1701 Computing courses delivered Live Online

Duration 1 Days 6 CPD hours This course is intended for This course is intended for: A technical audience at an intermediate level Overview Using Amazon SageMaker, this course teaches you how to: Prepare a dataset for training. Train and evaluate a machine learning model. Automatically tune a machine learning model. Prepare a machine learning model for production. Think critically about machine learning model results In this course, learn how to solve a real-world use case with machine learning and produce actionable results using Amazon SageMaker. This course teaches you how to use Amazon SageMaker to cover the different stages of the typical data science process, from analyzing and visualizing a data set, to preparing the data and feature engineering, down to the practical aspects of model building, training, tuning and deployment. Day 1 Business problem: Churn prediction Load and display the dataset Assess features and determine which Amazon SageMaker algorithm to use Use Amazon Sagemaker to train, evaluate, and automatically tune the model Deploy the model Assess relative cost of errors Additional course details: Nexus Humans Practical Data Science with Amazon SageMaker 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 Practical Data Science with Amazon SageMaker 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 2 Days 12 CPD hours This course is intended for This intermediate course is for Business and Technical Specialist working with the Matching, Linking, and Search services of InfoSphere MDM Virtual module. Overview Understand how Matching and Linking work for both the Virtual Implementations of InfoSphere MDM Understand the MDM configuration project and database tables used by the PME Understand the PME Algorithms (Standardization, Bucketing and Comparison steps) and how to create and customize the algorithms using the workbench Understand how to analyze the Bucketing steps in an algorithm Understand how to generate weights for a given algorithm and how those weights are generated based on a sample database set Understand how to analyze the weights that are generated using the workbench Understand how to deploy the PME configuration for the Virtual implementations of InfoSphere MDM The InfoSphere MDM Virtual Module Algorithms V.11 course prepares students to work with and customize the algorithm configurations deployed to the InfoSphere MDM Probabilistic Matching Engine (PME) for Virtual MDM implementations. PME and Virtual Overview Virtual MDM Overview Terminology (Source, Entity, Member, Attributes) PME and Virtual MDM ( Algorithms, Weights, Comparison Scores, Thresholds) Virtual MDM Linkages and Tasks Virtual MDM Algorithms Standardization Bucketing Comparison Functions Virtual PME Data Model Algorithm configuration tables Member Derived Data Bucketing Data Bucket Analysis Analysis Overview Attribute Completeness Bucket Analysis Weights Weights Overview (Frequency-based weights, Edit Distance weights and Parameterize weights) The weight formula Running weight generation Analyzing weights Bulk Cross Match process Pair Manager Threshold calculations Additional course details: Nexus Humans ZZ880 IBM Virtual Module Algorithms for InfoSphere MDM V11 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 ZZ880 IBM Virtual Module Algorithms for InfoSphere MDM V11 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 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 3 Days 18 CPD hours This course is intended for This course is for information technology professionals, security professionals, network, system managers and administrators tasked with installing, configuring and maintaining Symantec Data Center Security: Server Advanced. Overview At the completion of the course, you will be able to: Describe the major components of Symantec Data Center Security: Server Advanced and how they communicate. Install the management server, console and agent. Define, manage and create assets, policies, events and configurations. Understand policy creation and editing in depth. course is an introduction to implementing and managing a Symantec Data Center Security: Server Advanced 6.0 deployment. Introduction Course Overview The Classroom Lab Environment Introduction to Security Risks and Risk Security Risks Security Risk Management Managing and Protecting Systems Corporate Security Policies and Security Assessments Host-Based Computer Security Issues SDCS:Server Advanced Overview SDCS: Server Advanced Component Overview Policy Types and Platforms Management Console Overview Agent User Interface Overview DEMO of Management Console Installation and Deployment Planning the Installation Deploying SDCS:SA for High Availability Scalability Installing the Management Server Installing the Management Console Installing a Windows Agent Installing a UNIX Agent LAB: Install Manager and Agents Configuring Assets Asset and Agent Overview Viewing Agents and Assets Managing Agents Managing Agents on Assets LAB: Create Asset Groups LAB: Examine Agent Interface Policy Overview Policies Defined Prevention Policy Overview Process Sets Resource Access Policy Options Detection Policy Overview IDS Capabilities Rules Collectors Policy Management Workspace User Interface on Agent Example Use Cases LAB: Paper Based Scenarios LAB: What type of security strategy should be used? Detailed Prevention Policies Policy Editor Policy Structure Global Policy Options Service Options Program Options Policy Processing Order Network Rules File Rules Registry Rules Process Sets Predefined Policies LAB: Deploy Strict policy LAB: Examine Functionality Advanced Prevention Profiling Applications Customizing Predefined Policies LAB: Modify Policy Previously Deployed LAB: Re-examine Functionality LAB: Preparing for Policy deployment LAB: Best Practice - Covering Basics LAB: Further Enhance Strict Policy LAB: Create Custom Process Set LAB :Secure an FTP Server LAB: Troubleshoot Policy/pset Assignment Using CLI Detection Policies Detection Policies Structure Collectors Rules Predefined Detection Policies Creating a Detection Policy Using the Template Policy LAB: Deploy Baseline Policy LAB: Create Custom Policy Event Management Events Defined Viewing Events Reports and Queries Overview Creating Queries and Reports Creating Alerts LAB: View Monitor Types and Search Events LAB: Create Real Time Monitor Agent Management and Troubleshooting Configurations Defined Creating and Editing Configurations Common Parameters Prevention Settings Detection Settings Analyzing Agent Log Files Diagnostic Policies Local Agent Tool ? sisipsconfig LAB: Create Custom Configurations LAB: Implement Bulk Logging LAB: Disable Prevention on Agent Using CLI LAB: Use Diagnostic Policy to Gather Logs LAB: Troubleshoot a Policy System Management Managing Users and Roles Server Security Viewing and Managing Server Settings Viewing and Managing Database Settings Viewing and Managing Tomcat Settings LAB: Create a New User LAB: View System Settings

Duration 3 Days 18 CPD hours This course is intended for Operators of Juniper Networks security solutions, including network engineers, administrators, support personnel, and resellers. Overview Identify high-level security challenges in today's networks. Identify products that are incorporated into the Juniper Connected Security solution. Explain the value of implementing security solutions. Explain how Juniper Connected Security solves the cyber security challenges of the future. Explain the SRX Series devices and the added capabilities that next-generation firewalls provide. Explain traffic flows through the SRX Series devices. List the different security objects and how to create them. Describe interface types and perform basic interface configuration tasks. Describe the initial configuration for an SRX Series device. Explain security zones. Describe screens and their use. Explain address objects. Describe services and their use. Describe the purpose for security policies on an SRX Series device. Describe zone-based policies. Describe global policies and their use. Explain unified security policies. Configure unified security policies with the J-Web user interface. Describe IDP signatures. Configure an IDP policy using predefined templates with the J-Web user interface. Describe the use and configuration of the integrated user firewall feature. Describe the UTM security services List the available UTM services on the SRX Series device. Configure UTM filtering on a security policy with the J-Web user interface. Explain Sky ATP's use in security. Describe how Sky ATP and SRX Series devices operate together in blocking threats. Describe NAT and why it is used. Explain source NAT and when to use it. Explain destination NAT and when to use it. Explain static NAT and its uses. Describe the operation and configuration the different types of NAT. Identify various types of VPNs. Describe IPsec VPNs and their functionality. Describe how IPsec VPNs are established. Describe IPsec traffic processing. Configure IPsec VPNs with the J-Web user interface. Describe and configure proxy IDs and traffic selectors with the J-Web user interface. Monitor IPsec VPNs with the J-Web user interface. Describe the J-Web monitoring features. Explain the J-Web reporting features. Describe the Sky Enterprise service and how it can save resources. Explain the functionality of Junos Space Security Director. This course is designed to provide students with the foundational knowledge required to work with SRX Series devices. This course will use the J-Web user interface to introduce students to the Junos operating system. Module 1: COURSE INTRODUCTION COURSE INTRODUCTION Module 2: Juniper Security Concept Security Challenges Security Design Overview Juniper Connected Security Module 3: Juniper Connected Security ? SRX Series Devices Connected Security Interfaces Initial Configuration LAB 1: Initial Configuration Module 4: Security Objects Security Zone Objects Security Screen Objects Security Address Objects Security Services Objects LAB 2: Creating Security Objects with J-Web Module 5: Security Policies Security Policy Overview Zone-Based Policies Global Security Policies Application Firewall with Unified Security Policies LAB 3: Creating Security Policies with J-Web Module 6: Security Services ? IDP and User Firewall IDP Security Services Integrated User Firewall LAB 4: Adding IDP and User Firewall Security Services to Security Policies Module 7: Security Services ? UTM Content Filtering Web Filtering Antivirus Antispam LAB 5: Adding UTM Security Services to Security Policies Module 8: Juniper Connected Security ? Sky AT Sky ATP Overview Blocking Threats Lab 6: Demonstrating Sky ATP Module 9: Network Address Translation NAT Overview Source NAT Destination NAT Static NAT Lab 7: Implementing Network Address Translation Module 10: IPsec VPN Concepts VPN Types Secure VPN Requirements IPsec Tunnel Establishment IPsec Traffic Processing Module 11: Site-to-Site VPNs IPsec Configuration IPsec Site-to-Site Tunne Lab 8: Implementing Site-to-Site IPsec VPNs Module 12: Monitoring and Reporting J-Web monitoring options J-Web Reporting options Lab 9: Using Monitoring and Reporting Appendix A: SRX Series Hardware Appendix D: Sky Enterprise Services Appendix B: Virtual SRX Appendix EJunos Space Security Director Appendix CCLI Prime

Duration 3 Days 18 CPD hours This course is intended for This is an intermediate course for architects, system integrators, security administrators, network administrators, software engineers, technical support individuals, and IBM Business Partners who implement LPARs on IBM Power Systems. Overview Describe important concepts associated with managing POWER7 processor-based systems, such as Logical partitioning (LPAR), dynamic partitioning, virtual devices, virtual processors, virtual consoles, virtual Local Area Network (VLAN), and shared processors Describe the features of the PowerVM Editions. Use the System Planning Tool to plan an LPAR configuration Describe the functions of the HMC Configure and manage the HMC, including users and permissions, software, startup and shutdown, remote access features, network configuration, security features, HMC backup and restore options, and the HMC reload procedure Describe the rules associated with allocating resources, including dedicated processors, processing units for Micro-Partitions, memory, physical I/O for AIX and Linux partitions Configure and manage LPARs using the HMC Graphical User Interface (GUI) and HMC commands Interpret physical and AIX location codes and relate to the key hardware components Power on and power off the POWER7 system Use the HMC to back up and restore partition data In this course, students will learn the skills needed to become an effective administrator on IBM's POWER7-based systems that support Logical Partitioning (LPAR). Day 1 Introduction to partitioning Hardware system overview Hardware Management Console Day 2 Hardware Management Console (cont.) System Planning Tool HMC and managed system maintenance System power management Planning and configuring logical partitions Day 3 Planning and configuring logical partitions (cont.) Partition operations Dynamic resource allocation Exercise 9 Additional course details: Nexus Humans AN110 IBM Power Systems for AIX I - LPAR Configuration and Planning 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 AN110 IBM Power Systems for AIX I - LPAR Configuration and Planning 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 2 Days 12 CPD hours This course is intended for If you are a data analyst, data scientist, or a business analyst who wants to get started with using Python and machine learning techniques to analyze data and predict outcomes, this book is for you. Basic knowledge of computer programming and data analytics is a must. Familiarity with mathematical concepts such as algebra and basic statistics will be useful. Overview By the end of this course, you will have the skills you need to confidently use various machine learning algorithms to perform detailed data analysis and extract meaningful insights from data. This course is designed to give you practical guidance on industry-standard data analysis and machine learning tools in Python, with the help of realistic data. The course will help you understand how you can use pandas and Matplotlib to critically examine a dataset with summary statistics and graphs, and extract the insights you seek to derive. You will continue to build on your knowledge as you learn how to prepare data and feed it to machine learning algorithms, such as regularized logistic regression and random forest, using the scikit-learn package. You?ll discover how to tune the algorithms to provide the best predictions on new and unseen data. As you delve into later sections, you?ll be able to understand the working and output of these algorithms and gain insight into not only the predictive capabilities of the models but also their reasons for making these predictions. Data Exploration and Cleaning Python and the Anaconda Package Management System Different Types of Data Science Problems Loading the Case Study Data with Jupyter and pandas Data Quality Assurance and Exploration Exploring the Financial History Features in the Dataset Activity 1: Exploring Remaining Financial Features in the Dataset Introduction to Scikit-Learn and Model Evaluation Introduction Model Performance Metrics for Binary Classification Activity 2: Performing Logistic Regression with a New Feature and Creating a Precision-Recall Curve Details of Logistic Regression and Feature Exploration Introduction Examining the Relationships between Features and the Response Univariate Feature Selection: What It Does and Doesn't Do Building Cloud-Native Applications Activity 3: Fitting a Logistic Regression Model and Directly Using the Coefficients The Bias-Variance Trade-off Introduction Estimating the Coefficients and Intercepts of Logistic Regression Cross Validation: Choosing the Regularization Parameter and Other Hyperparameters Activity 4: Cross-Validation and Feature Engineering with the Case Study Data Decision Trees and Random Forests Introduction Decision trees Random Forests: Ensembles of Decision Trees Activity 5: Cross-Validation Grid Search with Random Forest Imputation of Missing Data, Financial Analysis, and Delivery to Client Introduction Review of Modeling Results Dealing with Missing Data: Imputation Strategies Activity 6: Deriving Financial Insights Final Thoughts on Delivering the Predictive Model to the Client

Duration 4 Days 24 CPD hours This course is intended for The primary audience for this course is as follows: Security administrators Security consultants Network administrators System engineers Technical support personnel Channel partners and resellers Overview Upon completing this course, the learner will be able to meet these overall objectives: Define the use and placement IDS/IPS components. Identify Snort features and requirements. Compile and install Snort. Define and use different modes of Snort. Install and utilize Snort supporting software. Securing Cisco Networks with Open Source Snort (SSFSNORT) v3.0 is a 4-day course that shows you how to deploy Snort© in small to enterprise-scale implementations. You will learn how to install, configure, and operate Snort in Intrusion Detection System (IDS) and Intrusion Prevention System (IPS) modes. You?ll practice installing and configuring Snort, utilize additional software tools and define rules to configure and improve the Snort environment, and more. The course qualifies for 32 Cisco Continuing Education credits (CE) towards recertification.This course will help you:Learning how to implement Snort, an open-source, rule-based, intrusion detection and prevention system. Gain leading-edge skills for high-demand responsibilities focused on security. Module 1: Detecting Intrusions with Snort 3.0 History of Snort IDS IPS IDS vs. IPS Examining Attack Vectors Application vs. Service Recognition Module 2: Sniffing the Network Protocol Analyzers Configuring Global Preferences Capture and Display Filters Capturing Packets Decrypting Secure Sockets Layer (SSL) Encrypted Packets Module 3: Architecting Nextgen Detection Snort 3.0 Design Modular Design Support Plug Holes with Plugins Process Packets Detect Interesting Traffic with Rules Output Data Module 4: Choosing a Snort Platform Provisioning and Placing Snort Installing Snort on Linux Module 5: Operating Snort 3.0 Start Snort Monitor the System for Intrusion Attempts Define Traffic to Monitor Log Intrusion Attempts Actions to Take When Snort Detects an Intrusion Attempt License Snort and Subscriptions Module 6: Examining Snort 3.0 Configuration Introducing Key Features Configure Sensors Lua Configuration Wizard Module 7: Managing Snort Pulled Pork Barnyard2 Elasticsearch, Logstash, and Kibana (ELK) Module 8: Analyzing Rule Syntax and Usage Anatomy of Snort Rules Understand Rule Headers Apply Rule Options Shared Object Rules Optimize Rules Analyze Statistics Module 9: Use Distributed Snort 3.0 Design a Distributed Snort System Sensor Placement Sensor Hardware Requirements Necessary Software Snort Configuration Monitor with Snort Module 10: Examining Lua Introduction to Lua Get Started with Lua

Duration 1 Days 6 CPD hours This course is intended for This course is intended for: Data platform engineers Solutions architects IT professionals Overview In this course, you will learn to: Apply data lake methodologies in planning and designing a data lake Articulate the components and services required for building an AWS data lake Secure a data lake with appropriate permission Ingest, store, and transform data in a data lake Query, analyze, and visualize data within a data lake In this course, you will learn how to build an operational data lake that supports analysis of both structured and unstructured data. You will learn the components and functionality of the services involved in creating a data lake. You will use AWS Lake Formation to build a data lake, AWS Glue to build a data catalog, and Amazon Athena to analyze data. The course lectures and labs further your learning with the exploration of several common data lake architectures. Module 1: Introduction to data lakes Describe the value of data lakes Compare data lakes and data warehouses Describe the components of a data lake Recognize common architectures built on data lakes Module 2: Data ingestion, cataloging, and preparation Describe the relationship between data lake storage and data ingestion Describe AWS Glue crawlers and how they are used to create a data catalog Identify data formatting, partitioning, and compression for efficient storage and query Lab 1: Set up a simple data lake Module 3: Data processing and analytics Recognize how data processing applies to a data lake Use AWS Glue to process data within a data lake Describe how to use Amazon Athena to analyze data in a data lake Module 4: Building a data lake with AWS Lake Formation Describe the features and benefits of AWS Lake Formation Use AWS Lake Formation to create a data lake Understand the AWS Lake Formation security model Lab 2: Build a data lake using AWS Lake Formation Module 5: Additional Lake Formation configurations Automate AWS Lake Formation using blueprints and workflows Apply security and access controls to AWS Lake Formation Match records with AWS Lake Formation FindMatches Visualize data with Amazon QuickSight Lab 3: Automate data lake creation using AWS Lake Formation blueprints Lab 4: Data visualization using Amazon QuickSight Module 6: Architecture and course review Post course knowledge check Architecture review Course review Additional course details: Nexus Humans Building Data Lakes on AWS 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 Building Data Lakes on AWS 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 is an intermediate course for system administrators, database administrators, and other technical individuals, who manage and implement DB2 10 for z/OS. Administrators of DB2 11 for z/OS can acquire a view of the architecture and fundamental processes required to manage a DB2 11 for z/OS subsystem. Course Outline Start and stop the DB2 subsystem Explain the allocation CLIST used at logon for DB2 data sets Use Set SYSPARM command Locate the Command recognition character for the DB2 subsystem Query the system log to gain knowledge about the IPL process and information in the system log when DB2 is initialized or stopped Explore DB2 Address Spaces information Select the DB2 functions that best satisfy your site requirements Explain the use of RACF for DB2 connection security Explain the use of Roles and Trusted Context Implement security procedures for a DB2 environment Describe the components and address space structure of a DB2 subsystem Explain DB2 Program Flow for all environments Invoke and use DB2 TSO Facilities Use the DB2 Catalog to monitor authorizations Increase the size of the Active Log data sets Explain DB2 Logging Use SET LOG SUSPEND and SET LOG RESUME Use DSNJU004 to Print Log Map Interpret the output of the Print Log Map Utility DSNJU004 Use DSNJU003 to rename DB2 data sets Plan for recovery of a BSDS failure Monitor and control DB2 Explain transaction flow in IMS and CICS Describe the CICS and DB2 environment Make use and implement the extended 10-byte RBA and LRSN