1923 Courses in Cardiff delivered Live Online

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 certification is appropriate for anyone interested in becoming familiar with the concepts and practices of Agile Project Delivery, and who wants to have a working knowledge of the various Agile methodologies. Overview Objectives are: To provide an understanding of Agile philosophy and practices To provide a working knowledge of various Agile methodologies To provide students with the ability to compare and choose which methodology is appropriate in a given situation To prepare participants to pass the SAMC™ exam Course outcomes: Participants will be familiar with the concepts and practices of Agile project delivery. Participants will be equipped with detailed knowledge and understanding of available Agile methodologies. Participants will be able to compare and choose the methodologies or parts of methodologies that are most relevant to their current and future situations. Participants will be armed with the proper tools to take the lead in Agile projects and to address and resolve Agile issues in their organizations. Participants will be SAMC certified. Agile relies on adaptive planning and iterative development and delivery. It focuses primarily on the value of people in getting the job done effectively.Successful candidates will be awarded the SCRUMstudy Agile Master Certified (SAMC?) certification by SCRUMstudy after passing the included certification exam. The certification exam voucher is included in this course so you can take the exam at your convenience. IntroductionAgile Overview Agile Defined Why Use Agile? Adaptive Project Management The Agile Manifesto Principles of the Agile Manifesto Declaration of Interdependence Difference between Waterfall and Agile Domains of Agile Practices Value-Driven Delivery Stakeholder Engagement Team Performance Practices Adaptive Planning Problem Detection and Resolution Continuous Improvement Agile Tools and Artifacts Lean Kanban Software Development Introduction Core Values Practices Understanding Lean Software Development Understanding Kanban Software Development Scrum Overview of Scrum Brief History of Scrum Why Use Scrum? Scalability of Scrum Scrum Principles Scrum Aspects Scrum Processes Scrum and Kanban Extreme Programming (XP) Introduction Core Values? Roles Practices XP Artifacts XP Events XP Release Adopting XP Test-Driven Development (TDD) Introduction The Process Dynamic Systems Development Methods (DSDM) Introduction Core Values Roles Practices Crystal Introduction Core Values Roles Practices The Process Feature Driven Development (FDD) Introduction Core Values Roles Practices The Process Comparison of Agile MethodsBest Fit Analysis ToolBlitz PlanningNote SCRUMstudy has authored the SBOK? Guide as a comprehensive guide to deliver successful projects using Scrum. SCRUMstudy works through its large global partner network of Authorized Training Providers (A.T.P.s) to deliver trainings and certifications. New Horizons is a proud Authorized Training Provider of SCRUMstudy. Additional course details: Nexus Humans SCRUMstudy Agile Master Certified (SAMC) 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 SCRUMstudy Agile Master Certified (SAMC) 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 students looking to establish a foundational understanding of Access, including the skills necessary to create a new database, construct data tables, design forms and reports, and create queries. Overview In this course, you will create and manage an Access database. You will: Navigate within the Access application environment, create a simple database, and customize Access configuration options. Organize and manage data stored within Access tables. Use queries to join, sort, and filter data from different tables. Use forms to make it easier to view, access, and input data. Create and format custom reports. Data is everywhere. Most job roles today involve some form of data management. Virtually everyone is affected in some way by the need to manage data. A relational database application such as Microsoft© Access© can help you and your organization with this task. This course is the first part of a three-course series that covers the skills needed to perform database design and development in Access. Microsoft© Access© for Office 365?: Part 1 (this course): Focuses on the design and construction of an Access database?viewing, navigating, searching, and entering data in a database, as well as basic relational database design and creating simple tables, queries, forms, and reports. Microsoft© Access© for Office 365?: Part 2 : Focuses on optimization of an Access database, including optimizing performance and normalizing data, data validation, usability, and advanced queries, forms, and reports. Microsoft© Access© for Office 365?: Part 3 : Focuses on managing the database and supporting complex database designs, including import and export of data, using action queries to manage data, creating complex forms and reports, macros and VBA, and tools and strategies to manage, distribute, and secure a database. This course may be a useful component in your preparation for the Microsoft Access Expert (Microsoft 365 Apps and Office 2019): Exam MO-500 certification exam. Lesson 1: Working with an Access Database Topic A: Launch Access and Open a Database Topic B: Use Tables to Store Data Topic C: Use Queries to Combine, Find, Filter, and Sort Data Topic D: Use Forms to View, Add, and Update Data Topic E: Use Reports to Present Data Topic F: Get Help and Configure Options in Access Lesson 2: Creating Tables Topic A: Plan an Access Database Topic B: Start a New Access Database Topic C: Create a New Table Topic D: Establish Table Relationships Lesson 3: Creating Queries Topic A: Create Basic Queries Topic B: Add Calculated Columns in a Query Topic C: Sort and Filter Data in a Query Lesson 4: Creating Forms Topic A: Start a New Form Topic B: Enhance a Form Lesson 5: Creating Reports Topic A: Start a New Report Topic B: Enhance Report Layout Additional course details: Nexus Humans Microsoft Access for Office 365: Part 1 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 Microsoft Access for Office 365: Part 1 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 3 Days 18 CPD hours This course is intended for This course is ideal for those who regularly deploy or manage Meraki networks and want to deepen their technical expertise and understanding of the full Meraki product suite and features. This may include professionals with job titles or in roles such as: Consulting Systems Engineer Deployment Engineer Network Administrator Network Manager Network Engineer Site Reliability Engineer Systems Engineer Technical Solutions Architect Wireless Design Engineer Wireless Engineer Overview After completing the course, you should be able to: Plan new Cisco Meraki architectures and expand existing deployments Design the network for scalable management and high availability Describe how to automate and scale Meraki deployments with dashboard tools Use dynamic routing protocols to expand networks and improve WAN performance Describe proper QoS, policy and performance-based routing configurations across a Cisco Meraki network and WAN optimization through traffic shaping Describe Virtual Private Network (VPN) and Wide Area Network (WAN) topologies and how to integrate them Secure, expand, and shape the network Implement switched network concepts and practices, and configure guests networks Implement wireless configurations concepts and practices Describe endpoint management concepts and practices using Cisco Meraki Systems Manager Describe physical security concepts and practices Gain network insight by monitoring applications Describe how to prepare monitoring, logging, and alerting services Set up reporting and auditing capabilities in the Cisco Meraki dashboard Monitor and troubleshoot issues using Cisco Meraki tools The course, Engineering Cisco Meraki Solutions Part 2 (ECMS2) v2.1 elevates your knowledge of Cisco© Meraki? technology suite. In this advanced technical training course, you?ll learn how to plan for network deployments and integrations using the Cisco Meraki platform. Through practical hands-on instruction and experiences, you will learn how to operate Meraki networks and troubleshoot complex network incidents using the Meraki Dashboard and analytics. You will also learn how to design Meraki architectures for redundancy, high-density, and scalability by implementing comprehensive Meraki product features to meet design objectives. This course is the second of two courses that prepares you for Cisco Meraki certification. Course Outline Planning new Cisco Meraki architectures and expanding existing deployments Designing for scalable management and high availability Automating and scaling Meraki deployments Designing routing and practices on the Meraki platform Describing Quality of Service (QoS) and traffic shaping design Building VPN and WAN topologies Securing, expanding, and shaping the network Describing network concepts and practices Implementing wireless configuration practices and concepts Describing Endpoint management concepts and practices Describing physical security concepts and practices Gaining network insight through monitoring applications Preparing monitoring, logging, and alerting services Setting up reporting and auditing capabilities in the Cisco Meraki Dashboard Gaining visibility and resolving issues using Meraki features and built-in troubleshooting tools Additional course details: Nexus Humans Cisco Engineering Cisco Meraki Solutions Part 2 (ECMS2) v2.1 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 Engineering Cisco Meraki Solutions Part 2 (ECMS2) v2.1 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 basic course is intended for anyone who is new to software development and wants, or needs, to gain an understanding of the fundamentals of coding and basics of Java and object-oriented programming concepts. Attendees might include: Technically-minded attendees who want or who want to begin the process of becoming an OO application developer Technical team members from non-development roles, re-skilling to move into software and application development roles within an organization Recent college graduates looking to apply their college experience to programming skills in a professional environment, or perhaps needing to learn the best practices and standards for programming within their new organization Technical managers tasked with overseeing programming teams, or development projects, where basic coding knowledge and exposure will be useful in project oversight or communications needs Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, designed to train attendees in basic coding with Java, coupling the most current, effective techniques with the soundest industry practices. Our engaging instructors and mentors are highly experienced practitioners who bring years of current 'on-the-job' experience into every classroom. Working in a hands-on learning environment, guided by our expert team, attendees will learn: The steps involved in the creation and deployment of a computer program What OO programming is and what the advantages of OO are in today's world To work with objects, classes, and OO implementations The basic concepts of OO such as encapsulation, inheritance, polymorphism, and abstraction The basic constructs that all programming languages share The basic Java constructs supporting processing as well as the OO orientation How to use Java exception handling About and how to use classes, inheritance and polymorphism About use collections, generics, autoboxing, and enumerations How to take advantage of the Java tooling that is available with the programming environment being used in the class Getting Started with Programming, OO and Java Basics for Non-Developers is a skills-focused, hands-on coding course that teaches students the fundamentals of programming object oriented (OO) applications with Java to a basic level, using sound coding skills and best practices for OO development. This course is presented in a way that enables interested students to embrace the fundamentals of coding as well as an introduction to Java, in a gentle paced environment that focuses on coding basics.Students are introduced to the application development cycle, structure of programs, and specific language syntax. The course introduces important algorithmic constructs, string and character manipulation, dynamic memory allocation, standard I/O, and fundamental object-oriented programming concepts. The course explains the use of inheritance and polymorphism early on so the students can practice extensively in the hands-on labs. Structured programming techniques and error handling are emphasized. The course includes the processing of command line arguments and environment variables, so students will be able to write flexible, user-friendly programs. Students will leave this course armed with the required skills to begin their journey as a Java programmer using modern coding skills and technologies. Introduction to Computer Programming Introduction to Programming Programming Tools Programming Fundamentals Thinking About Objects Program Basics Programming Constructs Java: A First Look The Java Platform Using the JDK The Eclipse Paradigm Writing a Simple Class OO Concepts Object-Oriented Programming Inheritance, Abstraction, and Polymorphism Getting Started with Java Adding Methods to the Class Language Statements Using Strings Specializing in a Subclass Essential Java Programming Fields and Variables Using Arrays Java Packages and Visibility Advanced Java Programming Inheritance and Polymorphism Interfaces and Abstract Classes Exceptions Java Developer's Toolbox Utility Classes Enumerations and Static Imports Formatting Strings Collections and Generics Introduction to Generics Collections

Duration 4 Days 24 CPD hours This course is intended for This course is geared for attendees with Intermediate IT skills who wish to learn Computer Vision with tensor flow 2 Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course. Working in a hands-on learning environment, led by our Computer Vision expert instructor, students will learn about and explore how to Build, train, and serve your own deep neural networks with TensorFlow 2 and Keras Apply modern solutions to a wide range of applications such as object detection and video analysis Run your models on mobile devices and web pages and improve their performance. Create your own neural networks from scratch Classify images with modern architectures including Inception and ResNet Detect and segment objects in images with YOLO, Mask R-CNN, and U-Net Tackle problems faced when developing self-driving cars and facial emotion recognition systems Boost your application's performance with transfer learning, GANs, and domain adaptation Use recurrent neural networks (RNNs) for video analysis Optimize and deploy your networks on mobile devices and in the browser Computer vision solutions are becoming increasingly common, making their way into fields such as health, automobile, social media, and robotics. Hands-On Computervision with TensorFlow 2 is a hands-on course that thoroughly explores TensorFlow 2, the brand-new version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks. This course begins with the fundamentals of computer vision and deep learning, teaching you how to build a neural network from scratch. You will discover the features that have made TensorFlow the most widely used AI library, along with its intuitive Keras interface. You'll then move on to building, training, and deploying CNNs efficiently. Complete with concrete code examples, the course demonstrates how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build generative adversarial networks (GANs) and variational autoencoders (VAEs) to create and edit images, and long short-term memory networks (LSTMs) to analyze videos. In the process, you will acquire advanced insights into transfer learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts. Computer Vision and Neural Networks Computer Vision and Neural Networks Technical requirements Computer vision in the wild A brief history of computer vision Getting started with neural networks TensorFlow Basics and Training a Model TensorFlow Basics and Training a Model Technical requirements Getting started with TensorFlow 2 and Keras TensorFlow 2 and Keras in detail The TensorFlow ecosystem Modern Neural Networks Modern Neural Networks Technical requirements Discovering convolutional neural networks Refining the training process Influential Classification Tools Influential Classification Tools Technical requirements Understanding advanced CNN architectures Leveraging transfer learning Object Detection Models Object Detection Models Technical requirements Introducing object detection A fast object detection algorithm ? YOLO Faster R-CNN ? a powerful object detection model Enhancing and Segmenting Images Enhancing and Segmenting Images Technical requirements Transforming images with encoders-decoders Understanding semantic segmentation Training on Complex and Scarce Datasets Training on Complex and Scarce Datasets Technical requirements Efficient data serving How to deal with data scarcity Video and Recurrent Neural Networks Video and Recurrent Neural Networks Technical requirements Introducing RNNs Classifying videos Optimizing Models and Deploying on Mobile Devices Optimizing Models and Deploying on Mobile Devices Technical requirements Optimizing computational and disk footprints On-device machine learning Example app ? recognizing facial expressions

Duration 2 Days 12 CPD hours This course is intended for This course is recommended for technical professionals who automate, orchestrate, and troubleshoot Check Point secured environments. Overview Explain how automation and orchestration work together Understand the key drivers for incorporating automation and orchestration into security management Execute a shell script that demonstrates how to build a comprehensive Security Policy. Recognize how the Check Point API framework integrates with R80 Security Management to support automation and orchestration of daily tasks Describe Check Point API tools and demonstrate how they are used to manage Check Point Security Management solutions Demonstrate how to define new objects and modify existing ones by using the Check Point API The goal of this course is to provide an understanding of the advanced concepts and skills necessary to automate and orchestrate tasks relating to managing Check Point Security Policies Course Ouline Explain how automation and orchestration work together Understand the key drivers for incorporating automation and orchestration into security management Execute a shell script that demonstrates how to build a comprehensive Security Policy. Recognize how the Check Point API framework integrates with R80 Security Management to support automation and orchestration of daily tasks Describe Check Point API tools and demonstrate how they are used to manage Check Point Security Management solutions Demonstrate how to define new objects and modify existing ones by using the Check Point API Demonstrate how to create API commands to efficiently maintain the Check Point Security Management Server database Demonstrate how to use different methods to update the database with API commands Become familiar with client-side and server-side scripting and scripting languages Understand how to use the Bash shell to develop APIs Recognize and describe many of the open source tools that are available to assist with API development Demonstrate how to use a custom REST application to update the database of a Security Management Server Demonstrate how to use Postman to manage the Security Policy database through the Check Point API Understand what steps to take to troubleshoot and debug API scripts Demonstrate basic troubleshooting techniques by reviewing debugging messages in various forms Understand how to use self-service portal capabilities to provide general IT services Recognize how automation tools work with Check Point APIs to automate security management tasks and orchestrate workflow behind service portals Demonstrate common tasks that are automated in a Web portal to manage the Security Policy LAB Exercises Demonstrate Check Point automation and orchestration Manage objects using the Check Point API Create a management API shell script Use a variety of methods to execute API commands Use a custom REST tool for API calls Use Postman for API calls Debug the Check Point management API Automate tasks using a Check Point API enabled Web portal Additional course details: Nexus Humans CCAS Check Point Certified Automation Specialist 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 CCAS Check Point Certified Automation Specialist 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 primarily for professionals in the following job roles: Collaboration engineers Collaboration administrators Overview After taking this course, you should be able to: Configure Cisco Unity Connection integration Configure and troubleshoot Cisco Unity Connection and Cisco Unity Connection call handlers Configure and troubleshoot Cisco Unity Express Describe SSO for Cisco Unified Communications applications Describe how Cisco Jabber and Cisco Unified Communications Manager IM and Presence are integrated with other Cisco or third-party applications Customize the Cisco Unified Communications Manager IM and Presence and Cisco Jabber functionality Configure and troubleshoot chat rooms and message archiving Troubleshoot Cisco Jabber and Cisco Unified Communications Manager IM and Presence Integrate Cisco Unified Attendant Console Advanced with Cisco Unified Communications Manager and Cisco Unified Communications Manager IM and Presence server Configure call recording and monitoring This course provides you with the knowledge and skills to streamline communication procedures, strengthen compliance measures, and enhance your communication systems and devices with knowledge about Single Sign-On (SSO), Cisco© Unified IM and Presence, Cisco Unity© Connection and Cisco Unity Express. This course will prepare you for certification exam 300-810 Implementing Cisco Collaboration Applications (CLICA). Course Outline Configuring and Troubleshooting Cisco Unity Connection Integration Configuring and Troubleshooting Cisco Unity Connection Call Handlers Troubleshooting Cisco Unity Connection Configuring and Troubleshooting Cisco Unity Express Configuring Single Sign-On (SSO) for Cisco Unified Communications Applications Integrating Cisco Unified Communications Manager IM and Presence and Cisco Jabber Customizing Cisco Unified Communications Manager IM and Presence and Cisco Jabber Functionality Configuring Cisco Unified Communications Manager IM and Presence Service Compliance and Message Archiving Troubleshooting Cisco Unified Communications Manager IM and Presence Service Integrating Cisco Unified Attendant Console Advanced Implementing Call Recording and Monitoring Lab outline Integrate and Set Up Cisco Unity Connection Configure Cisco Unity Connection Call Handlers Implement Toll Fraud Prevention Troubleshoot Cisco Unity Connection Call Handlers Troubleshoot Cisco Unity Connection Configure Cisco Unity Express Troubleshoot Cisco Unity Express Configure Cisco Unified Communications Manager IM and Presence High Availability Implement Cisco Jabber Configure Centralized Cisco Unified Communications Manager IM and Presence Configure Cisco Unified Communications Manager IM and Presence Service Functionality Enable Message Archiving and Chat Rooms Troubleshoot the Cisco Unified Communications IM and Presence Database Connection Troubleshoot Cisco Unified Communications Manager IM and Presence High Availability Troubleshoot Cisco Unified Communications Manager IM and Presence Service Integrate Cisco Unified Attendant Console Advanced Implement Call Recording and Monitoring Using a Switched Port Analyzer (SPAN)-based Solution Implement Cisco Unified Communications Manager Call Recording and Monitoring Additional course details: Nexus Humans Cisco Implementing Cisco Collaboration Applications v1.0 (CLICA) 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 Implementing Cisco Collaboration Applications v1.0 (CLICA) 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