682 PIP courses delivered Online

Duration 3 Days 18 CPD hours This course is intended for Experienced system administrators and network administrators Overview By the end of the course, you should be able to meet the following objectives: Describe the NSX Advanced Load Balancer architecture, components, and main functions Explain the key features and benefits of NSX Advanced Load Balancer Explain and configure local load-balancing constructs such as virtual services, pools, health monitors, and related components Recognize web application breaches and threats Recognize multiple attack vectors such as web scraping, Layer 7 Denial of Service, brute force, and code injections Explain the components of NSX Advanced Load Balancer WAF that build a security pipeline to protect a web application from being attacked Describe how to configure the NSX Advanced Load Balancer WAF components Describe an NSX Advanced Load Balancer WAF operational task such as setting up an application with WAF, tuning the WAF Policy, and working with logs and analytics Explain the NSX Advanced Load Balancer WAF best practices for on-boarding a web application; configuring WAF settings for effective application security Explain how to size the NSX Advanced Load Balancer WAF data plane Explain the WAF Application learning feature, configuration of Application learning, Virtual Patching concepts, common caveats, and troubleshooting while deploying in any environment Recognize NSX Advanced Load Balancer Cloud Services that include threat Intelligence services Describe the Threat Intelligence service provided by NSX Advanced Load Balancer WAF and how the NSX Advanced Load Balancer WAF Threat Intelligence service receives live security threat feed for multiple attack vectors from Cloud Services (formerly Avi Pulse) Describe the NSX Advanced Load Balancer DataScript capabilities for detecting and defending against advance and zero-day attacks. Discuss the relevant NSX Advanced Load Balancer WAF logs and perform basic troubleshooting of applications that are protected by NSX Advanced Load Balancer WAF Explain the NSX Advanced Load Balancer WAF capability to protect Personally Identifiable Information (PII) This three-day course provides comprehensive training to install, configure, and manage a VMware NSX Advanced Load Balancer Web Application Firewall (WAF) solution. This course covers key NSX Advanced Load Balancer WAF features and functionality offered in the NSX Advanced Load Balancer 22.1.3 release for web security and application attack protection. Features include security pipeline, application learning, policy tuning, false positive mitigation, virtual patching, threat intelligence, troubleshooting, logs, analytics, and solution monitoring. Hands-on labs provide access to an NSX Advanced Load Balancer environment to reinforce the skills and concepts presented in the course. Course Introduction Introduction and course logistics Course objectives Introduction to NSX Advanced Load Balancer Illustrate NSX Advanced Load Balancer Explain NSX Advanced Load Balancer architecture and components Describe control plane clustering and high availability Describe data plane high availability mode Understand the common terminologies used with NSX Advanced Load Balancer Explain the NSX Advanced Load Balancer service elements Explain virtual service components and how to configure a virtual service Explain application profiles and network profiles Explain the pool configuration options and how to configure a pool Explain the available load-balancing algorithms Explain and configure SSL profiles and certificates Explain cloud connectors and cloud connector integration modes Explain multiple health monitor types Understand client logs Introduction to Application Security Understand web application security breaches and the implication of breaches Explain common terminologies related to Web Application Security Understand the different teams involved to secure applications Attacking Web Applications Understand the various web application security testing methodologies Understand the OWASP Top 10 vulnerabilities Understand the tools to generate a web application attack Describe a few types of web application attacks Types of Transport Understand different web traffic transport modes Describe web traffic and API traffic NSX Advanced Load Balancer WAF Components Understand the core design principles of NSX Advanced Load Balancer WAF Describe the NSX Advanced Load Balancer WAF components that build the WAF security pipeline Understand the NSX Advanced Load Balancer WAF configuration objects NSX Advanced Load Balancer WAF Operations Examine how to set up an application with WAF Describe considerations for the WAF policy Work with WAF logs and analytics Describe WAF policy tuning Describe the options available to remediate false positive mitigation NSX Advanced Load Balancer WAF Best Practices Describe technical and application considerations for onboarding an application front ended by WAF Describe best practices to remediate false positive mitigation. Describe how to manage a response from a back-end application server and client upload to the application server Describe the consideration for setting the rigidity of a WAF signature rule set Describe the options available to identify client traffic NSX Advanced Load Balancer WAF Sizing Understand how to do WAF data plane sizing in Greenfield and Brownfield deployments NSX Advanced Load Balancer WAF Custom Rules Understand WAF custom rules Describe the need and recommendation for custom rules Describe ModSecurity rules Understand the ModSecurity rule structure and explain how to construct the rule Analyze a sample custom rule for the use-case scenario for in-depth understanding of a custom rule NSX Advanced Load Balancer WAF Application Learning Understand the significance of Application Learning Explain the Positive Security Model architecture Describe the WAF multifaceted Application Learning technique to build an application model for creating positive security rules Describe how to view the data that is learned by the Application learning module Describe the WAF Virtual Patching technique to construct a WAF policy from Dynamic Application Security Testing (DAST) scanner results Understand the conditions for sharing WAF Learning Data and PSM Group in WAF Policy. Malware Protection Through ICAP in NSX Advanced Load Balancer Understand Malicious File Upload Protection and ICAP workflow Describe ICAP configuration and log analytics NSX Advanced Load Balancer IP Reputation Understand IP Reputation concepts and their integration with NSX Advanced Load Balancer Describe IP Reputation configuration, log analytics, and troubleshooting DataScript for Application Security Describe DataScript events and reference Describe application security using DataScript Explain how to troubleshoot DataScript issues Rate Limiting and DOS Describe and configure the NSX Advanced Load Balancer rate limiter technique Describe protection from denial of service (DoS) attacks and distributed DoS (DDoS) attacks in NSX Advanced Load Balancer Explain the Service Engine general advice and guidance for DDOS Bot Management Understand Bots Describe the Bot Management mechanism in NSX Advanced Load Balancer Describe how to configure NSX Advanced Load Balancer Bot Management Managing Personally Identifiable Information in NSX Advanced Load Balancer Understand Personally Identifiable Information (PII) Understand the scope of managing PII in NSX Advanced Load Balancer Describe how to configure the hidden PII in NSX Advanced Load Balancer logs using profiles and WAF rules. Threat Intelligence Introduce the Threat Intelligence service Describe the Threat Intelligence live security threat feed for multiple attack vectors Describe how to configure Threat Intelligence in NSX Advanced Load Balancer Application Programming Interface Security Define Application Programming Interface (API) Security Understand API authentication and authorization using virtual service authentication mechanisms used for a virtual service such as LDAP, SAML, JSON Web Token, and OAUTH Understand API Rate Limiting in NSX Advanced Load Balancer Understand the NSX Advanced Load Balancer WAF Protection for API Additional course details:Notes Delivery by TDSynex, Exit Certified and New Horizons an VMware Authorised Training Centre (VATC) Nexus Humans VMware NSX Advanced Load Balancer: Web Application Firewall Security [V22.x] 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 VMware NSX Advanced Load Balancer: Web Application Firewall Security [V22.x] course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 1 Days 6 CPD hours This course is intended for This course is designed for sales representatives who are managing their sales territories, with the goal of converting sales leads into sales opportunities and sales opportunities into closed sales. You may be selling products or services, or you may or may not be familiar with other CRM systems and may be new to Salesforce CRM. Overview In this course, students will create and manage records in the trial version of Salesforce© Sales Cloud© Lightning Enterprise Edition.Students will:- Create a basic Salesforce Sales Cloud environment and navigate the interface.- Optimize lead qualification.- Manage accounts and contacts.- Manage the opportunity pipeline.- Use Salesforce email.- Work with reports and dashboards. This course will give students the knowledge and skills they need to use Salesforce© in the real world?ultimately enabling them to meet and exceed their sales targets. Getting Started with Salesforce Set Up a Trial Version of Salesforce Sales Cloud Enterprise Edition Navigate the Salesforce LE Interface Navigate in the Salesforce Classic Interface Optimizing Lead Qualification View Leads Manage Leads Work Leads Convert Leads Managing Accounts and Contacts Manage Accounts Manage Contacts Managing the Opportunity Pipeline Manage Opportunities Work Opportunities Close Opportunities Using Salesforce Email Use Salesforce Email in Salesforce Classic Use Salesforce Email in Salesforce LE Working with Reports and Dashboards View Reports and Dashboards Create and Edit Reports and Dashboards

Duration 2 Days 12 CPD hours This course is intended for Developers, Data Engineers, Architects, and Administrators Overview Join an engaging hands-on learning environment, where you'll learn: Splunk essentials Indexing in Splunk Splunk architecture and components Query and search your data How to create dashboards and visualizations How to apply alerts This is a hands-on course with engaging instruction, demos, group discussions, labs, and project work. Join an engaging hands-on learning environment, where you?ll learn - Splunk essentials Indexing in Splunk Splunk architecture and components Query and search your data How to create dashboards and visualizations How to apply alerts This is a hands-on course with engaging instruction, demos, group discussions, labs, and project work. Introduction to Splunk What?s Splunk? What?s Splunk? Authentication Methods Access Controls and Users Products, Licensing, and Costs Quick Tour Guide: User Interface Indexes Splunk Data What are Indexes? Search-Head Index Clusters Index Pipeline Events Fields and Field Extraction Forwarders Metrics Removing Data Splunk Architecture Components of Splunk Deployments Deployment Scenarios Search Processing Language What is Search Processing Language (SPL)? Searching Operators Search Commands Search Pipeline Sub-searches Commonly Used Search Commands Drilldowns Lookups Optimize Searches Dashboard and Visualizations Dashboards in Splunk Creating Dashboards Visualization Types Search as Reports Dashboards Drilldown Forms Alerts Creating Alerts Scheduling Alerts Alerts Notifications Scheduled Reports Creating Scheduled Reports Putting the Pieces Together In your final exercise, you?ll configure a typical scenario when using Splunk. You'll install and configure an NGINX, then the Splunk forwarder to collect logs in Splunk. The idea is that you can apply everything you've learned within the Bootcamp: creating searches, visualizations, dashboards, etc.

Duration 5 Days 30 CPD hours This course is intended for This class is designed for experienced BizTalk Server Developers who have at least one year of hands-on experience developing BizTalk Server applications. Overview In this 5-day course, you will learn how to apply best practices and design patterns to build smarter BizTalk Server applications. Furthermore, this course provides extensive coverage of BizTalk Server's extensibility, including such topics as: custom functoids, custom pipeline components, and invoking external .NET methods. This course is designed specifically for experienced BizTalk Server developers and focuses on best practices & pattern-based design while pulling back the curtain on some of BizTalk Server's eccentricities. Review of BizTalk Server Fundamentals The BizTalk Server Architecture Inner Workings of the Messaging Engine Messaging Engine Deep Dive Two-way Messaging Without Orchestrations Designing and Testing Schemas Schema Design Enabling Unit Testing for BizTalk Projects Data Translation and Transformation Custom Data Transformation Creating Custom Pipeline Components Working with Message Interchanges Debatching Message Interchanges Advanced Concepts of WCF Adapters Connecting to External Systems Using WCF LOB Adapters in BizTalk Server Publishing and Consuming WCF and RESTful Services Overview of Service Integration Using WCF Implementing WCF Services Preprocessing Messages with IIS Modules Consuming Services Advanced Orchestration Communication Patterns Orchestration Engine Deep Dive Splitting and Aggregating Messages using Orchestrations Orchestration Communication Bridging the Synchronous/Asynchronous Gap Across Multiple Channels Correlating Messages in Orchestration Instances Building Convoy Orchestrations Handling Orchestration Faults and Exceptions Exception Handling in Orchestrations Implementing Transactions and Compensation Creating Transactional Processes Designing Custom Tracking Models for BizTalk Applications Introduction to Business Activity Monitoring Enabling Business Activity Monitoring Extending BAM Beyond BizTalk Building Declarative Logic Using the Business Rules Engine Concepts of Declarative Logic Fundamentals of BizTalk BRE Integrating Policies with BizTalk Advanced Concepts of the Business Rules Engine Advanced Business Rule Concepts Working with Advanced Facts Integrating Across Business Boundaries Using Parties, Roles, and EDI Port Binding Option Review Role-Based Integration What is EDI? Enabling EDI-Based Messaging

Duration 5 Days 30 CPD hours This course is intended for The Messaging Administrator deploys, configures, manages, and troubleshoots recipients, permissions, mail protection, mail flow, and public folders in both on-premises and cloud enterprise environments. Responsibilities include managing message hygiene, messaging infrastructure, and hybrid configuration and migration. To implement a secure hybrid topology that meets the business needs of a modern organization, the Messaging Administrator must collaborate with the Security Administrator and Microsoft 365 Enterprise Administrator. The Messaging Administrator should have a working knowledge of authentication types, licensing, and integration with Microsoft 365 applications. Overview After completing this course, students will be able to: Configure and manage the transport pipeline Manage and troubleshoot mail flow and transport issues Manage message hygiene and compliance Manage authentication for messaging Configure organizational settings and sharing Manage mobile devices Manage role-based permissions Create and manage recipient objects and resources Plan, implement, and troubleshoot public folders Plan a hybrid environment Perform mailbox migrations Deploy and troubleshoot a hybrid environment This course examines the key elements of Microsoft 365 messaging administration, including message transport and mail flow, messaging security, hygiene, and compliance, messaging infrastructure, and hybrid messaging. This course is designed for IT Professionals who deploy and manage the messaging infrastructure for Microsoft 365 in their organization. Managing the Transport Pipeline Overview of Transport Services Configuring Message Transport Managing Transport Rules Managing and Troubleshooting Mail Flow Managing Mail Flow Troubleshooting Mail Flow Troubleshooting Transport Issues Troubleshooting with Logs Managing Message Hygiene Planning for Message Hygiene Managing Anti-Malware and Anti-Spam Policies Managing Advanced Threat Protection Managing Compliance Messaging Compliance in the SCC Messaging Compliance in Exchange Managing Exchange Online Archiving and Auditing Managing Content Search Managing Organizational Settings Managing Authentication for Messaging Configuring Organizational Settings Configuring Organizational Sharing Managing Mobile Devices Mobile Device Mailbox Policies Managing Mobile Device Access Managing Role-Based Permissions Managing Admin Roles Managing User Roles Exchange Setup - RBAC and AD Split Permission Managing Recipient Objects and Resources Exchange Recipients Creating and Managing Exchange Recipients Managing Email Addresses, Lists, and Resources Managing Public Folders Planning the Public Folder Hierarchy Implementing and Managing Public Folders Troubleshooting Public Folders Planning a Hybrid Environment Exchange Hybrid Deployment Requirements Planning to Run the Hybrid Configuration Wizard Performing Mailbox Migrations Planning Mailbox Migrations Performing IMAP Migrations Performing Cutover and Staged Migrations Performing Advanced Migrations Deploying and Troubleshooting a Hybrid Environment Deploying and Managing an Edge Transport Server Configuring a Hybrid Deployment using the HCW Implementing Advanced Hybrid Functionality Troubleshooting Hybrid Deployments

Duration 5 Days 30 CPD hours This course is intended for The primary audience for this course is individuals who administer and maintain SQL Server databases. These individuals perform database administration and maintenance as their primary area of responsibility, or work in environments where databases play a key role in their primary job. The secondary audiences for this course are individuals who develop applications that deliver content from SQL Server databases. Overview After completing this course, you will be able to: Authenticate and authorize users Assign server and database roles Authorize users to access resources Use encryption and auditing features to protect data Describe recovery models and backup strategies Backup and Restore SQL Server databases Automate database management Configure security for the SQL Server agent Manage alerts and notifications Managing SQL Server using PowerShell Trace access to SQL Server Monitor a SQL Server infrastructure Troubleshoot a SQL Server infrastructure Import and export data This course will provide training in how to administer and maintain SQL Server, Azure SQL Database and other cloud-based SQL Server databases. IT professionals who work in environments where databases play a key role in their job will find this material useful. By using demonstrations and hands-on lab exercises, students will learn to carry out these important tasks. This course covers content that was in retired Microsoft Course 20764: Administering a SQL Database Infrastructure. 1 - Creating advanced functions Lesson 1: Converting a command into an advanced function Lesson 2: Creating a script module Lesson 3: Defining parameter attributes and input validation Lesson 4: Writing functions that accept pipeline input Lesson 5: Producing complex pipeline output Lesson 6: Using comment-based Help Lesson 7: Using Whatif and Confirm parameters 2 - Using Microsoft .NET Framework and REST API in Windows PowerShell Lesson 1: Using .NET Framework in PowerShell Lesson 2: Using REST API in PowerShell 3 - Writing controller scripts Lesson 1: Understanding controller scripts Lesson 2: Writing controller scripts with a user interface Lesson 3: Writing controller scripts that create reports 4 - Handling script errors Lesson 1: Understanding error handling Lesson 2: Handling errors in a script 5 - Using XML, JSON, and custom-formatted data Lesson 1: Working with XML formatted data Lesson 2: Working with JSON formatted data Lesson 3: Working with custom-formatted data 6 - Enhancing server management with Desired State Configuration and Just Enough Administration Lesson 1: Implementing Desired State Configuration Lesson 2: Implementing Just Enough Administration 7 - Analyzing and debugging scripts Lesson 1: Debugging in Windows PowerShell Lesson 2: Analyzing and debugging an existing script 8 - Understanding Windows PowerShell Workflow Lesson 1: Understanding Windows PowerShell Workflows Lesson 2: Running Windows PowerShell Workflows

Duration 4 Days 24 CPD hours This course is intended for This course is best suited to developers, engineers, and architects who want to use use Hadoop and related tools to solve real-world problems. Overview Skills learned in this course include:Creating a data set with Kite SDKDeveloping custom Flume components for data ingestionManaging a multi-stage workflow with OozieAnalyzing data with CrunchWriting user-defined functions for Hive and ImpalaWriting user-defined functions for Hive and ImpalaIndexing data with Cloudera Search Cloudera University?s four-day course for designing and building Big Data applications prepares you to analyze and solve real-world problems using Apache Hadoop and associated tools in the enterprise data hub (EDH). IntroductionApplication Architecture Scenario Explanation Understanding the Development Environment Identifying and Collecting Input Data Selecting Tools for Data Processing and Analysis Presenting Results to the Use Defining & Using Datasets Metadata Management What is Apache Avro? Avro Schemas Avro Schema Evolution Selecting a File Format Performance Considerations Using the Kite SDK Data Module What is the Kite SDK? Fundamental Data Module Concepts Creating New Data Sets Using the Kite SDK Loading, Accessing, and Deleting a Data Set Importing Relational Data with Apache Sqoop What is Apache Sqoop? Basic Imports Limiting Results Improving Sqoop?s Performance Sqoop 2 Capturing Data with Apache Flume What is Apache Flume? Basic Flume Architecture Flume Sources Flume Sinks Flume Configuration Logging Application Events to Hadoop Developing Custom Flume Components Flume Data Flow and Common Extension Points Custom Flume Sources Developing a Flume Pollable Source Developing a Flume Event-Driven Source Custom Flume Interceptors Developing a Header-Modifying Flume Interceptor Developing a Filtering Flume Interceptor Writing Avro Objects with a Custom Flume Interceptor Managing Workflows with Apache Oozie The Need for Workflow Management What is Apache Oozie? Defining an Oozie Workflow Validation, Packaging, and Deployment Running and Tracking Workflows Using the CLI Hue UI for Oozie Processing Data Pipelines with Apache Crunch What is Apache Crunch? Understanding the Crunch Pipeline Comparing Crunch to Java MapReduce Working with Crunch Projects Reading and Writing Data in Crunch Data Collection API Functions Utility Classes in the Crunch API Working with Tables in Apache Hive What is Apache Hive? Accessing Hive Basic Query Syntax Creating and Populating Hive Tables How Hive Reads Data Using the RegexSerDe in Hive Developing User-Defined Functions What are User-Defined Functions? Implementing a User-Defined Function Deploying Custom Libraries in Hive Registering a User-Defined Function in Hive Executing Interactive Queries with Impala What is Impala? Comparing Hive to Impala Running Queries in Impala Support for User-Defined Functions Data and Metadata Management Understanding Cloudera Search What is Cloudera Search? Search Architecture Supported Document Formats Indexing Data with Cloudera Search Collection and Schema Management Morphlines Indexing Data in Batch Mode Indexing Data in Near Real Time Presenting Results to Users Solr Query Syntax Building a Search UI with Hue Accessing Impala through JDBC Powering a Custom Web Application with Impala and Search

Duration 3 Days 18 CPD hours This course is intended for Senior Executives CIOs and CTOs Business Intelligence Executives Marketing Executives Data & Business Analytics Specialists Innovation Specialists & Entrepreneurs Academics, and other people interested in Big Data Overview More specifically, BDAW addresses advanced big data architecture topics, including, data formats, transformation, real-time, batch and machine learning processing, scalability, fault tolerance, security and privacy, minimizing the risk of an unsound architecture and technology selection. Big Data Architecture Workshop (BDAW) is a learning event that addresses advanced big data architecture topics. BDAW brings together technical contributors into a group setting to design and architect solutions to a challenging business problem. The workshop addresses big data architecture problems in general, and then applies them to the design of a challenging system. Throughout the highly interactive workshop, students apply concepts to real-world examples resulting in detailed synergistic discussions. The workshop is conducive for students to learn techniques for architecting big data systems, not only from Cloudera?s experience but also from the experiences of fellow students. Workshop Application Use Cases Oz Metropolitan Architectural questions Team activity: Analyze Metroz Application Use Cases Application Vertical Slice Definition Minimizing risk of an unsound architecture Selecting a vertical slice Team activity: Identify an initial vertical slice for Metroz Application Processing Real time, near real time processing Batch processing Data access patterns Delivery and processing guarantees Machine Learning pipelines Team activity: identify delivery and processing patterns in Metroz, characterize response time requirements, identify Machine Learning pipelines Application Data Three V?s of Big Data Data Lifecycle Data Formats Transforming Data Team activity: Metroz Data Requirements Scalable Applications Scale up, scale out, scale to X Determining if an application will scale Poll: scalable airport terminal designs Hadoop and Spark Scalability Team activity: Scaling Metroz Fault Tolerant Distributed Systems Principles Transparency Hardware vs. Software redundancy Tolerating disasters Stateless functional fault tolerance Stateful fault tolerance Replication and group consistency Fault tolerance in Spark and Map Reduce Application tolerance for failures Team activity: Identify Metroz component failures and requirements Security and Privacy Principles Privacy Threats Technologies Team activity: identify threats and security mechanisms in Metroz Deployment Cluster sizing and evolution On-premise vs. Cloud Edge computing Team activity: select deployment for Metroz Technology Selection HDFS HBase Kudu Relational Database Management Systems Map Reduce Spark, including streaming, SparkSQL and SparkML Hive Impala Cloudera Search Data Sets and Formats Team activity: technologies relevant to Metroz Software Architecture Architecture artifacts One platform or multiple, lambda architecture Team activity: produce high level architecture, selected technologies, revisit vertical slice Vertical Slice demonstration Additional course details: Nexus Humans Big Data Architecture Workshop 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 Big Data Architecture Workshop 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 The skills covered in this course converge on four areas-software development, IT operations, applied math and statistics, and business analysis. Target students for this course should be looking to build upon their knowledge of the data science process so that they can apply AI systems, particularly machine learning models, to business problems. So, the target student is likely a data science practitioner, software developer, or business analyst looking to expand their knowledge of machine learning algorithms and how they can help create intelligent decisionmaking products that bring value to the business. A typical student in this course should have several years of experience with computing technology, including some aptitude in computer programming. This course is also designed to assist students in preparing for the CertNexus Certified Artificial Intelligence (AI) Practitioner (Exam AIP-210) certification Overview In this course, you will develop AI solutions for business problems. You will: Solve a given business problem using AI and ML. Prepare data for use in machine learning. Train, evaluate, and tune a machine learning model. Build linear regression models. Build forecasting models. Build classification models using logistic regression and k -nearest neighbor. Build clustering models. Build classification and regression models using decision trees and random forests. Build classification and regression models using support-vector machines (SVMs). Build artificial neural networks for deep learning. Put machine learning models into operation using automated processes. Maintain machine learning pipelines and models while they are in production Artificial intelligence (AI) and machine learning (ML) have become essential parts of the toolset for many organizations. When used effectively, these tools provide actionable insights that drive critical decisions and enable organizations to create exciting, new, and innovative products and services. This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, all while following a methodical workflow for developing data-driven solutions. Solving Business Problems Using AI and ML Topic A: Identify AI and ML Solutions for Business Problems Topic B: Formulate a Machine Learning Problem Topic C: Select Approaches to Machine Learning Preparing Data Topic A: Collect Data Topic B: Transform Data Topic C: Engineer Features Topic D: Work with Unstructured Data Training, Evaluating, and Tuning a Machine Learning Model Topic A: Train a Machine Learning Model Topic B: Evaluate and Tune a Machine Learning Model Building Linear Regression Models Topic A: Build Regression Models Using Linear Algebra Topic B: Build Regularized Linear Regression Models Topic C: Build Iterative Linear Regression Models Building Forecasting Models Topic A: Build Univariate Time Series Models Topic B: Build Multivariate Time Series Models Building Classification Models Using Logistic Regression and k-Nearest Neighbor Topic A: Train Binary Classification Models Using Logistic Regression Topic B: Train Binary Classification Models Using k-Nearest Neighbor Topic C: Train Multi-Class Classification Models Topic D: Evaluate Classification Models Topic E: Tune Classification Models Building Clustering Models Topic A: Build k-Means Clustering Models Topic B: Build Hierarchical Clustering Models Building Decision Trees and Random Forests Topic A: Build Decision Tree Models Topic B: Build Random Forest Models Building Support-Vector Machines Topic A: Build SVM Models for Classification Topic B: Build SVM Models for Regression Building Artificial Neural Networks Topic A: Build Multi-Layer Perceptrons (MLP) Topic B: Build Convolutional Neural Networks (CNN) Topic C: Build Recurrent Neural Networks (RNN) Operationalizing Machine Learning Models Topic A: Deploy Machine Learning Models Topic B: Automate the Machine Learning Process with MLOps Topic C: Integrate Models into Machine Learning Systems Maintaining Machine Learning Operations Topic A: Secure Machine Learning Pipelines Topic B: Maintain Models in Production

Duration 1 Days 6 CPD hours This course is intended for This course is intended for the following participants:Cloud professionals interested in taking the Data Engineer certification exam.Data engineering professionals interested in taking the Data Engineer certification exam. Overview This course teaches participants the following skills: Position the Professional Data Engineer Certification Provide information, tips, and advice on taking the exam Review the sample case studies Review each section of the exam covering highest-level concepts sufficient to build confidence in what is known by the candidate and indicate skill gaps/areas of study if not known by the candidate Connect candidates to appropriate target learning This course will help prospective candidates plan their preparation for the Professional Data Engineer exam. The session will cover the structure and format of the examination, as well as its relationship to other Google Cloud certifications. Through lectures, quizzes, and discussions, candidates will familiarize themselves with the domain covered by the examination, to help them devise a preparation strategy. Rehearse useful skills including exam question reasoning and case comprehension. Tips and review of topics from the Data Engineering curriculum. Understanding the Professional Data Engineer Certification Position the Professional Data Engineer certification among the offerings Distinguish between Associate and Professional Provide guidance between Professional Data Engineer and Associate Cloud Engineer Describe how the exam is administered and the exam rules Provide general advice about taking the exam Sample Case Studies for the Professional Data Engineer Exam Flowlogistic MJTelco Designing and Building (Review and preparation tips) Designing data processing systems Designing flexible data representations Designing data pipelines Designing data processing infrastructure Build and maintain data structures and databases Building and maintaining flexible data representations Building and maintaining pipelines Building and maintaining processing infrastructure Analyzing and Modeling (Review and preparation tips) Analyze data and enable machine learning Analyzing data Machine learning Machine learning model deployment Model business processes for analysis and optimization Mapping business requirements to data representations Optimizing data representations, data infrastructure performance and cost Reliability, Policy, and Security (Review and preparation tips) Design for reliability Performing quality control Assessing, troubleshooting, and improving data representation and data processing infrastructure Recovering data Visualize data and advocate policy Building (or selecting) data visualization and reporting tools Advocating policies and publishing data and reports Design for security and compliance Designing secure data infrastructure and processes Designing for legal compliance Resources and next steps Resources for learning more about designing data processing systems, data structures, and databases Resources for learning more about data analysis, machine learning, business process analysis, and optimization Resources for learning more about data visualization and policy Resources for learning more about reliability design Resources for learning more about business process analysis and optimization Resources for learning more about reliability, policies, security, and compliance Additional course details: Nexus Humans Preparing for the Professional Data Engineer Examination 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 Preparing for the Professional Data Engineer Examination 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.