31621 Courses

Duration 3 Days 18 CPD hours This course is intended for This is an Introductory level course for experienced Linux system administrators, DevOps engineers, infrastructure automation engineers, and systems design engineers. Ideally students should have familiarity with basic Python scripting. Attendees without programming skills can follow along with the scripting portion of the labs. Overview This course is approximately 50% hands-on, 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 practitioner attendees will explore how to: Describe Ansible concepts and install Red Hat Ansible Engine (optional - we can pre-install is as well if desired, depending on the audience) Deploy Ansible and Configure Ansible to manage hosts and run ad hoc Ansible commands. Implement playbooks Write a simple Ansible playbook and run it to automate tasks on multiple managed hosts. Manage variables and facts Write playbooks that use variables to simplify management of the playbook and facts to reference information about managed hosts. Implement task control; Manage task control, handlers, and task errors in Ansible playbooks. Deploy files to managed hosts Deploy, manage, and adjust files on hosts managed by Ansible. Manage large projects Write playbooks that are optimized for larger, more complex projects. Simplify playbooks with roles Use Ansible roles to develop playbooks more quickly and to reuse Ansible code. Troubleshoot Ansible Troubleshoot playbooks and managed hosts. Automate Linux administration tasks Automate common Linux system administration tasks with Ansible This lab-intensive course is geared toward those responsible for automation of configuration management; consistent and repeatable application deployment; provisioning and deployment of development, testing, and production servers; and integration with DevOps CI/CD workflows. Throughout the course you will explore core Ansible features such as automatic provisioning, configuration management, service deployment and operational processes. Ansible Overview Overview of Architecture Overview of Deployments Inventory Deploying Ansible Installing Configuration Files Running Ad Hoc Commands Dynamic Inventory Playbooks Writing YAML Files Modules Variables and Inclusions Variables Facts Inclusions Task Control Constructing Flow Control Handlers Tags Handling Errors Jinja2 Templates Jinja2 Templates Jinja2 Templates Roles Role Structure Creating Roles Deploying Roles with Ansible Galaxy Optimizing Ansible Configuring Connection Types Configuring Delegation Configuring Parallelism Ansible Vault Configuring Ansible Vault Executing with Ansible Vault Troubleshooting Ansible Troubleshooting Playbooks Troubleshooting Managed Hosts Ansible Tower Ansible Tower overview Installing Account management Hosts Jobs Optional: Ansible in a DevOps Environment Provisioning Vagrant Machines Deploying Vagrant in a DevOps Environment Deploying Docker in a DevOps Environment Additional course details: Nexus Humans Introduction to Ansible: Automation with Ansible (TTDV7580) 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 Ansible: Automation with Ansible (TTDV7580) 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 primarily intended for existing IT professionals who have some AD DS knowledge and experience and who aim to develop knowledge about identity and access technologies in Windows Server 2016. The secondary audience for this course includes IT professionals who are looking to consolidate their knowledge about AD DS and related technologies, in addition to IT professionals who want to prepare for the 70-742 exam. Overview After completing this course, students will be able to:Install and configure domain controllers.Manage objects in AD DS by using graphical tools and Windows PowerShell.Implement AD DS in complex environments.Implement AD DS sites, and configure and manage replication.Implement and manage Group Policy Objects (GPOs).Manage user settings by using GPOs.Secure AD DS and user accounts.Implement and manage a certificate authority (CA) hierarchy with AD CS.Deploy and manage certificates.Implement and administer AD FS.Implement and administer Active Directory Rights Management Services (AD RMS).Implement synchronization between AD DS and Azure AD.Monitor, troubleshoot, and establish business continuity for AD DS services. This course teaches IT Pros how to deploy and configure Active Directory Domain Services in a distributed environment, how to implement Group Policy, how to perform backup & restore, & how to troubleshoot Active Directory?related issues. Installing & Configuring DCs Overview of AD DS Overview of AD DS DCs Deploying DCs Lab: Deploying and administering AD DS Managing Objects in AD DS Managing user accounts Managing groups in AD DS Managing computer accounts Using Windows PowerShell for AD DS administration Implementing and managing organizational units Lab: Deploying and administering AD DS Lab: Administering AD DS Advanced AD DS Infrastructure Management Overview of advanced AD DS deployments Deploying a distributed AD DS environment Configuring AD DS trusts Lab: Domain and trust management in AD DS Implementing & Administering AD DS Sites & Replication Overview of AD DS replication Configuring AD DS sites Configuring and monitoring AD DS replication Lab: Managing and implementing AD DS sites and replication Implementing Group Policy Introducing Group Policy Implementing and administering GPOs Group Policy scope and Group Policy processing Troubleshooting the application of GPOs Lab: Implementing a Group Policy infrastructure Lab: Troubleshooting a Group Policy Infrastructure Managing User Settings with GPOs Implementing administrative templates Configuring Folder Redirection and scripts Configuring Group Policy preferences Lab: Managing user settings with GPOs Securing AD DS Securing domain controllers Implementing account security Audit authentication Configuring managed service accounts (MSAs) Lab: Securing AD DS Deploying & Managing AD CS Deploying CAs Administering CAs Troubleshooting and maintaining CAs Lab: Deploying and configuring a two-tier CA hierarchy Deploying & Managing Certificates Deploying and managing certificate templates Managing certificate deployment, revocation, and recovery Using certificates in a business environment Implementing and managing smart cards Lab: Deploying certificates Implementing & Administering AD FS Overview of AD FS AD FS requirements and planning Deploying and configuring AD FS Overview of Web Application Proxy Lab: Implementing AD FS Implementing & Administering AD RMS Overview of AD RMS Deploying and managing an AD RMS infrastructure Configuring AD RMS content protection Lab: Implementing an AD RMS infrastructure Implementing AD DS Synchronization with Azure AD Planning and preparing for directory synchronization Implementing directory synchronization by using Azure AD Connect Managing identities with directory synchronization Lab: Configuring directory synchronization Monitoring, Managing, & Recovering AD DS Monitoring AD DS Managing the AD DS database Recovering AD DS objects Lab: Recovering objects in AD DS

Duration 5 Days 30 CPD hours This course is intended for This course is primarily intended for existing IT professionals who have some AD DS knowledge and experience and who aim to develop knowledge about identity and access technologies in Windows Server 2016. The secondary audience for this course includes IT professionals who are looking to consolidate their knowledge about AD DS and related technologies, in addition to IT professionals who want to prepare for the 70-742 exam. Overview After completing this course, students will be able to: Install and configure domain controllers. Manage objects in AD DS by using graphical tools and Windows PowerShell. Implement AD DS in complex environments. Implement AD DS sites, and configure and manage replication. Implement and manage Group Policy Objects (GPOs). Manage user settings by using GPOs. Secure AD DS and user accounts. Implement and manage a certificate authority (CA) hierarchy with AD CS. Deploy and manage certificates. Implement and administer AD FS. Implement and administer Active Directory Rights Management Services (AD RMS). Implement synchronization between AD DS and Azure AD. Monitor, troubleshoot, and establish business continuity for AD DS services. This course teaches IT Pros how to deploy and configure Active Directory Domain Services in a distributed environment, how to implement Group Policy, how to perform backup & restore, & how to troubleshoot Active Directory?related issues. Installing & Configuring DCs Overview of AD DS Overview of AD DS DCs Deploying DCs Lab: Deploying and administering AD DS Managing Objects in AD DS Managing user accounts Managing groups in AD DS Managing computer accounts Using Windows PowerShell for AD DS administration Implementing and managing organizational units Lab: Deploying and administering AD DS Lab: Administering AD DS Advanced AD DS Infrastructure Management Overview of advanced AD DS deployments Deploying a distributed AD DS environment Configuring AD DS trusts Lab: Domain and trust management in AD DS Implementing & Administering AD DS Sites & Replication Overview of AD DS replication Configuring AD DS sites Configuring and monitoring AD DS replication Lab: Managing and implementing AD DS sites and replication Implementing Group Policy Introducing Group Policy Implementing and administering GPOs Group Policy scope and Group Policy processing Troubleshooting the application of GPOs Lab: Implementing a Group Policy infrastructure Lab: Troubleshooting a Group Policy Infrastructure Managing User Settings with GPOs Implementing administrative templates Configuring Folder Redirection and scripts Configuring Group Policy preferences Lab: Managing user settings with GPOs Securing AD DS Securing domain controllers Implementing account security Audit authentication Configuring managed service accounts (MSAs) Lab: Securing AD DS Deploying & Managing AD CS Deploying CAs Administering CAs Troubleshooting and maintaining CAs Lab: Deploying and configuring a two-tier CA hierarchy Deploying & Managing Certificates Deploying and managing certificate templates Managing certificate deployment, revocation, and recovery Using certificates in a business environment Implementing and managing smart cards Lab: Deploying certificates Implementing & Administering AD FS Overview of AD FS AD FS requirements and planning Deploying and configuring AD FS Overview of Web Application Proxy Lab: Implementing AD FS Implementing & Administering AD RMS Overview of AD RMS Deploying and managing an AD RMS infrastructure Configuring AD RMS content protection Lab: Implementing an AD RMS infrastructure Implementing AD DS Synchronization with Azure AD Planning and preparing for directory synchronization Implementing directory synchronization by using Azure AD Connect Managing identities with directory synchronization Lab: Configuring directory synchronization Monitoring, Managing, & Recovering AD DS Monitoring AD DS Managing the AD DS database Recovering AD DS objects Lab: Recovering objects in AD DS

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 This course is intended for network administrators, operators, and engineers responsible for managing the normal day-to-day operation and administration of a BIG-IP application delivery network. This course presents the prerequisite knowledge for many other of F5's BIG-IP instructor-led training courses. Overview Getting started with the BIG-IP system Traffic processing with BIG-IP Local Traffic Manager (LTM) Using the TMSH (TMOS Shell) command line interface Using NATs and SNATs Monitoring application health and managing object status Modifying traffic behavior with profiles, including SSL offload and re-encryption Modifying traffic behavior with persistence, including source address affinity and cookie persistence Troubleshooting the BIG-IP system, including logging (local, high-speed, and legacy remote logging), and using tcpdump User roles and administrative partitions vCMP concepts Customizing application delivery with iRules This course gives network administrators, network operators, and network engineers a functional understanding of the BIG-IP system as it is commonly deployed in an application delivery network. The course introduces students to the BIG-IP system, its configuration objects, how it processes traffic, and how typical administrative and operational activities are performed. The course includes lecture, hands-on labs, interactive demonstrations, and discussions. Setting Up the BIG-IP System Introducing the BIG-IP System Initially Setting Up the BIG-IP System Configuring the Management Interface Activating the Software License Provisioning Modules and Resources Importing a Device Certificate Specifying BIG-IP Platform Properties Configuring the Network Configuring Network Time Protocol (NTP) Servers Configuring Domain Name System (DNS) Settings Configuring High Availability Options Archiving the BIG-IP Configuration Leveraging F5 Support Resources and Tools Traffic Processing Building Blocks Identifying BIG-IP Traffic Processing Objects Configuring Virtual Servers and Pools Load Balancing Traffic Viewing Module Statistics and Logs Using the Traffic Management Shell (TMSH) Understanding the TMSH Hierarchical Structure Navigating the TMSH Hierarchy Managing BIG-IP Configuration State and Files BIG-IP System Configuration State Loading and Saving the System Configuration Shutting Down and Restarting the BIG-IP System Saving and Replicating Configuration Data (UCS and SCF) Using NATs and SNATs Address Translation on the BIG-IP System Mapping IP Addresses with NATs Solving Routing Issues with SNATs Configuring SNAT Auto Map on a Virtual Server Monitoring for and Mitigating Port Exhaustion Monitoring Application Health Introducing Monitors Types of Monitors Monitor Interval and Timeout Settings Configuring Monitors Assigning Monitors to Resources Managing Pool, Pool Member, and Node Status Using the Network Map Modifying Traffic Behavior with Profiles Introducing Profiles Understanding Profile Types and Dependencies Configuring and Assigning Profiles Introducing SSL Offload and SSL Re-Encryption Managing Object State Modifying Traffic Behavior with Persistence Understanding the Need for Persistence Introducing Source Address Affinity Persistence Managing Object State Administering the BIG-IP System Configuring Logging Legacy Remote Logging Introducing High Speed Logging (HSL) High-Speed Logging Filters HSL Configuration Objects Configuring High Speed Logging Using TCPDUMP on the BIG-IP System Leveraging the BIG-IP iHealth System Viewing BIG-IP System Statistics Defining User Roles and Administrative Partitions Leveraging vCMP Configuring High Availability Introducing Device Service Clustering (DSC) Preparing to Deploy a DSC Configuration Configuring DSC Communication Settings Establishing Device Trust Establishing a Sync-Failover Device Group Synchronizing Configuration Data Exploring Traffic Group Behavior Understanding Failover Managers and Triggers Achieving Stateful Failover with Mirroring

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 2 Days 12 CPD hours This course is intended for This is an intermediate level training course, designed for experienced Java developers and architects who need to identify, design, and implement web services. We will explore and apply the terminology, the specification, the processes and technologies specific to web services. Students should have at least a year of practical development experience with Java and servlets, and should be familiar with XML and JSON. Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, designed to train attendees in core RESTful development skills, coupling the most current, effective techniques with the soundest industry practices. Working within in a hands-on learning environment, guided by our expert team, attendees will learn to: Understand and apply the basic concepts of REST Understand and intelligently discuss the similarities and differences between RESTful services and SOAP-based services Appreciate the security concerns associated with RESTful services Design, develop, and deploy real-world RESTful Services Effectively define and design endpoints Work with query parameters Determine the best format to use for exchanging data Understand the principles associated with HTTP methods and how to stay congruent to them Extend the semantics of the RESTful service beyond the HTTP methods Implement RESTful services using JAX-RS to Handle various HTTP methods Use different approaches for parameters Deal with content negotiation Work with different data formats including XML and JSON Handle exceptions Implement RESTful Java clients Develop JAX-RS Java clients using the JAX-RS 2.0 Client API Manage different Web targets Deal with content negotiation on the client Work with different data formats including XML and JSON Properly process server responses Implement JAX-RS Filters and Interceptors Intercept and manipulate service requests and responses Dynamically register interceptor to resources Understand the concept of NameBinding Discover asynchronous JAX-RS processing Implement an asynchronous JAX-RS service endpoint Register response listeners Geared for experienced Java developers, Java REST Essentials is a two day, lab-intensive services training course that introduces developers to the core concepts, principles, and Java implementations for RESTful services. Today's development environments are increasingly dominated by sophisticated tooling that makes the implementation of RESTful services less arduous. The proper design of these services is far more complex and demanding. Java RESTful Service Essentials focuses on providing an understanding of the fundamental principles and technologies that are used in building these services. This understanding is critical to being able to diagnose, troubleshoot, tune, and perform other lifecycle activities. Session: Working with REST Overview of REST Designing RESTful Services JAX-RS Lesson: Introduction to JAX-RS @Path: URI Matching JAX-RS Content Negotiation JAX-RS Request and Response JAX-RS Client API JAX-RS Filters and Interceptors Asynchronous JAX-RS Additional course details: Nexus Humans Java REST Essentials (TT7305) 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 Java REST Essentials (TT7305) 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 beginning DB2 basic course is for z/OS database administrators who need to acquire the basic skills required to administer a DB2 database in a z/OS environment. Overview Describe several services provided in a z/OS environmentExplain workloads in the batch environmentExplain workloads in the online environmentDescribe job roles in a z/OS environmentLog On to TSO/ENavigate TSO/E and ISPFUse TSO commandsSetup and utilize JCL (Job Control Language)Utilize SDSFDescribe the different types of data sets in a z/OS environmentAllocate data sets and list data set information and contentCreate and modify data set contentGive an overview of the DB2 9 environmentDescribe and utilize DB2 ObjectsDescribe and utilize several DB2 UtilitiesDescribe the DB2I (DB2 Interactive Facility) environmentUse SPUFI (SQL Processing Using File Input) to compose and execute SQLSetup and execute DB2 CommandsUnderstand DB2 LoggingDescribe DB2 program preparation processUnderstand DB2 startup and shutdownUnderstand and utilize DB2 recovery strategies This course is intended for students looking to develop fundamental skills or recognition through lectures and hands-on exercises of TSO/E and ISPF, data sets, DB2 objects, Structured Query Language, DB2 commands, JCL and SDSF. Day 1 Welcome Unit 1: Introduction Unit 2: TSO/E and ISPF Exercise 1: TSO and ISPF Exercise 1 Review Unit 3: Data Sets (Data Sets and Sequential Data Sets) Exercise 2: Sequential Data Sets Exercise 2 Review Day 2 Unit 3: Data Sets (Partitioned Data Sets) Exercise 3: Partitioned Data Sets Exercise 3 Review Unit 3: Data Sets (VSAM Data Sets) Exercise 4: VSAM Data Sets Exercise 4 Review Unit 4: JCL and SDSF Exercise 5: JCL and SDSF Exercise 5 Review Day 3 Unit 5: DB2 Relational Database Concepts Unit 6: Structured Query Language (SQL) and SPUFI Exercise 6: SQL and SPUFI Exercise 6 Review Unit 7: DB2 Objects (Databases and Table Spaces) Exercise 7: Databases and Table Spaces Exercise 7 Review Unit 7: DB2 Objects (Tables, Indexes, and Views) Exercise 8: Tables, Indexes, and Views Exercise 8 Review Day 4 Unit 7: DB2 Objects (Qualified Names, Implicit Object Creation, and SQL Statements) Exercise 9: Qualified Names, Implicit Object Creation, and SQL Statements Exercise 9 Review Unit 8: The DB2 System Exercise 10: The DB2 System Exercise 10 Review Unit 9: DB2 Commands and Program Preparation Exercise 11: DB2 Commands Exercise 11 Review Day 5 Unit 10: DB2 Utilities Exercise 12: DB2 Utilities Exercise 12 Review Unit 11: DB2 Shutdown, Startup, and Recovery Exercise 13: DB2 Recovery Exercise 13 Review Unit 12: Course Summary Additional course details: Nexus Humans CV041 IBM z/OS and DB2 Basics for DB2 for z/OS DBA Beginners 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 CV041 IBM z/OS and DB2 Basics for DB2 for z/OS DBA Beginners 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 workshop is designed for data scientists who currently use Python or R to work with smaller datasets on a single machine and who need to scale up their analyses and machine learning models to large datasets on distributed clusters. Data engineers and developers with some knowledge of data science and machine learning may also find this workshop useful. Overview Overview of data science and machine learning at scale Overview of the Hadoop ecosystem Working with HDFS data and Hive tables using Hue Introduction to Cloudera Data Science Workbench Overview of Apache Spark 2 Reading and writing data Inspecting data quality Cleansing and transforming data Summarizing and grouping data Combining, splitting, and reshaping data Exploring data Configuring, monitoring, and troubleshooting Spark applications Overview of machine learning in Spark MLlib Extracting, transforming, and selecting features Building and evaluating regression models Building and evaluating classification models Building and evaluating clustering models Cross-validating models and tuning hyperparameters Building machine learning pipelines Deploying machine learning models Spark, Spark SQL, and Spark MLlib PySpark and sparklyr Cloudera Data Science Workbench (CDSW) Hue This workshop covers data science and machine learning workflows at scale using Apache Spark 2 and other key components of the Hadoop ecosystem. The workshop emphasizes the use of data science and machine learning methods to address real-world business challenges. Using scenarios and datasets from a fictional technology company, students discover insights to support critical business decisions and develop data products to transform the business. The material is presented through a sequence of brief lectures, interactive demonstrations, extensive hands-on exercises, and discussions. The Apache Spark demonstrations and exercises are conducted in Python (with PySpark) and R (with sparklyr) using the Cloudera Data Science Workbench (CDSW) environment. The workshop is designed for data scientists who currently use Python or R to work with smaller datasets on a single machine and who need to scale up their analyses and machine learning models to large datasets on distributed clusters. Data engineers and developers with some knowledge of data science and machine learning may also find this workshop useful. Overview of data science and machine learning at scaleOverview of the Hadoop ecosystemWorking with HDFS data and Hive tables using HueIntroduction to Cloudera Data Science WorkbenchOverview of Apache Spark 2Reading and writing dataInspecting data qualityCleansing and transforming dataSummarizing and grouping dataCombining, splitting, and reshaping dataExploring dataConfiguring, monitoring, and troubleshooting Spark applicationsOverview of machine learning in Spark MLlibExtracting, transforming, and selecting featuresBuilding and evauating regression modelsBuilding and evaluating classification modelsBuilding and evaluating clustering modelsCross-validating models and tuning hyperparametersBuilding machine learning pipelinesDeploying machine learning models Additional course details: Nexus Humans Cloudera Data Scientist Training training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Cloudera Data Scientist Training 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 To fully benefit from this course, you should have three to five years of experience designing and implementing applications that are built on top of Cisco platforms. This course is appropriate for: Network engineers expanding their skill-base to include software and automation Developers expanding expertise in automation and DevOps Solution architects moving to the Cisco ecosystem Infrastructure developers designing hardened production environments The job roles best suited to the material in this course are: Senior network automation engineer Senior software developer Senior system integration programmer Additional job roles that could find this course useful are: Senior infrastructure architect Senior network designer Senior test development engineer Students preparing for Cisco Certified DevNet Professional and Cisco Certified DevNet Specialist - Core certification will also find this material useful. Overview After taking this course, you should be able to: Describe the architectural traits and patterns that improve application maintainability Describe the architectural traits and patterns that improve application serviceability Identify steps to design and build a ChatOps application Implement robust Representational State Transfer (REST) API integrations with network error handling, pagination, and error flow control Describe the necessary steps for securing user and system data in applications Describe the necessary steps for securing applications Identify common tasks in automated application release process Describe best practices for application deployment Describe methodologies for designing distributed systems Describe the concepts of infrastructure configuration management and device automation Utilize Yet Another Next Generation (YANG) data models to describe network configurations and telemetry Compare various relational and nonrelational database types and how to select the appropriate type based on requirements In this course, you will learn how to implement network applications using Cisco© platforms as a base, from initial software design to diverse system integration, as well as testing and deployment automation. The course gives you hands-on experience solving real world problems using Cisco Application Programming Interfaces (APIs) and modern development tools. This course helps you prepare for Cisco DevNet Professional certification and for professional-level network automation engineer roles. COURSE OUTLINE DESIGNING FOR MAINTAINABILITY (SELF-STUDY) DESIGNING FOR SERVICEABILITY (SELF-STUDY) IMPLEMENTING CHATOPS APPLICATION DESCRIBING ADVANCED REST API INTEGRATION SECURING APPLICATION DATA (SELF-STUDY) SECURING WEB AND MOBILE APPLICATIONS (SELF-STUDY) AUTOMATING APPLICATION-RELEASE DEPLOYING APPLICATIONS UNDERSTANDING DISTRIBUTED SYSTEMS ORCHESTRATING NETWORK AND INFRASTRUCTURE MODELING DATA WITH YANG USING RELATIONAL AND NON-RELATIONAL DATABASES (SELF-STUDY) PLEASE NOTE:This class includes lecture sections and self-study sections. In instructor-led classes, lectures are delivered in real-time, either in person or via video conferencing. In e-learning courses, the lectures are on recorded videos. In both versions, you will need to review self-study sections on your own before taking the certification exam. Additional course details: Nexus Humans Cisco Developing Applications Using Cisco Core Platforms and APIs v1.0 (DEVCOR) 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 Developing Applications Using Cisco Core Platforms and APIs v1.0 (DEVCOR) 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.