will be partnering with Data Analysts to build scalable data solutions on Google Cloud Platform To get the most out of this specialization, we recommend participants have some proficiency with ANSI SQL. Introduction to Data on the Google Cloud Platform Highlight Analytics Challenges Faced by Data Analysts Compare Big Data On-Premises vs on the Cloud Learn from Real-World Use Cases of Companies Transformed through Analytics on the Cloud Navigate Google Cloud Platform Project Basics Lab: Getting started with Google Cloud Platform Big Data Tools Overview Walkthrough Data Analyst Tasks, Challenges, and Introduce Google Cloud Platform Data Tools Demo: Analyze 10 Billion Records with Google BigQuery Explore 9 Fundamental Google BigQuery Features Compare GCP Tools for Analysts, Data Scientists, and Data Engineers Lab: Exploring Datasets with Google BigQuery Exploring your Data with SQL Compare Common Data Exploration Techniques Learn How to Code High Quality Standard SQL Explore Google BigQuery Public Datasets Visualization Preview: Google Data Studio Lab: Troubleshoot Common SQL Errors Google BigQuery Pricing Walkthrough of a BigQuery Job Calculate BigQuery Pricing: Storage, Querying, and Streaming Costs Optimize Queries for Cost Lab: Calculate Google BigQuery Pricing Cleaning and Transforming your Data Examine the 5 Principles of Dataset Integrity Characterize Dataset Shape and Skew Clean and Transform Data using SQL Clean and Transform Data using a new UI: Introducing Cloud Dataprep Lab: Explore and Shape Data with Cloud Dataprep Storing and Exporting Data Compare Permanent vs Temporary Tables Save and Export Query Results Performance Preview: Query Cache Lab: Creating new Permanent Tables Ingesting New Datasets into Google BigQuery Query from External Data Sources Avoid Data Ingesting Pitfalls Ingest New Data into Permanent Tables Discuss Streaming Inserts Lab: Ingesting and Querying New Datasets Data Visualization Overview of Data Visualization Principles Exploratory vs Explanatory Analysis Approaches Demo: Google Data Studio UI Connect Google Data Studio to Google BigQuery Lab: Exploring a Dataset in Google Data Studio Joining and Merging Datasets Merge Historical Data Tables with UNION Introduce Table Wildcards for Easy Merges Review Data Schemas: Linking Data Across Multiple Tables Walkthrough JOIN Examples and Pitfalls Lab: Join and Union Data from Multiple Tables Advanced Functions and Clauses Review SQL Case Statements Introduce Analytical Window Functions Safeguard Data with One-Way Field Encryption Discuss Effective Sub-query and CTE design Compare SQL and Javascript UDFs Lab: Deriving Insights with Advanced SQL Functions Schema Design and Nested Data Structures Compare Google BigQuery vs Traditional RDBMS Data Architecture Normalization vs Denormalization: Performance Tradeoffs Schema Review: The Good, The Bad, and The Ugly Arrays and Nested Data in Google BigQuery Lab: Querying Nested and Repeated Data More Visualization with Google Data Studio Create Case Statements and Calculated Fields Avoid Performance Pitfalls with Cache considerations Share Dashboards and Discuss Data Access considerations Optimizing for Performance Avoid Google BigQuery Performance Pitfalls Prevent Hotspots in your Data Diagnose Performance Issues with the Query Explanation map Lab: Optimizing and Troubleshooting Query Performance Advanced Insights Introducing Cloud Datalab Cloud Datalab Notebooks and Cells Benefits of Cloud Datalab Data Access Compare IAM and BigQuery Dataset Roles Avoid Access Pitfalls Review Members, Roles, Organizations, Account Administration, and Service Accounts

Duration 5 Days 30 CPD hours This course is intended for The primary audience for this course is as follows: • This course is intended primarily for network administrators, network engineers, network managers and systems engineers who would like to implement BGP. The secondary audience for this course is as follows: • This course is intended for network designers and project managers. The course is also recommended to all individuals preparing for BGP exam. Overview After completing this course the student should be able to: - Describe how to configure, monitor, and troubleshoot basic BGP to enable interdomain routing in a network scenario with multiple domains - Describe how to use BGP policy controls to influence the BGP route selection process in a network scenario In which you must support connections to multiple ISPs - Describe how to use BGP attributes to influence the route selection process in a network scenario where you must support multiple connections - Describe how to successfully connect the customer network to the Internet in a network scenario in which multiple connections must be implemented - Describe how to configure the service provider network to behave as a transit AS in a typical implementation with multiple BGP connections to other autonomous systems - Enable route reflection as possible solution to BGP scaling issues in a typical service provider network with multiple BGP connections to other autonomous systems - Describe the available BGP tools and features to optimize the scalability of the BGP routing protocol in a typical BGP network This covers the theory of BGP, configuration of BGP on Cisco IOS© routers, detailed troubleshooting information, and hands-on exercises that provide learners with the skills that they need to configure and troubleshoot BGP networks in customer environments. BGP Overview Introducing BGP Understanding BGP Path Attributes Establishing BGP Sessions Processing BGP Routes Configuring Basic BGP Monitoring and Troubleshooting BGP Lab 1-1: Initial Lab Setup Lab 1-2: Configuring Basic BGP BGP Transit Autonomous Systems Working with a Transit AS Interacting with IBGP and EBGP in a Transit AS Forwarding Packets in a Transit AS Configuring a Transit AS Monitoring and Troubleshooting IBGP in a Transit AS Lab 2-1: Configuring a Transit AS Route Selection Using Policy Controls Using Multihomed BGP Networks Employing AS-Path Filters Filtering with Prefix-Lists Using Outbound Route Filtering Applying Route-Maps as BGP Filters Implementing Changes in BGP Policy Lab 3-1: Using Multihomed BGP Networks Lab 3-2: Employing AS-Path Filters Lab 3-3: Filtering with Prefix-Lists Lab 3-4: Implementing Changes in BGP Policy Route Selection Using Attributes Influencing BGP Route Selection with Weights Setting BGP Local Preference Using AS-Path Prepending Understanding BGP Multi-Exit Discriminators Addressing BGP Communities Lab 4-1: Influencing BGP Route Selection with Weights Lab 4-2: Setting BGP Local Preference Lab 4-3: Understanding BGP Multi-Exit Discriminators Lab 4-4: Addressing BGP Communities Customer-to-Provider Connectivity with BGP Understanding Customer-to-Provider Connectivity Requirements Implementing Customer Connectivity Using Static Routing Connecting a Multihomed Customer to a Single Service Provider Connecting a Multihomed Customer to Multiple Service Providers Scaling Service Provider Networks Scaling IGP and BGP in Service Provider Networks Introducing Route Reflectors Designing Networks with Route Reflectors Configuring and Monitoring Route Reflectors Introducing Confederations Configuring and Monitoring Confederations Lab 6-1: Introducing Route Reflectors Lab 6-2: Configuring and Monitoring Confederations Optimizing BGP Scalability Improving BGP Convergence Limiting the Number of Prefixes Received from a BGP Neighbor Implementing BGP Peer Groups Using BGP Route Dampening Lab 7-1: Limiting the Number of Prefixes Received from a BGP Neighbor Lab 7-2: Implementing BGP Peer Groups Lab 7-3: Using BGP Route Dampening Additional course details: Nexus Humans Cisco Configuring BGP on Cisco Routers v4.0 (BGP) 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 Cisco Configuring BGP on Cisco Routers v4.0 (BGP) 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 5 Days 30 CPD hours This course is intended for This course is for all Oracle Professionals. Specifically Database Administrators, Web Server Administrators, System Administrators, CIOs and other IT Management Professionals. Overview Upon successful completion of this course, students will be able to perform many of the day-to-day administration tasks required of an Oracle database administrator. This course introduces many of the powerful capabilities of the Oracle database. In this course, students will learn about day-to-day administration tasks. It will also address administration sub-specialties. Introduction: Managing the Database Instance The Database Management Tools EM Database Express EM Cloud Control SQL Developer Database Administrator Introduction: Database Architecture Review Database Instance Configurations Memory Structures Process Structures Storage Architecture Introduction: Starting & Stopping Databse Services Start & Stop the Database Listener ABOUT DATABASE STARTUP/SHUTDOWN SYSOPER SYSDBA DATABASE STATE & STAGES STARTUP WITH EM CLOUD CONTROL STARTUP WITH SQL*PLUS SHUTDOWN WITH EM CLOUD CONTROL SHUTDOWN WITH SQL*PLUS USING MS WINDOWS SERVICES Introduction: Oracle Network Environment Oracle Net Services Architecture ORACLE NET CONFIGURATION ASSISTANT ORACLE NET MANAGER USING EM CLOUD CONTROL ADVANCED NETWORK COMPRESSION TROUBLESHOOTING NETWORK PROBLEMS Introduction: Diagnostics & Oracle Support About Database Diagnostics Fault Diagnosability Infrastructure DATABASE INSTANCE HEALTH SNAPSHOT THE SUPPORT WORKBENCH PROACTIVE DATABASE HEALTH CHECKS PACKAGE DIAGNOSTIC DATA WORKING WITH THE KNOWLEDGE BASE Storage: Tablespace Management Starter Tablespaces CREATE TABLESPACE WITH EM CC CREATE TABLESPACE WITH SQL MANAGE TABLESPACES WITH EM CC MANAGE TABLESPACES WITH EM DE MANAGE TABLESPACES WITH SQL DROP TABLESPACE ALTER TABLESPACE Storage: Advanced Tablespace Management Managing Temporary Tablespaces TEMP TABLESPACE GROUPS WITH EM TEMP TABLESPACE GROUPS WITH SQL DEFAULT PERMANENT TABLESPACES BIGFILE TABLESPACES MANAGING THE SYSAUX TABLESPACE Storage: Data Files & Temp Files Management Manage Data Files with EM ACCESS METADATA WITH SQL MANAGE DATA FILES WITH SQL MANAGE TEMP FILES ORACLE-MANAGED FILES (OMF) Storage: UNDO Data & UNDO Tablespaces About UNDO Space Management GUARANTEE UNDO RETENTION MONITOR UNDO SPACE WITH SQL USE THE EM UNDO ADVISOR Security & Schemas: Security Overview & Database Privileges Database Security Principles DATABASE SYSTEM PRIVILEGES DATABASE OBJECT PRIVILEGES SUPER ADMINISTRATOR ROLES PRIVILEGE ANALYSIS Security & Schemas: User Security Create & Manage User Accounts MANAGE USERS WITH EM MANAGE USERS WITH SQL CREATE USER ALTER USER DROP USER GRANT & REVOKE PRIVILEGES RESOURCE LIMITS VIA PROFILES ALTER PROFILE DROP PROFILE PASSWORD MANAGEMENT VIA PROFILES ROLE-BASED SECURITY MANAGEMENT ALTER USER...DEFAULT ROLE SET ROLE DELEGATING PRIVILEGE AUTHORIZATION WITH ADMIN OPTION & System Privileges WITH GRANT OPTION & Object Privileges PRINCIPLE OF LEAST PRIVILEGE CHECKLIST Security & Schemas: Database Auditing Auditing Database Activity Traditional Auditing Unified Auditing Create Audit Policy Security & Schemas: SQL Loader Loader Concepts Loader From the Command Line control File Options Load Methods Loader Express Mode Loader From EM Security & Schemas: Export & Import Manage Directory Objects The Data Pump Architecture Data Pump Export Data Pump Import Data Pump Dictionary Views Using the EM CC Interface Performance & Availability: Managing Performance & SQL Tuning Management Advisory Framework Performance Monitoring & AWR The SQL Tuning Advisor Monitoring Exceptions with Metrics Performance & Availability: Data Concurrency About System & User Locks Monitor & Manage User Locks Moitor Locks with Data Dictionary Manage Locks with EM Performance & Availability: Backup & Recovery Concepts Backup & Recovery Structures Managing REDO Data Configuring for Recoverability Instance Recovery Recoverability Checklist Additional course details: Nexus Humans Oracle 12c Administration II 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 Oracle 12c Administration II 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 3 Days 18 CPD hours This course is intended for This hands-on course is geared for experienced DBAs already working with Oracle. Overview This course combines expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises. Working in a hands-on learning environment led by our expert facilitator, you'll learn how to: Implement backup and recovery settings and perform backup operations to the media of your choice. Move data between databases and files Use Oracle Database recovery processes to recover from media and other failures. Diagnose and repair data failures Use flashback technologies and data duplication to complement backup and recovery procedures Secure the availability of their database using backup and recovery strategies Geared for DBAs and other technical support staff, Oracle Database 19c Backup and Recovery is a hands-on course that allows you to develop appropriate backup and recovery procedures to address their business model and requirements. Throughout the course you?ll explore how to implement basic backup and recovery procedures, move data between databases and files, and employ basic monitoring procedures. You?ll also learn how to secure the availability of a database by using appropriate backup and recovery strategies, how to how to perform backup and recovery operations using RMAN, and how to use Flashback features to recover from human error. This course combines expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises. Working in a hands-on learning environment led by our expert facilitator, you?ll learn how to:Implement backup and recovery settings and perform backup operations to the media of your choice.Move data between databases and filesUse Oracle Database recovery processes to recover from media and other failures.Diagnose and repair data failuresUse flashback technologies and data duplication to complement backup and recovery proceduresSecure the availability of their database using backup and recovery strategies Backup Methods User Managed Backups Oracle Managed Backups Types of Failures Types of Recoveries Recovery Configuration Configuring the Database for Archivelog Configuring the Database for No-Archivelog Configuring the Flash Recovery Area Configuring RMAN RMAN Default Settings Command Line Enterprise Manager RMAN Backups Full RMAN Backup Compressed Backups Uncompressed Backups Partial RMAN Backup Incremental Backups Change Tracking File Managing Backups Backup Reports Backup Maintenance Backup Catalog Backup Crosscheck RMAN Complete Recovery RMAN Complete Recovery Database Recovery Tablespace Recovery Datafile Recovery RMAN In-Complete Recovery Time Based Recovery Sequence Based Recovery SCN Based Recovery Non-Database File Recovery Spfile Recovery Controlfile Recovery Incremental Recovery Flash Recovery Area for a Fast Recovery User Managed Backup Configuring User Managed Backups Perform a User Managed Backup User Managed Recovery User Managed Complete Recovery User Managed Incomplete Recovery Configuring Flashback Flashback Query Flashback Drop Flashback Database Performing Flashback Recoveries Flashback Query Flashback Drop Flashback Transaction Query Flashback Versions Query Performing Flashback Database Determining the FRA Size FRA Retention Performing a Flashback Database RMAN Duplicate Command Setting up for a Duplicate Database Creating the Duplicate spfiles Performing the Duplicate Command. RMAN Recovery Catalog Configuring for the Recovery Catalog Creating the Recovery Catalog Backups with the Recovery Catalog Registering the Database with the Recovery Catalog Performing Backups with the Recovery Catalog Recoveries with the Recovery Catalog Identifying Type of Recoveries with the Recovery Catalog Performing Recoveries with the Recovery Catalog Recovery Catalog Maintenance Registering Additional Databases with the Recovery Catalog Cataloging Additional Backups with the Recovery Catalog Recovery Catalog Scripts DataPump Configuring Datapump DataPump Exports DataPump Imports Tuning RMAN RMAN Sessions RMAN Channels RMAN Job Progress Additional course details: Nexus Humans Oracle 19c Database Backup and Recovery (TTOR21619) 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 Oracle 19c Database Backup and Recovery (TTOR21619) 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 5 Days 30 CPD hours This course is intended for Network designers Network administrators Network engineers Systems engineers Data center engineers Consulting systems engineers Technical solutions architects Field engineers Cisco integrators and partners Server administrator Network manager Overview After taking this course, you should be able to: Implement routing and switching protocols in Data Center environment Implement overlay networks in data center Introduce high-level Cisco Application Centric Infrastructure (Cisco ACI™) concepts and Cisco Virtual Machine manager (VMM) domain integration Describe Cisco Cloud Service and deployment models Implement Fibre Channel fabric Implement Fibre Channel over Ethernet (FCoE) unified fabric Implement security features in data center Implement software management and infrastructure monitoring Implement Cisco UCS Fabric Interconnect and Server abstraction Implement SAN connectivity for Cisco Unified Computing System™ (Cisco UCS) Describe Cisco HyperFlex™ infrastructure concepts and benefits Implement Cisco automation and scripting tools in data center Evaluate automation and orchestration technologies This course helps you prepare for the CiscoÿCCNPÿData Center and CCIEÿData Center certifications. In this course, you will master the skills and technologies you need to implement data center compute, LAN and SAN infrastructure. You will also learn the essentials of automation and security in data centers. You will gain hands-on experience deploying, securing, operating, and maintaining Cisco data center. Implementing Data Center Switching Protocols* Spanning Tree Protocol Port Channels Overview Implementing First-Hop Redundancy Protocols* Hot Standby Router Protocol (HSRP) Overview Virtual Router Redundancy Protocol (VRRP) Overview Implementing Routing in Data Center* Open Shortest Path First (OSPF) v2 and Open Settlement Protocol (OSP) v3 Border Gateway Protocol Implementing Multicast in Data Center* IP Multicast in Data Center Networks Internet Group Management Protocol (IGMP) and Multicast Listener Discovery (MLD) Implementing Data Center Overlay Protocols Cisco Overlay Transport Virtualization Virtual Extensible LAN Implementing Network Infrastructure Security* User Accounts and Role Based Access Control (RBAC) Authentication, Authorization, and Accounting (AAA) and SSH on Cisco NX-OS Describing Cisco Application-Centric Infrastructure Cisco ACI Overview, Initialization, and Discovery Cisco ACI Management Describing Cisco ACI Building Blocks and VMM Domain Integration Tenant-Based Components Cisco ACI Endpoints and Endpoint Groups (EPG) Describing Packet Flow in Data Center Network* Data Center Traffic Flows Packet Flow in Cisco Nexus Switches Describing Cisco Cloud Service and Deployment Models Cloud Architectures Cloud Deployment Models Describing Data Center Network Infrastructure Management, Maintenance, and Operations* Time Synchronization Network Configuration Management Explaining Cisco Network Assurance Concepts* Need for Network Assurance Cisco Streaming Telemetry Overview Implementing Fibre Channel Fabric Fibre Channel Basics Virtual Storage Area Network (VSAN) Overview Implementing Storage Infrastructure Services Distributed Device Aliases Zoning Implementing FCoE Unified Fabric Fibre Channel over Ethernet Describing FCoE Implementing Storage Infrastructure Security* User Accounts and RBAC Authentication, Authorization, and Accounting Describing Data Center Storage Infrastructure Maintenance and Operations* Time Synchronization Software Installation and Upgrade Describing Cisco UCS Server Form Factors* Cisco UCS B-Series Blade Servers Cisco UCS C-Series Rack Servers Implementing Cisco Unified Computing Network Connectivity Cisco UCS Fabric Interconnect Cisco UCS B-Series Connectivity Implementing Cisco Unified Computing Server Abstraction Identity Abstraction Service Profile Templates Implementing Cisco Unified Computing SAN Connectivity iSCSI Overview Fibre Channel Overview Implementing Unified Computing Security User Accounts and RBAC Options for Authentication Introducing Cisco HyperFlex Systems* Hyper converged and Integrated Systems Overview Cisco HyperFlex Solution Describing Data Center Unified Computing Management, Maintenance, and Operations* Compute Configuration Management Software Updates Implementing Cisco Data Center Automation and Scripting Tools* Cisco NX-OS Additional course details: Nexus Humans Cisco Implementing and Operating Cisco Data Center Core Technologies (DCCOR) v1.2 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 Cisco Implementing and Operating Cisco Data Center Core Technologies (DCCOR) v1.2 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 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.

Duration 4 Days 24 CPD hours This course is intended for The primary audience for this course is as follows: Phone Network Administrators Phone Network Engineers Data System Administrators Entry-level Network Engineers Channel Partners/Resellers, Customers, Employees Overview Describe the Cisco Unified Communications Manager network, service, and features Understand the importance of and configuration of redundancy and high availability in the enterprise network Describe user configuration and the user web interface Explain basic phone options and the use of BAT Explain the route plan and on-net/off-net calling Describe the various media resources, including conferencing and MOH Describe the basic phone features and use of hunt groups Administering Cisco Unified Communications Manager (ACUCM) v12.0 is a 3-day training program that provides system administrators and networking professionals with an understanding of the Cisco Unified Communications Manager System. The Cisco IT training course teaches the concepts of IP telephony based in system administration, including its function, features, and configuration. This is an entry-level IP telephony course that begins with the basic concepts of IP telephony and very quickly moves the learner forward into an understanding of system concepts: clustering, creation of phones and users, route plans, digit manipulation, media resources, and phone features, which are all important to supporting IP telephony in the enterprise network. The course focuses on Cisco Unified Communications Manager version v12.x.The course is geared to individuals that will be using and managing the system and performing administration for Level 1 and Level 2 support. Level 1 support is geared toward supporting phone users and making moves, adds, and changes to the desktop phone environment. Level 2 support is oriented to supporting changes in the organization, such as opening new office locations or relocating departments. The Cisco training course does not cover issues of initial deployment, new cluster deployment or international deployments. Also, the course does not cover issues with the underlying network that involves routers, switches, or Cisco IOS software configuration. Exploring IP Telephone Traditional Voice versus IP Telephony Clustering Overview Intracluster Communications Cisco Unified Communications Manager Clusters Clustering Options Platform Requirements Describing Deployment Models Single-Site Deployment Centralized Call-Processing Deployment Distributed Call-Processing Deployment Distributed Single-Cluster Call-Processing Deployment Hybrid Call-Processing Deployment New Advanced Multicluster Options Understanding Advanced Multisite Features Need for CAC Deploying AAR Survivable Remote Site Telephony SRST Failover Logging in to Cisco Unified Communications Manager Logging In to Cisco Unified CM Administration and Cisco Unified Serviceability Logging In to Cisco Unified Operating System Administration and the DRS Navigation Menu Command-Line Interface Examining Basic Server Configuration Server Configuration?Eliminating DNS Reliance Configuring Enterprise Parameters Describing Multilevel Administration Configuring Multilevel Administration Creating End Users Creating Roles Creating User Groups Assigning Users to User Groups Configuring DRS Backup and Restore Procedures DRS Backup Procedures DRS Restore Procedures Understanding User Configuration Understanding User Management Configuring Users Using the User Web Pages Understanding the User Web Pages Using the User Web Pages Configuring System Parameter Cisco Unified CM Configuration Cisco Unified Communications Manager Group Configuration Phone NTP Configuration Date/Time Group Codecs and Regions Location Configuration Device Pool Configuration DHCP Service Configuration Device Defaults Configuration Clusterwide Parameters Licensing Supporting Cisco Unified IP Phones Cisco Unified IP Phones Overview Specialized Cisco Unified IP 7900 Series Phones Phone Button Templates Softkey Templates Exploring Phone Registration and IP Phone Communications Cisco Unified IP Phone Registration Cisco Unified IP Phone Configuration Utilizing the Bulk Administration Tool (BAT) Overview of Cisco Unified Communications Manager BAT Cisco Unified Communications Manager TAPS Implementing Dial Plan Connectivity Organizational Dial Plan Trunks Gateways Creating Route Plans Dial Plan Overview Route Pattern Overview Digit Collection Call Routing Configuring Transition Patterns and Route Filters Translation Patterns The 9.@ Pattern Route Filters Implementing Digit Manipulation Discard Digits Instruction Transformation Masks Route Plan Report Defining Class of Control Overview of Class of Control Partitions CSS Configuration PLAR Application Using Class of Control Features Call Restriction Time of Day Routing Traditional vs. Line/Device Approach Defining Media Resources Overview of Media Resources Conference Bridge Media Termination Points Transcoder Music on Hold Annunciator Exploring Media Resource Management MRG Management Configuring MRGs Configuring MRGLs Describing Basic Features Call Park Call Pickup Cisco Call Back Shared Lines with Barge and Privacy Exploring Hunt Groups Hunt Group Overview Line Group Configuration Hunt List Configuration Hunt Pilot Configuration Final Forwarding Describing Phone Services Cisco IP Phone Services Cisco Phone Services Configuration

Duration 3 Days 18 CPD hours This course is intended for This course is appropriate for advanced users, system administrators and web site administrators who want to use Python to support their server installations, as well as anyone else who wants to automate or simplify common tasks with the use of Python scripts. Students can apply the course skills to use Python in basic web development projects or automate or simplify common tasks with the use of Python scripts. Overview This skills-focused course is about 50% hands-on lab to lecture ratio, combining expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises. Working in a hands-on learning environment led by our expert instructor, you'll learn how to: Create working Python scripts following best practices Use python data types appropriately Read and write files with both text and binary data Search and replace text with regular expressions Work with with the standard library and its work-saving modules Create 'real-world', professional Python applications Know when to use collections such as lists, dictionaries, and sets Work with Pythonic features such as comprehensions and iterators Write robust code using exception handling Introduction to Python Programming Basics is a hands-on Python programming course that teaches you the key skills you?ll need to get started with programming in Python to a solid foundational level. The start of the course will lead you through writing and running basic Python scripts, and then guide you through how to use more advanced features such as file operations, regular expressions, working with binary data, and using the extensive functionality of Python modules. Extra emphasis is placed on features unique to Python, such as tuples, array slices, and output formatting. This course provides you with an excellent kick start for users new to Python and scripting, enabling you to quickly use basic Python skills on the job in a variety of ways. You?ll be able use Python in basic web development projects, or use it to automate or simplify common tasks with the use of Python scripts. The course also serves as a solid primer course / foundation for continued Python study in support for next level web development with Python, using Python in DevOps, Python for data science / machine learning or Python for systems admin or networking support. Python Quick View What is Python? Python timeline Advantages/disadvantages Installing Python Getting help The Python Environment Starting Python Using the interpreter Running a Python script Editors and IDEs Getting Started with Python Using variables Builtin functions String data Numberic data Converting types Console input/output Command line parameters Flow Control About flow control The if statement Relational and Boolean operators while loops Exiting from loops Array Types About array types Lists and list methods Tuples Indexing and slicing Iterating through a sequence Sequence functions, keywords, and operators List comprehensions and generators Working with Files File overview Opening a text file Reading a text file Writing to a text file Dictionaries and Sets About dictionaries Creating dictionaries Iterating through a dictionary About sets Creating sets Working with sets Functions Defining functions Returning values Parameters and arguments Variable scope Sorting The sorted() function Custom sort keys Lambda functions Sorting in reverse Using min() and max() Errors and Exception Handling Exceptions Using try/catch/else/finally Handling multiple exceptions Ignoring exceptions Modules and Packages Creating Modules The import statement Module search path Using packages Function and module aliases Getting Started with Object Oriented Programming and Classes About object-oriented programming Defining classes Constructors Understanding self Properties Instance Methods and data Class methods and data Inheritance Additional course details: Nexus Humans Introduction to Python Programming Basics (TTPS4800) 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 Introduction to Python Programming Basics (TTPS4800) 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 5 Days 30 CPD hours This course is intended for System administrators and system integrators responsible for designing, implementing, and managing VMware Aria Automation Overview By the end of the course, you should be able to meet the following objectives: Describe the VMware Aria Automation architecture and use cases in cloud environments Describe the key services of VMware Cloud Automation Services™ Manage VMware Aria Automation entities on VMware and third-party virtual and cloud infrastructures Install VMware Aria Automation with VMware Aria Suite Lifecycle Configure and manage cloud accounts, projects, flavor mappings, image mappings, network profiles, storage profiles, volumes, tags, and services Create, modify, manage, and deploy VMware Aria Automation Templates Customize services and virtual machines with cloudConfig and cloudbase-init Configure and manage VMware Aria Automation Consumption Configure and manage ABX actions, custom properties, event broker subscriptions, and VMware Aria Automation Orchestrator workflows Connect to a Kubernetes cluster and manage namespaces Use VMware Aria Automation Config to configure and deploy systems Use logs and CLI commands to monitor and troubleshoot VMware Aria Automation During this five-day course, you focus on installing, configuring, and managing VMware Aria Automation 8.10? on-premises systems. You learn how it can be used to automate the delivery of virtual machines, applications, and personalized IT services across different data centers and hybrid cloud environments. The course covers how VMware Aria Automation Consumption? can aggregate content in native formats from multiple clouds and platforms into a common catalog.This course also covers interfacing VMware Aria Automation with other systems using VMware Aria Orchestrator and how to use VMware Aria Automation to manage Kubernetes systems and leverage other systems. In this course, you will use VMware Aria Automation Config? as a configuration management tool. Course Introduction Introductions and course logistics Course objectives VMware Aria Automation Overview and Architecture Describe the purpose and functionality of VMware Aria Automation Identify the key services offered by VMware Aria Automation Describe the VMware Aria Automation architecture Describe the use of VMware Workspace ONE Access? Describe the relationship between Kubernetes clusters, container, and VMware Aria Automation services Installing VMware Aria Automation List the different VMware Aria Automation deployment types Describe the purpose of Easy Installer Describe the VMware Aria Automation installation process Authentication and Authorization Identify the steps to integrating Workspace ONE© Access with Active Directory Describe the features of Workspace ONE Access Describe the user roles available in VMware Aria Automation Identify the key tasks performed by each user role Define custom roles Configure branding and multitenancy Basic Initial Configuration Create a basic configuration with a cloud account, cloud zone, project, flavor mapping, and image mapping VMware Aria Automation Templates Configure and deploy a basic VMware Aria Automation template Create a VMware Aria Automation template that can run on any cloud Use cloudConfig and cloudbase-init to run commands, create users, and install software Use YAML for inputs, variables, and conditional deployments Tags Configure tags Describe functions of tags Manage tags Storage Configuration Configure storage profiles Use tags and storage profiles Integrating NSX With VMware Aria Automation List the capabilities and use cases of VMware NSX© Describe the NSX architecture and components Integrate NSX with VMware Aria Automation List the supported network profiles in VMware Aria Automation Use the NSX components to design a multitier application with VMware Aria Automation Templates Identify the network and security options available in design canvas Create and manage on-demand networks and security groups Configure NSX Day 2 actions Integrating with Public Clouds Configure and use VMware Cloud Foundation? accounts Integrate VMware Cloud Director? account Configure and use an AWS cloud account Configure and use an Azure cloud account Configure and use a Google Cloud Platform cloud account Integrate VMware Cloud on AWS cloud account Using VMware Aria Automation Consumption Release a VMware Aria Automation template Define content source and content sharing Define VMware Aria Automation policy enforcement Use custom forms for catalog items VMware Aria Automation Extensibility Describe VMware Aria Automation extensibility Use event topics Create a subscription Call a VMware Aria Automation Orchestrator workflow Create ABX actions Using Kubernetes Clusters Introduction to Kubernetes Connect to an existing Kubernetes Cluster Create a VMware Aria Automation template with Kubernetes components Using VMware Aria Automation Config for Configuration Management Describe VMware Aria Automation Config Use VMware Aria Automation Config for software deployment Use VMware Aria Automation Config for configuration management Use VMware Aria Automation Config with event-driven orchestration VMware Aria Automation Troubleshooting and Integration Demonstrate how to monitor deployment history Demonstrate basic troubleshooting Execute CLI commands Explain how to collect logs Describe integration with VMware Aria Operations for Logs Describe integration with VMware Aria Operations

Duration 2 Days 12 CPD hours This course is intended for Audience: Data Scientists, Software Developers, IT Architects, and Technical Managers. Participants should have the general knowledge of statistics and programming Also familiar with Python Overview ? NumPy, pandas, Matplotlib, scikit-learn ? Python REPLs ? Jupyter Notebooks ? Data analytics life-cycle phases ? Data repairing and normalizing ? Data aggregation and grouping ? Data visualization ? Data science algorithms for supervised and unsupervised machine learning Covers theoretical and technical aspects of using Python in Applied Data Science projects and Data Logistics use cases. Python for Data Science ? Using Modules ? Listing Methods in a Module ? Creating Your Own Modules ? List Comprehension ? Dictionary Comprehension ? String Comprehension ? Python 2 vs Python 3 ? Sets (Python 3+) ? Python Idioms ? Python Data Science ?Ecosystem? ? NumPy ? NumPy Arrays ? NumPy Idioms ? pandas ? Data Wrangling with pandas' DataFrame ? SciPy ? Scikit-learn ? SciPy or scikit-learn? ? Matplotlib ? Python vs R ? Python on Apache Spark ? Python Dev Tools and REPLs ? Anaconda ? IPython ? Visual Studio Code ? Jupyter ? Jupyter Basic Commands ? Summary Applied Data Science ? What is Data Science? ? Data Science Ecosystem ? Data Mining vs. Data Science ? Business Analytics vs. Data Science ? Data Science, Machine Learning, AI? ? Who is a Data Scientist? ? Data Science Skill Sets Venn Diagram ? Data Scientists at Work ? Examples of Data Science Projects ? An Example of a Data Product ? Applied Data Science at Google ? Data Science Gotchas ? Summary Data Analytics Life-cycle Phases ? Big Data Analytics Pipeline ? Data Discovery Phase ? Data Harvesting Phase ? Data Priming Phase ? Data Logistics and Data Governance ? Exploratory Data Analysis ? Model Planning Phase ? Model Building Phase ? Communicating the Results ? Production Roll-out ? Summary Repairing and Normalizing Data ? Repairing and Normalizing Data ? Dealing with the Missing Data ? Sample Data Set ? Getting Info on Null Data ? Dropping a Column ? Interpolating Missing Data in pandas ? Replacing the Missing Values with the Mean Value ? Scaling (Normalizing) the Data ? Data Preprocessing with scikit-learn ? Scaling with the scale() Function ? The MinMaxScaler Object ? Summary Descriptive Statistics Computing Features in Python ? Descriptive Statistics ? Non-uniformity of a Probability Distribution ? Using NumPy for Calculating Descriptive Statistics Measures ? Finding Min and Max in NumPy ? Using pandas for Calculating Descriptive Statistics Measures ? Correlation ? Regression and Correlation ? Covariance ? Getting Pairwise Correlation and Covariance Measures ? Finding Min and Max in pandas DataFrame ? Summary Data Aggregation and Grouping ? Data Aggregation and Grouping ? Sample Data Set ? The pandas.core.groupby.SeriesGroupBy Object ? Grouping by Two or More Columns ? Emulating the SQL's WHERE Clause ? The Pivot Tables ? Cross-Tabulation ? Summary Data Visualization with matplotlib ? Data Visualization ? What is matplotlib? ? Getting Started with matplotlib ? The Plotting Window ? The Figure Options ? The matplotlib.pyplot.plot() Function ? The matplotlib.pyplot.bar() Function ? The matplotlib.pyplot.pie () Function ? Subplots ? Using the matplotlib.gridspec.GridSpec Object ? The matplotlib.pyplot.subplot() Function ? Hands-on Exercise ? Figures ? Saving Figures to File ? Visualization with pandas ? Working with matplotlib in Jupyter Notebooks ? Summary Data Science and ML Algorithms in scikit-learn ? Data Science, Machine Learning, AI? ? Types of Machine Learning ? Terminology: Features and Observations ? Continuous and Categorical Features (Variables) ? Terminology: Axis ? The scikit-learn Package ? scikit-learn Estimators ? Models, Estimators, and Predictors ? Common Distance Metrics ? The Euclidean Metric ? The LIBSVM format ? Scaling of the Features ? The Curse of Dimensionality ? Supervised vs Unsupervised Machine Learning ? Supervised Machine Learning Algorithms ? Unsupervised Machine Learning Algorithms ? Choose the Right Algorithm ? Life-cycles of Machine Learning Development ? Data Split for Training and Test Data Sets ? Data Splitting in scikit-learn ? Hands-on Exercise ? Classification Examples ? Classifying with k-Nearest Neighbors (SL) ? k-Nearest Neighbors Algorithm ? k-Nearest Neighbors Algorithm ? The Error Rate ? Hands-on Exercise ? Dimensionality Reduction ? The Advantages of Dimensionality Reduction ? Principal component analysis (PCA) ? Hands-on Exercise ? Data Blending ? Decision Trees (SL) ? Decision Tree Terminology ? Decision Tree Classification in Context of Information Theory ? Information Entropy Defined ? The Shannon Entropy Formula ? The Simplified Decision Tree Algorithm ? Using Decision Trees ? Random Forests ? SVM ? Naive Bayes Classifier (SL) ? Naive Bayesian Probabilistic Model in a Nutshell ? Bayes Formula ? Classification of Documents with Naive Bayes ? Unsupervised Learning Type: Clustering ? Clustering Examples ? k-Means Clustering (UL) ? k-Means Clustering in a Nutshell ? k-Means Characteristics ? Regression Analysis ? Simple Linear Regression Model ? Linear vs Non-Linear Regression ? Linear Regression Illustration ? Major Underlying Assumptions for Regression Analysis ? Least-Squares Method (LSM) ? Locally Weighted Linear Regression ? Regression Models in Excel ? Multiple Regression Analysis ? Logistic Regression ? Regression vs Classification ? Time-Series Analysis ? Decomposing Time-Series ? Summary Lab Exercises Lab 1 - Learning the Lab Environment Lab 2 - Using Jupyter Notebook Lab 3 - Repairing and Normalizing Data Lab 4 - Computing Descriptive Statistics Lab 5 - Data Grouping and Aggregation Lab 6 - Data Visualization with matplotlib Lab 7 - Data Splitting Lab 8 - k-Nearest Neighbors Algorithm Lab 9 - The k-means Algorithm Lab 10 - The Random Forest Algorithm