10419 Guide courses in Manchester delivered Online

Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python-experienced attendees who wish to be equipped with the skills you need to use pandas to ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Overview Working in a hands-on learning environment, guided by our expert team, attendees will learn to: Understand how data analysts and scientists gather and analyze data Perform data analysis and data wrangling using Python Combine, group, and aggregate data from multiple sources Create data visualizations with pandas, matplotlib, and seaborn Apply machine learning (ML) algorithms to identify patterns and make predictions Use Python data science libraries to analyze real-world datasets Use pandas to solve common data representation and analysis problems Build Python scripts, modules, and packages for reusable analysis code Perform efficient data analysis and manipulation tasks using pandas Apply pandas to different real-world domains with the help of step-by-step demonstrations Get accustomed to using pandas as an effective data exploration tool. Data analysis has become a necessary skill in a variety of domains where knowing how to work with data and extract insights can generate significant value. Geared for data team members with incoming Python scripting experience, Hands-On Data Analysis with Pandas will show you how to analyze your data, get started with machine learning, and work effectively with Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the powerful pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will be able to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding lessons, you will explore some applications of anomaly detection, regression, clustering, and classification using scikit-learn to make predictions based on past data. Students will leave the course armed with the skills required to use pandas to ensure the veracity of their data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Introduction to Data Analysis Fundamentals of data analysis Statistical foundations Setting up a virtual environment Working with Pandas DataFrames Pandas data structures Bringing data into a pandas DataFrame Inspecting a DataFrame object Grabbing subsets of the data Adding and removing data Data Wrangling with Pandas What is data wrangling? Collecting temperature data Cleaning up the data Restructuring the data Handling duplicate, missing, or invalid data Aggregating Pandas DataFrames Database-style operations on DataFrames DataFrame operations Aggregations with pandas and numpy Time series Visualizing Data with Pandas and Matplotlib An introduction to matplotlib Plotting with pandas The pandas.plotting subpackage Plotting with Seaborn and Customization Techniques Utilizing seaborn for advanced plotting Formatting Customizing visualizations Financial Analysis - Bitcoin and the Stock Market Building a Python package Data extraction with pandas Exploratory data analysis Technical analysis of financial instruments Modeling performance Rule-Based Anomaly Detection Simulating login attempts Exploratory data analysis Rule-based anomaly detection Getting Started with Machine Learning in Python Learning the lingo Exploratory data analysis Preprocessing data Clustering Regression Classification Making Better Predictions - Optimizing Models Hyperparameter tuning with grid search Feature engineering Ensemble methods Inspecting classification prediction confidence Addressing class imbalance Regularization Machine Learning Anomaly Detection Exploring the data Unsupervised methods Supervised methods Online learning The Road Ahead Data resources Practicing working with data Python practice

Duration 2 Days 12 CPD hours This course is intended for Anyone who works with IBM SPSS Statistics and wants to learn advanced statistical procedures to be able to better answer research questions. Overview Introduction to advanced statistical analysis Group variables: Factor Analysis and Principal Components Analysis Group similar cases: Cluster Analysis Predict categorical targets with Nearest Neighbor Analysis Predict categorical targets with Discriminant Analysis Predict categorical targets with Logistic Regression Predict categorical targets with Decision Trees Introduction to Survival Analysis Introduction to Generalized Linear Models Introduction to Linear Mixed Models This course provides an application-oriented introduction to advanced statistical methods available in IBM SPSS Statistics. Students will review a variety of advanced statistical techniques and discuss situations in which each technique would be used, the assumptions made by each method, how to set up the analysis, and how to interpret the results. This includes a broad range of techniques for predicting variables, as well as methods to cluster variables and cases. Introduction to advanced statistical analysis Taxonomy of models Overview of supervised models Overview of models to create natural groupings Group variables: Factor Analysis and Principal Components Analysis Factor Analysis basics Principal Components basics Assumptions of Factor Analysis Key issues in Factor Analysis Improve the interpretability Use Factor and component scores Group similar cases: Cluster Analysis Cluster Analysis basics Key issues in Cluster Analysis K-Means Cluster Analysis Assumptions of K-Means Cluster Analysis TwoStep Cluster Analysis Assumptions of TwoStep Cluster Analysis Predict categorical targets with Nearest Neighbor Analysis Nearest Neighbor Analysis basics Key issues in Nearest Neighbor Analysis Assess model fit Predict categorical targets with Discriminant Analysis Discriminant Analysis basics The Discriminant Analysis model Core concepts of Discriminant Analysis Classification of cases Assumptions of Discriminant Analysis Validate the solution Predict categorical targets with Logistic Regression Binary Logistic Regression basics The Binary Logistic Regression model Multinomial Logistic Regression basics Assumptions of Logistic Regression procedures Testing hypotheses Predict categorical targets with Decision Trees Decision Trees basics Validate the solution Explore CHAID Explore CRT Comparing Decision Trees methods Introduction to Survival Analysis Survival Analysis basics Kaplan-Meier Analysis Assumptions of Kaplan-Meier Analysis Cox Regression Assumptions of Cox Regression Introduction to Generalized Linear Models Generalized Linear Models basics Available distributions Available link functions Introduction to Linear Mixed Models Linear Mixed Models basics Hierachical Linear Models Modeling strategy Assumptions of Linear Mixed Models Additional course details: Nexus Humans 0G09A IBM Advanced Statistical Analysis Using IBM SPSS Statistics (v25) 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 0G09A IBM Advanced Statistical Analysis Using IBM SPSS Statistics (v25) 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 course is designed for existing Python programmers who have at least one year of Python experience and who want to expand their programming proficiency in Python 3. Overview In this course, you will expand your Python proficiencies. You will: Select an object-oriented programming approach for Python applications. Create object-oriented Python applications. Create a desktop application. Create a data-driven application. Create and secure web service-connected applications. Program Python for data science. Implement unit testing and exception handling. Package an application for distribution.   Python continues to be a popular programming language, perhaps owing to its easy learning curve, small code footprint, and versatility for business, web, and scientific uses. Python is useful for developing custom software tools, applications, web services, and cloud applications. In this course, you'll build upon your basic Python skills, learning more advanced topics such as object-oriented programming patterns, development of graphical user interfaces, data management, creating web service-connected apps, performing data science tasks, unit testing, and creating and installing packages and executable applications. Selecting an Object-Oriented Programming Approach for Python Applications Topic A: Implement Object-Oriented Design Topic B: Leverage the Benefits of Object-Oriented Programming Creating Object-Oriented Python Applications Topic A: Create a Class Topic B: Use Built-in Methods Topic C: Implement the Factory Design Pattern Creating a Desktop Application Topic A: Design a Graphical User Interface (GUI) Topic B: Create Interactive Applications Creating Data-Driven Applications Topic A: Connect to Data Topic B: Store, Update, and Delete Data in a Database Creating and Securing a Web Service-Connected App Topic A: Select a Network Application Protocol Topic B: Create a RESTful Web Service Topic C: Create a Web Service Client Topic D: Secure Connected Applications Programming Python for Data Science Topic A: Clean Data with Python Topic B: Visualize Data with Python Topic C: Perform Linear Regression with Machine Learning Implementing Unit Testing and Exception Handling Topic A: Handle Exceptions Topic B: Write a Unit Test Topic C: Execute a Unit Test Packaging an Application for Distribution Topic A: Create and Install a Package Topic B: Generate Alternative Distribution Files Additional course details: Nexus Humans Advanced Programming Techniques with Python 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 Advanced Programming Techniques with Python 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 Data Protection Officers Data Protection Managers Auditors Legal Compliance Officers Security Manager Information Managers Anyone involved with data protection processes and programmes Overview Principles of Privacy Program Management is the how-to training on implementing a privacy program framework, managing the privacy program operational lifecycle and structuring a knowledgeable, high-performing privacy team. Those taking this course will learn the skills to manage privacy in an organization through process and technology?regardless of jurisdiction or industry. The Principles of Privacy Program Management training is based on the body of knowledge for the IAPP?s ANSI accredited Certified Information Privacy Manager (CIPM) certification program. Founded in 2000, the IAPP is the world?s largest and most comprehensive privacy resource with a mission to define, support and improve the Privacy profession globally. Every organization has data protection needs. Every day, we access, share and manage data across companies, continents and the globe. Knowing how to implement a privacy program is an invaluable skill that will help you protect your organization?s data?and take your career to the next level. Our Principles of Privacy Program Management training is the premier course on implementing a privacy program framework, managing the privacy program operational lifecycle and structuring a privacy team. Introduction to privacy program management Privacy program management responsibilities Accountability in privacy program management Privacy governance Considerations for developing and implementing a privacy program Position of the privacy function within an organization Role of the DPO Program scope and charter Privacy strategy Support and ongoing involvement of key functions and privacy frameworks Applicable laws and regulations The regulatory environment Common elements across jurisdictions Strategies for aligning compliance with organizational strategy Data assessments Practical processes for creating and using data inventories/maps Generating and applying gap analyses Privacy assessments Privacy impact assessments/data protection impact assessments Vendor assessments Policies Common types of privacy-related policies Policy components Strategies for implementation Data subject rights Operational considerations for communicating and ensuring data subject rights Privacy notice Choice and consent Access and rectification Data portability Erasure Training and awareness Developing privacy training and awareness programs Implementing privacy training and awareness programs Protecting personal information Holistic approach to protecting personal information Privacy by design Data breach incident plans Planning for a data security incident or breach Responding to a data security incident or breach Monitoring and auditing program performance Common practices for monitoring privacy program performance Measuring, analyzing and auditing privacy programs Additional course details: Nexus Humans Certified Information Privacy Manager (CIPM) 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 Certified Information Privacy Manager (CIPM) 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 Data Modelers Participants will learn the full scope of the metadata modeling process, from initial project creation, to publishing a dynamic cube, and enabling end users to easily author reports and analyze data. Introduction to IBM Cognos Dynamic Cubes Define and differentiate Dynamic Cubes Dynamic Cubes characteristics Examine Dynamic Cube requirements Examine Dynamic Cube components Examine high level architecture IBM Cognos Dynamic Query Review Dimensional Data Structures Dynamic Cubes caching Create & Design a Dynamic Cube Explore the IBM Cognos Cube Designer Review the cube development process Examine the Automatic Cube Generation Manual development overview Create dimensions Model the cube Best practice for effective modeling Deploy & Configure a Dynamic Cube Deploy a cube Explore the Estimate Hardware Requirements Identify cube management tasks Examine Query Service administration Explore Dynamic Cube properties Schedule cube actions Use the DCAdmin comment line tool Advanced Dynamic Cube Modelling Examine advanced modeling concepts Explore modeling caveats Calculated measures and members Model Relative Time Explore the Current Period property Define period aggregation rules for measures Advanced Features of Cube Designer Examine multilingual support Examine ragged hierarchies and padding members Define Parent-Child Dimensions Refresh Metadata Import Framework Manager packages Filter measures and dimensions Optimize Performance with Aggregates Identify aggregates and aggregate tables In-memory aggregates Use Aggregate Advisor to identify aggregates User defined in-memory aggregates Optimize In-Memory Aggregates automatically Aggregate Advisor recommendations Monitor Dynamic Cube performance Model aggregates (automatically vs manually) Use Slicers to define aggregation partitions Define Security Overview of Dynamic Cube security Identify security filters The Security process - Three steps Examine security scope Identify scope rules Identify roles Capabilities and access permissions Cube security deep dive Model a Virtual Cube Explore virtual cubes Create the virtual cube Explore virtual cube objects Examine virtual measures and calculated members Currency conversion using virtual cubes Security on virtual cubes Introduction to IBM Cognos Analytics Define IBM Cognos Analytics Redefined Business Intelligence Self-service Navigate to content in IBM Cognos Analytics Interact with the user interface Model data with IBM Cognos Analytics IBM Cognos Analytics components Create reports Perform self-service with analysis and Dashboards IBM Cognos Analytics architecture (high level) IBM Cognos Analytics security Package / data source relationship Create Data modules Upload files Additional course details: Nexus Humans B6063 IBM Cognos Cube Designer - Design Dynamic Cubes (v11.0) 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 B6063 IBM Cognos Cube Designer - Design Dynamic Cubes (v11.0) 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 introductory-level Python course is geared for experienced web developers new to Python who want to use Python and Django for full stack web development projects. Overview Working in a hands-on learning environment, guided by our expert team, attendees will learn to: Develop full-stack web sites based on content stored in an RDMS Use python data types appropriately Define data models Understand the architecture of a Django-based web site Create Django templates for easy-to-modify views Map views to URLs Take advantage of the built-in Admin interface Provide HTML form processing Geared for experienced web developers new to Python, Introduction to Full Stack Web Development with Python and Django is a five-day hands-on course that teaches students how to develop Web applications using the Django framework. Students will explore the basics of creating basic applications using the MVC (model-view-controller) design pattern, as well as more advanced topics such as administration, session management, authentication, and automated testing. This comprehensive, practical course provides an in-depth exploration of working with the programming language, not an academic overview of syntax and grammar. Students will immediately be able to use Python to complete tasks in the real world. The Python Environment Starting Python Using the interpreter Running a Python script Getting help Editors and IDEs Getting Started Using variables Built in functions Strings Numbers Converting among types Writing to the screen Command line parameters Flow Control About flow control Conditional expressions Relational and Boolean operators while loops Lists and Tuples About sequences Lists and list methods Tuples Indexing and slicing Iterating through a sequence Sequence functions, keywords, and operators List comprehensions Working with Files File overview The with statement Opening a file Reading/writing files Dictionaries and Sets About dictionaries Creating and using dictionaries About sets Creating and using sets Functions Returning values Function parameters Variable Scope Sorting with functions Errors and Exception Handling Exception overview Using try/catch/else/finally Handling multiple exceptions Ignoring exceptions Modules and Packages Creating Modules The import statement Module search path Creating packages Classes About OO programming Defining classes Constructors Properties Instance methods and data Class/static methods and data Inheritance Django Architecture Django overview Sites and apps Shared configuration Minimal Django layout Built in flexibility Configuring a Project Executing manage.py Starting the project Generating app files App configuration Database setup The development server Using cookiecutter Creating models Defining models Related objects SQL Migration Simplel model access Login for Nothing and Admin for Free Setting up the admin user Using the admin interface Views What is a view HttpResponse URL route configuration Shortcut: get_object_or_404() Class-based views Templates About templates Variable lookups The url tag Shortcut: render() Querying Models QuerySets Field lookups Chaining filters Slicing QuerySets Related fields Q objects Advanced Templates Use Comments Inheritance Filters Escaping HTML Custom filters Forms Forms overview GET and POST The Form class Processing the form Widgets Validation Forms in templates Automated Testing Why create tests? When to create tests Using Django's test framework Using the test client Running tests Checking code coverage

Duration 3 Days 18 CPD hours Overview In this course you?ll learn how to: Containerize and deploy a new Python script Configure the deployment with ConfigMaps, Secrets and SecurityContexts Understand multi-container pod design Configure probes for pod health Update and roll back an application Implement services and NetworkPolicies Use PersistentVolumeClaims for state persistence And more In this vendor agnostic course, you will use Python to build, monitor and troubleshoot scalable applications in Kubernetes. Introduction Objectives Who You Are The Linux Foundation Linux Foundation Training Preparing Your System Course Registration Labs Kubernetes Architecture What Is Kubernetes? Components of Kubernetes Challenges The Borg Heritage Kubernetes Architecture Terminology Master Node Minion (Worker) Nodes Pods Services Controllers Single IP per Pod Networking Setup CNI Network Configuration File Pod-to-Pod Communication Cloud Native Computing Foundation Resource Recommendations Labs Build Container Options Containerizing an Application Hosting a Local Repository Creating a Deployment Running Commands in a Container Multi-Container Pod readinessProbe livenessProbe Testing Labs Design Traditional Applications: Considerations Decoupled Resources Transience Flexible Framework Managing Resource Usage Multi-Container Pods Sidecar Container Adapter Container Ambassador Points to Ponder Labs Deployment Configuration Volumes Overview Introducing Volumes Volume Spec Volume Types Shared Volume Example Persistent Volumes and Claims Persistent Volume Persistent Volume Claim Dynamic Provisioning Secrets Using Secrets via Environment Variables Mounting Secrets as Volumes Portable Data with ConfigMaps Using ConfigMaps Deployment Configuration Status Scaling and Rolling Updates Deployment Rollbacks Jobs Labs Security Security Overview Accessing the API Authentication Authorization ABAC RBAC RBAC Process Overview Admission Controller Security Contexts Pod Security Policies Network Security Policies Network Security Policy Example Default Policy Example Labs Exposing Applications Service Types Services Diagram Service Update Pattern Accessing an Application with a Service Service without a Selector ClusterIP NodePort LoadBalancer ExternalName Ingress Resource Ingress Controller Labs Troubleshooting Troubleshotting Overview Basic Troubleshooting Steps Ongoing (Constant) Change Basic Troubleshooting Flow: Pods Basic Troubleshooting Flow: Node and Security Basic Troubleshooting Flow: Agents Monitoring Logging Tools Monitoring Applications System and Agent Logs Conformance Testing More Resource Labs Additional course details: Nexus Humans Kubernetes for App Developers 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 Kubernetes for App Developers 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 There is no specific prerequisite for the CDRP© course. However, participants who have at least three years' experience in a data centre and/or IT infrastructures will be best suited. Overview After completion of the course, the participant will be able to: 1. Understand the different standards and methodologies for risk management and assessment 2. Establish the required project team for risk management 3. Perform the risk assessment, identifying current threats, vulnerabilities and the potential impact based on customised threat catalogues 4. Report on the current risk level of the data centre both quantitative and qualitative 5. Anticipate and minimise potential financial impacts 6. Understand the options for handling risk 7. Continuously monitor and review the status of risk present in the data centre 8. Reduce the frequency and magnitude of incidents 9. Detect and respond to events when they occur 10. Meet regulatory and compliance requirements 11. Support certification processes such as ISO/IEC 27001 12. Support overall corporate and IT governance Introduction to Risk Management Risk management concepts Senior management and risk Enterprise Risk Management (ERM) Benefits of risk management Data Centre Risk and Impact Risk in facility, power, cooling, fire suppression, infrastructure and IT services Impact of data centre downtime Main causes of downtime Cost factors in downtime Standards, Guidelines and Methodologies ISO/IEC 27001:2013, ISO/IEC 27005:2011, ISO/IEC 27002:2013 NIST SP 800-30 ISO/IEC 31000:2009 SS507:2008 ANSI/TIA-942 Other methodologies (CRAMM, EBIOS, OCTAVE, etc.) Risk Management Definitions Asset Availability/Confidentiality/Integrity Control Information processing facility Information security Policy Risk Risk analysis/Risk assessment/Risk evaluation/ Risk treatment Threat/Vulnerability Types of risk Risk Assessment Software The need for software Automation Considerations Risk Management Process The risk management process Establishing the context Identification Analysis Evaluation Treatment Communication and consultation Monitoring and review Project Approach Project management principles Project management methods Scope Time Cost Cost estimate methods Context Establishment General considerations Risk evaluation, impact and acceptance criteria Severity rating of impact Occurrence rating of probability Scope and boundaries Scope constraints Roles & responsibilities Training, awareness and competence Risk Assessment - Identification The risk assessment process Identification of assets Identification of threats Identification of existing controls Identification of vulnerabilities Identification of consequences Hands-on exercise: Identification of assets, threats, existing controls, vulnerabilities and consequences Risk Assessment - Analysis and Evaluation Risk estimation Risk estimation methodologies Assessment of consequences Assessment of incident likelihood Level of risk estimation Risk evaluation Hands-on exercise: Assessment of consequences, probability and estimating level of risk Risk Treatment The risk treatment process steps Risk Treatment Plan (RTP) Risk modification Risk retention Risk avoidance Risk sharing Constraints in risk modification Control categories Control examples Cost-benefit analysis Control implementation Residual risk Communication Effective communication of risk management activities Benefits and concerns of communication Risk Monitoring and Review Ongoing monitoring and review Criteria for review Risk scenarios Risk assessment approach Data centre site selection Data centre facility Cloud computing UPS scenarios Force majeure Organisational shortcomings Human failure Technical failure Deliberate acts Exam: Certified Data Centre Risk Professional Actual course outline may vary depending on offering center. Contact your sales representative for more information.

Duration 4 Days 24 CPD hours This course is intended for This course is intended for the person who has responsibility for daily system operations. Overview Send, display, and respond to messages Use the online help and reference materials Monitor and control job queues, active jobs, and output queues Create and change user profiles Use authorization lists and group profiles Start and stop Power Systems with IBM i Manage system devices, user display stations, and printers Save and restore objects and libraries Monitor job and history logs Diagnose a system problem Order, receive, and install PTFs This course enables a new system operator to develop basic to intermediate level skills needed for day-to-day operations of the Power System with IBM i Power Systems and IBM i concepts and overview . Reference material and support . Overview of 5250 emulation and help . Overview of System i Navigator . Overview of IBM Navigator for i . Messaging concepts . Messaging with 5250 emulation . Messaging with System i Navigator . Messaging with IBM Navigator for i . CL command concepts . CL commands with 5250 emulation . Concepts: Object, library, and the IFS . Object management with 5250 emulation . Object management with System i Navigator . Object management with IBM Navigator for i . Introduction to work management . Work management with 5250 emulation . Job control with 5250 emulation . Job control with System i Navigator . Job control with IBM Navigator for i . Print concepts . Print control with 5250 emulation . Print control with System i Navigator . Print control with IBM Navigator for i . Starting and stopping the system . System security concepts . System security with 5250 emulation . System security with System i Navigator . System security with IBM Navigator for i . System configuration overview . Configuration with 5250 emulation . Configuration with System i Navigator . Configuration with IBM Navigator for i . Save concepts . Save with 5250 emulation . Save with System i Navigator . Save with IBM Navigator for i . Restore concepts and overview . Problem determination with 5250 emulation . Problem determination with System i Navigator . Overview of the PTF process . PTFs with 5250 Emulation . Class summary . Additional course details: Nexus Humans AS24 IBM System Operator Workshop for IBM i 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 AS24 IBM System Operator Workshop for IBM i 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 4 Days 24 CPD hours This course is intended for The primary audience for this course are as follows: Technical professionals, including system engineers, technical support personnel, channel partners, and resellers, who need to know how to deploy Cisco ASR 9000 Series routers in their network environment Overview Upon completing this course, the learner will be able to meet these overall objectives: Major features and benefits of a Cisco ASR 9000 Series router Major features and benefits of the Cisco IOS XR Software operating system Data flow through the Cisco ASR 9000 Series router Configure the Cisco ASR 9000, back out of configuration changes, and restore older versions of the configuration Install the Cisco IOS XR operating system, package information envelopes (PIEs), and software maintenance updates (SMUs) Enable multicast routing on a Cisco ASR 9000 Series router Configure Multiprotocol Label Switch-Traffic Engineering (MPLS-TE) on a Cisco ASR 9000 Series router Configure Layer 3 VPN services Configure Ethernet link bundles Configure local E-Line L2VPN Configure Ethernet over MPLS E-Line L2VPN Configure EoMPLS with pseudowire backup Configure local E-LAN L2VPN Configure link-based Ethernet operations, administration, and maintenance (E-OAM) Configure virtual private LAN service (VPLS) L2VPN Configure VPLS with Border Gateway Protocol (BGP) autodiscover Configure service-based connectivity fault management (CFM) Multiple Spanning Tree-Access Gateway (MST-AG) Configure Layer 2 multicast features Basic QoS implementation How to configure and verify network virtualization (nV) on the ASR 9000 series In this 4-day course, Cisco Aggregation Services Router 9000 Series Essentials (ASR9KE), you will learn about the features and functions of the Cisco ASR 9000 Series platforms. Through a combination of lecture and hands-on labs, you will gain an understanding of all major aspects of the platform, including hardware; software; Layer 2 and Layer 3 services; Layer 2 and Layer 3 multicast; operations, administration, and management (OAM); quality of service (QoS) features; and network virtualization. Course Outline Introduction to the Cisco ASR 9000 Aggregation Series Cisco ASR 9000 Hardware Cisco IOS XR Software Overview Cisco IOS XR Software Basics Cisco IOS XR Software Installation Cisco IOS XR Software Operations Cisco IOS XR Routing Protocols Layer 3 Multicast Cisco IOS XR MPLS Cisco IOS XR Layer 3 VPN Cisco ASR 9000 Layer 2 Architecture Cisco ASR 9000 Point-to-Point Layer 2 Services Cisco ASR 9000 Multipoint Layer 2 Services Cisco ASR 9000 Operations, Administration, and Maintenance Cisco ASR 9000 Layer 2 Multicast Cisco ASR 9000 QoS Cisco ASR 9000 Network Virtualization Additional course details: Nexus Humans Cisco ASR 9000 Aggregation Services Router Series Essentials v6.1 (ASR9KE) 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 ASR 9000 Aggregation Services Router Series Essentials v6.1 (ASR9KE) 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.