451 Developer courses in Cardiff delivered Live Online

Duration 3 Days 18 CPD hours This course is intended for Data Science for Marketing Analytics is designed for developers and marketing analysts looking to use new, more sophisticated tools in their marketing analytics efforts. It'll help if you have prior experience of coding in Python and knowledge of high school level mathematics. Some experience with databases, Excel, statistics, or Tableau is useful but not necessary. Overview By the end of this course, you will be able to build your own marketing reporting and interactive dashboard solutions. The course starts by teaching you how to use Python libraries, such as pandas and Matplotlib, to read data from Python, manipulate it, and create plots, using both categorical and continuous variables. Then, you'll learn how to segment a population into groups and use different clustering techniques to evaluate customer segmentation.As you make your way through the course, you'll explore ways to evaluate and select the best segmentation approach, and go on to create a linear regression model on customer value data to predict lifetime value. In the concluding sections, you'll gain an understanding of regression techniques and tools for evaluating regression models, and explore ways to predict customer choice using classification algorithms. Finally, you'll apply these techniques to create a churn model for modeling customer product choices. Data Preparation and Cleaning Data Models and Structured Data pandas Data Manipulation Data Exploration and Visualization Identifying the Right Attributes Generating Targeted Insights Visualizing Data Unsupervised Learning: Customer Segmentation Customer Segmentation Methods Similarity and Data Standardization k-means Clustering Choosing the Best Segmentation Approach Choosing the Number of Clusters Different Methods of Clustering Evaluating Clustering Predicting Customer Revenue Using Linear Regression Understanding Regression Feature Engineering for Regression Performing and Interpreting Linear Regression Other Regression Techniques and Tools for Evaluation Evaluating the Accuracy of a Regression Model Using Regularization for Feature Selection Tree-Based Regression Models Supervised Learning: Predicting Customer Churn Classification Problems Understanding Logistic Regression Creating a Data Science Pipeline Fine-Tuning Classification Algorithms Support Vector Machine Decision Trees Random Forest Preprocessing Data for Machine Learning Models Model Evaluation Performance Metrics Modeling Customer Choice Understanding Multiclass Classification Class Imbalanced Data Additional course details: Nexus Humans Data Science for Marketing Analytics 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 Data Science for Marketing Analytics 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 designed for IBM Integration Bus administrators and developers who administer IBM Integration Bus. Overview After completing this course, you should be able to:Install and configure an IBM Integration Bus instanceEstablish, maintain, and manage an integration nodeAdminister IBM Integration Bus components and message flow applications by using the IBM Integration web user interface and command interfaceConfigure connectivity to IBM MQ to enable IBM Integration Bus to get messages from, or put messages to, queues on a local or remote queue managerImplement IBM Integration Bus administration and message flow securityUse problem determination aids to diagnose and solve development and runtime errorsUse the IBM Integration web user interface to generate and display message flow statisticsUse IBM MQ or MQTT to publish and subscribe to IBM Integration Bus topicsImplement an IBM Integration Bus global cache to store, reuse, and share data between integration nodesUse workload management policies to adjust the processing speed of messages and control the actions that are taken on unresponsive flows and threadsUse the IBM Integration web user interface and a database to record events and replay messagesEnable an integration node to connect to a database with ODBC and JDBCConfigure a Java Message Services (JMS) provider for use with the JMS nodesConfigure IBM Integration Bus for the secure file transfer protocol (SFTP)Find and install IBM Integration Bus SupportPac components In this course, students learn how to administer IBM Integration Bus on distributed operating systems, such as Windows and AIX, by using the IBM Integration Bus administrative interfaces. Course Outline Course introduction IBM Integration Bus overview Product installation, configuration, and security planning Exercise: Integration node setup and customization Connecting to IBM MQ Exercise: Connecting to IBM MQ Administration in the IBM Integration Toolkit Exercise: Using the IBM Integration Toolkit Administration basics Exercise: Administering the IBM Integration Bus runtime components Implementing IBM Integration Bus administration security Exercise: Using file-based security to control administration access Exercise: Using queue-based security to control administration access Implementing IBM Integration Bus message flow security Administering web services and web service security Exercise: Implementing web services and web services security Diagnosing problems Exercise: Using problem diagnosis tools Exercise: Identifying runtime problems Monitoring the integration node and message flow performance Publish/subscribe implementation overview Exercise: Viewing runtime statistics Configuring IBM Integration Bus for high availability Exercise: Administering workload management policies Monitoring, recording, and replaying message flow events Exercise: Recording and replaying message flow data Extending IBM Integration Bus Course summary Additional course details: Nexus Humans WM646 IBM Integration Bus V10 System Administration 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 WM646 IBM Integration Bus V10 System Administration 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 intended for system administrators, network administrators and application developers responsible for the customization of traffic flow through a BIG-IP system. This course provides networking professionals a functional understanding of iRules development. The course builds on the foundation of the Administering BIG-IP or Configuring LTM course, demonstrating how to logically plan and write iRules to help monitor and manage common tasks involved with processing traffic on the BIG-IP system. Extensive course labs consist of writing, applying and evaluating the effect of iRules on local traffic. This hands-on course includes lectures, labs, and discussions. Module 1: Setting Up the BIG-IP System Introducing the BIG-IP System Initially Setting Up the BIG-IP System Archiving the BIG-IP System Configuration Leveraging F5 Support Resources and Tools Module 2: Getting Started with iRules Customizing Application Delivery with iRules Triggering an iRule Leveraging the DevCentral Ecosystem Creating and Deploying iRules Module 3: Exploring iRule Elements Introducing iRule Constructs Understanding iRule Events and Event Context Working with iRule Commands Logging from an iRule Using SYSLOG-NG (LOG Command) Working with User-Defined Variables Working with Operators and Data Types Working with Conditional Control Structures (IF and SWITCH) Incorporating Best Practices in iRules Module 4: Developing and Troubleshooting iRules Mastering Whitespace and Special Symbols Grouping Strings Developing and Troubleshooting Tips Using Fiddler to Test and Troubleshoot iRules Module 5: Optimizing iRule Execution Understanding the Need for Efficiency Measure iRule Runtime Efficiency Using Timing Statistics Modularizing iRules for Administrative Efficiency Using Procedures to Modularize Code Optimizing Logging Using High-Speed Logging Commands in an iRule Implementing Other Efficiencies Using Looping Control Structures (WHILE, FOR, FOREACH Commands) Module 6: Securing Web Applications with iRules Integrating iRules into Web Application Defense Mitigating HTTP Version Attacks Mitigating Path Traversal Attacks Using iRules to Defends Against Cross-Site Request Forgery (CSRF) Mitigating HTTP Method Vulnerabilities Securing HTTP Cookies with iRules Adding HTTP Security Headers Removing Undesirable HTTP Headers Module 7: Working with Numbers and Strings Understanding Number Forms and Notation Working with Strings (STRING and SCAN Commands) Combining Strings (Adjacent Variables, CONCAT and APPEND Commands) Using iRule String Parsing Functions (FINDSTR, GETFIELD, and SUBSTR Commands) Module 8: Processing the HTTP Payload Reviewing HTTP Headers and Commands Accessing and Manipulating HTTP Headers (HTTP::header Commands) Other HTTP commands (HTTP::host, HTTP::status, HTTP::is_keepalive, HTTP::method, HTTP::version, HTTP::redirect, HTTP::respond, HTTP::uri) Parsing the HTTP URI (URI::path, URI::basename, URI::query) Parsing Cookies with HTTP::cookie Selectively Compressing HTTP Data (COMPRESS Command) Module 9: Working with iFiles and Data Groups Working with iFiles Introducing Data Groups Working with Old Format Data Groups (MATCHCLASS, FINDCLASS) Working with New Format Data Groups (CLASS MATCH, CLASS SEARCH) Module 10: Using iRules with Universal Persistence, Stream, and Statistics Profiles Implementing Universal Persistence (PERSIST UIE Command) Working with the Stream Profile (STREAM Command) Collecting Statistics Using a Statistics Profile (STATS Command) Collecting Statistics Using iStats (ISTATS Command) Module 11: Incorporating Advanced Variables Reviewing the Local Variable Namespace Working with Arrays (ARRAY Command) Using Static and Global Variables Using the Session Table (TABLE Command) Processing Session Table Subtables Counting ?Things? Using the Session Table

Duration 1 Days 6 CPD hours This course is intended for This course is intended for both novice and experienced IT professionals, Network Administrators new to Active Directory, Help Desk Personnel, Network Support Personal, Desktop Support Personal, Managers that oversee IT personnel, Developers that create products that interact with Active Directory and Exchange Administrators. Overview At Course Completion you will Understand the industry standards used in Active Directory and their importance. Recognize the functionality of Domain Controllers and Active Directory Replication mechanisms. Understand Forest, Domain and OU structure. Recognize and understand the role of Active Directory Sites. Skills needed to determine Domain Controller Server versions, Forest and Domain Functional levels. Describe authentication Mechanisms in Active Directory NTLM and Kerberos. Optimize and maintain Group Policy Objects (GPO) used in Active Directory. Understand the functioning of Active Directory Partitions and the Global Catalog. Fundamental understanding of using Active Directory with Cloud Services like Federation Services and Azure. This one-day instructor-led class is intended for IT professionals and IT managers who work with Active Directory or supervise IT professionals that work with Active Directory. Additionally, IT professionals that work with products that integrate with Active Directory such as Exchange can also benefit. In this course, students learn how and why Active Directory was developed by Microsoft, the fundamental architecture, basic design, management, as well as security and fundamentals for cloud integration with services like Azure. Module 1: Principles of Active Directory Development of Active Directory What is X.500 LDAP Active Directory Architecture NTLM and Kerberos Managing operating systems with GPOs, Workplace Join and InTune Active Directory Groups: Domain Local, Global and Universal Using and Managing Active Directory Domain Controllers Forest and Domain Functional Levels Introduction to Active Directory Partitions and the Global Catalog Basic Forest Structure and Design Basic Domain Structure and Design Basic OU Structure and Design Module 2: Fundamentals of WAN management with Active Directory Understanding AD Sites and WAN Traffic Management Basic AD Sites and Logon Traffic Introduction to AD Sites and Replication Traffic Bridgehead Servers and Site Link Objects Site Aware Applications Module 3: Introduction to Active Directory Group Policy Objects Introduction to Group Policy Administrative Templates Fundamental Concepts of GPO Scripts Introduction to Creating and Using GPOs Principles of Managing Multiple GPOs Block, Enforce and Inheritance GPOs and Active Directory Versions Introduction to Controlling and Installing Software with GPOs, SRP and App Locker Module 4: Principles of Active Directory Integration Active Directory and ?The Cloud? User Principle Names, Authentication and Active Directory Federated Services Conclusion, Additional Resources, Labs and Exercises Additional course details: Nexus Humans 55152AC Fundamentals of Active Directory 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 55152AC Fundamentals of Active Directory 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 Overview VMware vSphere: What's New [V8] https://lms.nhcms.neYou will learn essential Terraform concepts including: Writing Terraform HCL code Deploying into common clouds such as AWS, Azure, Docker, Kubernetes, and VMWare Where Terraform fits in the Enterprise CI/CD model Differences between Terraform and Ansible As enterprises seek to deploy and maintain increasingly complex cloud infrastructure, there is a necessity to use ?Infrastructure as Code? (IaC) tools, like Terraform. An open-source, state management tool developed by HashiCorp, Terraform allows developers to use a common coding interface to work through their various clouds safely and efficiently. Attendees will leave being able to write and understand Terraform code (HCL), have a clear understanding of Terraform?s various components and supporting tools, as well as when to reach for Terraform over another IaC tool, such as Ansible. This class prepares you for Terraform Certifcation. Up and Running with Terraform Terraform Overview Defining ?declarative? How to think about Terraform (versus Ansible) Reviewing the Terraform Configuration Running the Terraform Configuration Provisioners Syntax Low Level? HCL syntax Style Conventions Comments Blocks Arguments JSON Configuration Syntax Resources Meta-Arguments depends_on count for_each provider lifecycle Data Sources Variables and Output Input Variables Output Values Local Values Functions String Collection Numeric Encoding Filesystem Date and Time Hash and Crypto IP Network Type Conversion Modules Module Blocks Module Sources Meta Arguments Terraform Templates templatefile Function Template Demonstration Introducing Data Sources Creating an External Data Source Building tftpl template files Expressions Types and Values Strings and Templates Reference to Values Operators Function Calls Conditionals For Expressions Splat Expressions Dynamic Blocks Type Constraints Version Constraints State Understanding the importants of states state storage and locking importing existing resources Remote State What to do when local state is lost CICD Piplines with Terraform Terraform and GitLab pipelines Terraform and Jenkins pipelines Enterprise Case Studies Terraform and Docker Terraform and Kubernetes Terraform and Amazon AWS Terraform and Azure Terraform and VMWare Understanding how to apply Terraform to your unique infrastructure Beyond Basics Intro to Go Programming Terraform Cloud Additional HashiCorp Offerings Backends Secrets Additional course details: Nexus Humans Terraform 101 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 Terraform 101 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 People working in an organization aiming to improve performance, especially in response to digital transformation or disruption. Any roles involved in the creation and delivery of products or services: Leadership and CXO, especially CIO, CTO, CPO, and CVO Transformation and evolution leads and change agents Value stream architects, managers, engineers Scrum Masters, agile and DevOps coaches and facilitators Portfolio, product and project managers, and owners Business analysts Architects, developers, and engineers Release and environment managers IT Ops, service and support desk workers Customer experience and success professionals Overview After completing this course, students will be able to: Describe the origins of value stream management and key concepts such as flow, value, and delivery Describe what value stream management is, why it's needed and the business benefits of its practice Describe how lean, agile, DevOps, and ITSM principles contribute to value stream management Identify and describe value streams, where they start and end, and how they interconnect Identify value stream roles and responsibilities Express value streams visually using mapping techniques, define current and target states and hypothesis backlog Write value stream flow and realization optimization hypotheses and experiments Apply metrics such as touch/processing time, wait/idle time, and cycle time to value streams Understand flow metrics and how to access the data to support data-driven conversations and decisions Examine value realization metrics and aligning to business outcomes, and how to sense and respond to them (outcomes versus outputs) Architect a DevOps toolchain alongside a value stream and data connection points Design a continuous inspection and adaptation approach for organizational evolution The Value Stream Management Foundation course from Value Stream Management Consortium, and offered in partnership with DevOps Institute, is an introductory course taking learners through a value stream management implementation journey. It considers the human, process, and technology aspects of this way of working and explores how optimizing value streams for flow and realization positively impacts organizational performance. History and Evolution of Value Stream Management and its Application Value stream management?s origins Definitions of value stream management Flow Lean and systems thinking and practices Agile, DevOps and other frameworks Research and analysis Identifying Value Streams What is a value stream? Identifying value streams Choosing a value stream Digital value streams Value stream thinking Mapping Value Streams Types of maps Value stream mapping The fuzzy front end Artifacts 10 steps to value stream mapping Mapping and management VSM investment case Limitations of value stream mapping Connecting DevOps Toolchains CICD and the DevOps toolchain Value stream management processes Value stream management platforms DevOps tool categories Building an end-to-end DevOps toolchain Common data model and tools integrations Value Stream Metrics The duality of VSM Downtime in technology Lean, DORA and Flow metrics Definition of Done Value metrics Benefits hypotheses Value streams as profit centers KPIs and OKRs Inspecting the Value Stream 3 Pillars of Empiricism Organizational performance Visibility When to inspect Data and discovery Insights and trends Organizing as Value Streams Value stream alignment Team types and topologies Project to product Hierarchy to autonomy Target Operating Model Value stream people Value stream roles Value stream funding Evolving Value Streams Why now? Transitions VSM capability matrix VSM culture iceberg Learning Making local discoveries global improvements Managing value stream interdependencies

Duration 3 Days 18 CPD hours This course is intended for This course is designed for project leaders, scrum masters, coaches, product owners, and team members who intend on taking the PMI-ACP© exam. This course provides participants with a foundation of the PMI-ACP© exam. Participants will be introduced to PMI Agile concepts and practices with banks of sample questions. PMI-ACP© Exam Preperation PMI-ACP© Exam Particulars Overview PMI-ACP© Exam Particulars PMI-ACP© Candidate Requirements PMI-ACP© Candidate Fees PMI-ACP© Exam Application Process Core Agile Concepts Core Agile Concepts Overview Traditional Project Management Methodologies Drawbacks of Waterfall Methodologies Agile Approach Empirical Process Control Agile and Traditional Project Management Choice of Methodologies/Frameworks The Agile Manifesto The Agile Manifesto Overview Manifesto Contributors Manifesto Values Manifesto Principles Common Agile Methodology Elements Common Agile Methodology Elements Overview Project (Product; Release) Initiation Agile Planning Iteration Planning and Executing Project Initiation Project Initiation Overview Determine Project Justifications and Metrics Provide Value-Driven Delivery Write Project Vision Statement Create Project Charter Identify Stakeholders and Leader/Coach Form Project Team Agile Teams and Team Space Agile Teams and Team Space Overview Scrum Master/Coach Product Owner/Customer Team Members/Developers (XP) Trackers and Testers Other Roles Team Space Physical Space Recommendations Agile Planning Agile Planning Overview Develop Epics and Stories Create Stories Non-Customer Facing Stories Personas and Extreme Personas Story Maps Estimating Stories Prioritizing Stories Create Product Backlog Create Product Roadmap Conduct Release Planning Create Parking Lot Iterations/Sprints Iterations/Sprints Overview Velocity Determination Iteration Planning Meeting Iteration Planning Guidelines Development Testing Daily Standup Meetings Progress Tracking Velocity Tracking Interpersonal Aspects of Agile Interpersonal Aspects of Agile Overview Methodologies and Uncertainty Coach/Scrum Master Team Motivation Soft Skills Emotional Intelligence Collaboration Negotiations Active listening Conflict Resolution Speed Leas? Model of Group Conflict Conducting Retrospectives Mindsets of Agile Coaches Leadership Stages Key Coaching Responsibilities Agile Methodologies Agile Methodologies Overview XP and Scrum Terms XP Terms and Concepts XP Primary Practices XP Corollary Practices Scrum Lean Software Development Seven Principles of Lean Seven Types of Muda Responsibilities Core Beliefs of Lean-Agile Software Development Other Principles of Lean-Agile Software Development Value Stream Mapping Lean-Agile Software Development Portfolio Management Additional course details: Nexus Humans PMI Agile Certified Practitioner (PMI-ACP) Exam Preparation 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 PMI Agile Certified Practitioner (PMI-ACP) Exam Preparation 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 Experienced system administrators, system integrators, and developers responsible for designing and implementing vRealize Log Insight Overview By the end of the course, you should be able to meet the following objectives: Identify features and benefits of vRealize Log Insight Determine the vRealize Log Insight cluster that meets your monitoring requirements Describe the vRealize Log Insight architecture and use cases Deploy and configure a vRealize Log Insight cluster Use the Interactive Analytics tab to get a deep understanding of log data Create and manage queries Managing vRealize Agents and Agent Groups Create various custom dashboards Describe and use the vRealize Log Insight widgets Extend the capabilities of vRealize Log Insight by adding content packs and configuring solutions This two-day course focuses on deploying, using, and managing VMware vRealize© Log Insight? product. It provides you with the knowledge and skills to deploy a vRealize Log Insight cluster that meets the monitoring requirements of your environment. This course covers the configuration and use of vRealize Log Insight to collect and manage logs from a variety of VMware and third-party products. This course discusses interfacing vRealize Log Insight with other systems to monitor, troubleshoot, and secure a data center. Course Introduction Introductions and course logistics Course objectives Introduction to vRealize Log Insight Describe a cloud management platform Explain the importance of efficient log management Describe the requirements for a log analytics solution Describe the key benefits of vRealize Log Insight Describe the key features of vRealize Log Insight Describe the various stages of log processing vRealize Log Insight Architecture and Deployment Identify the minimum requirements for deploying vRealize Log Insight Using vRealize Log Insight Sizing Calculator Describe vRealize Log Insight compatibility with other VMware products Describe the vRealize Log Insight architecture Determine the correct vRealize Log Insight deployment for an environment Install the vRealize Log Insight virtual appliance vRealize Log Insight Queries and Dashboards Describe the primary functions of the vRealize Log Insight UI Use the Interactive Analytics tab to get a deep understanding of log data Create and Manage queries Create vRealize Log Insight custom dashboards Describe and use the vRealize Log Insight widgets Administering vRealize Log Insight Describe User Access Control in vRealize Log Insight Describe User Management Access the vRealize Log Insight Administration page Configure vRealize Log Insight settings Manage certificates Configure system notifications Upgrade vRealize Log Insight Describe the vRealize Log Insight Importer vRealize Log Insight Integrations Describe how to integrate vRealize Operations with vRealize Log Insight Describe the advantages of integrating vRealize Operations with vRealize Log Insight Describe the advantages of using the vSAN content pack Install NSX content packs Additional course details:Notes Delivery by TDSynex, Exit Certified and New Horizons an VMware Authorised Training Centre (VATC) Nexus Humans VMware vRealize Log Insight: Deploy and Manage [V8.4] 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 vRealize Log Insight: Deploy and Manage [V8.4] 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 This course is intended for: Developers Solutions Architects Data Engineers Anyone with little to no experience with ML and wants to learn about the ML pipeline using Amazon SageMaker Overview In this course, you will learn to: Select and justify the appropriate ML approach for a given business problem Use the ML pipeline to solve a specific business problem Train, evaluate, deploy, and tune an ML model using Amazon SageMaker Describe some of the best practices for designing scalable, cost-optimized, and secure ML pipelines in AWS Apply machine learning to a real-life business problem after the course is complete This course explores how to use the machine learning (ML) pipeline to solve a real business problem in a project-based learning environment. Students will learn about each phase of the pipeline from instructor presentations and demonstrations and then apply that knowledge to complete a project solving one of three business problems: fraud detection, recommendation engines, or flight delays. By the end of the course, students will have successfully built, trained, evaluated, tuned, and deployed an ML model using Amazon SageMaker that solves their selected business problem. Module 0: Introduction Pre-assessment Module 1: Introduction to Machine Learning and the ML Pipeline Overview of machine learning, including use cases, types of machine learning, and key concepts Overview of the ML pipeline Introduction to course projects and approach Module 2: Introduction to Amazon SageMaker Introduction to Amazon SageMaker Demo: Amazon SageMaker and Jupyter notebooks Hands-on: Amazon SageMaker and Jupyter notebooks Module 3: Problem Formulation Overview of problem formulation and deciding if ML is the right solution Converting a business problem into an ML problem Demo: Amazon SageMaker Ground Truth Hands-on: Amazon SageMaker Ground Truth Practice problem formulation Formulate problems for projects Module 4: Preprocessing Overview of data collection and integration, and techniques for data preprocessing and visualization Practice preprocessing Preprocess project data Class discussion about projects Module 5: Model Training Choosing the right algorithm Formatting and splitting your data for training Loss functions and gradient descent for improving your model Demo: Create a training job in Amazon SageMaker Module 6: Model Evaluation How to evaluate classification models How to evaluate regression models Practice model training and evaluation Train and evaluate project models Initial project presentations Module 7: Feature Engineering and Model Tuning Feature extraction, selection, creation, and transformation Hyperparameter tuning Demo: SageMaker hyperparameter optimization Practice feature engineering and model tuning Apply feature engineering and model tuning to projects Final project presentations Module 8: Deployment How to deploy, inference, and monitor your model on Amazon SageMaker Deploying ML at the edge Demo: Creating an Amazon SageMaker endpoint Post-assessment Course wrap-up Additional course details: Nexus Humans The Machine Learning Pipeline on AWS training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the The Machine Learning Pipeline on AWS course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python experienced developers, analysts or others who are intending to learn the tools and techniques required in building various kinds of powerful recommendation systems (collaborative, knowledge and content based) and deploying them to the web. Overview Working in a hands-on lab environment led by our expert instructor, attendees will Understand the different kinds of recommender systems Master data-wrangling techniques using the pandas library Building an IMDB Top 250 Clone Build a content-based engine to recommend movies based on real movie metadata Employ data-mining techniques used in building recommenders Build industry-standard collaborative filters using powerful algorithms Building Hybrid Recommenders that incorporate content based and collaborative filtering Recommendation systems are at the heart of almost every internet business today; from Facebook to Net?ix to Amazon. Providing good recommendations, whether its friends, movies, or groceries, goes a long way in defining user experience and enticing your customers to use your platform.This course shows you how to do just that. You will learn about the different kinds of recommenders used in the industry and see how to build them from scratch using Python. No need to wade through tons of machine learning theory?you will get started with building and learning about recommenders as quickly as possible. In this course, you will build an IMDB Top 250 clone, a content-based engine that works on movie metadata. You will also use collaborative filters to make use of customer behavior data, and a Hybrid Recommender that incorporates content based and collaborative filtering techniques.Students will learn to build industry-standard recommender systems, leveraging basic Python syntax skills. This is an applied course, so machine learning theory is only used to highlight how to build recommenders in this course.This skills-focused ccombines engaging lecture, demos, group activities and discussions with machine-based student labs and exercises.. Our engaging instructors and mentors are highly-experienced practitioners who bring years of current, modern 'on-the-job' modern applied datascience, AI and machine learning experience into every classroom and hands-on project. Getting Started with Recommender Systems Technical requirements What is a recommender system? Types of recommender systems Manipulating Data with the Pandas Library Technical requirements Setting up the environment The Pandas library The Pandas DataFrame The Pandas Series Building an IMDB Top 250 Clone with Pandas Technical requirements The simple recommender The knowledge-based recommender Building Content-Based Recommenders Technical requirements Exporting the clean DataFrame Document vectors The cosine similarity score Plot description-based recommender Metadata-based recommender Suggestions for improvements Getting Started with Data Mining Techniques Problem statement Similarity measures Clustering Dimensionality reduction Supervised learning Evaluation metrics Building Collaborative Filters Technical requirements The framework User-based collaborative filtering Item-based collaborative filtering Model-based approaches Hybrid Recommenders Technical requirements Introduction Case study and final project ? Building a hybrid model Additional course details: Nexus Humans Applied AI: Building Recommendation Systems with Python (TTAI2360) 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 Applied AI: Building Recommendation Systems with Python (TTAI2360) 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.