21435 Improv courses

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.

Duration 5 Days 30 CPD hours This course is intended for Change Managers: Responsible for documentation, approval and change processes System Landscape Architects: Responsible for the design of the transport landscape topology System Administrators: Responsible for executing transports Development Managers: Responsible for performing development changes Application Manager: Responsible for approving and performing changes in an application Support Manager and members of the customer's SAP competence center: Responsible for Reporting and Diagnostics capabilities Partners and System Integrators Overview This course will prepare you to: Describe the concept and methods of E2E Change Control Management. Leverage the SAP Solution Manager 7.2 as application platform for E2E Change Control Management. In this course you will learn how change control management coordinates changes that are introduced into a software landscape so that the changes do not conflict with each other and how to make sure the changes are executed without disrupting ongoing business. This results in improved quality of the software landscape, higher availability of IT solutions, and lower total cost of ownership. Also important, change control management ensures that the changes introduced remain transparent, traceable and are made available for reporting and change analysis. Becoming adept at change control management requires skill in the efficient use of standardized methods and procedures. In this ?how to use? training, SAP imparts best-in-class knowledge of solution operations. The End-to-End Change Control Management course introduces participants to what change control management is and the standard tools used to accomplish it, tools provided by SAP Solution Manager. Introduction to E2E Change Control Management Explain the scope of End-to-End Change Control Management Explain the role of SAP Solution Manager to manage changes in your solution landscape Enhanced Change and Transport System Explain how the Enhanced Change and Transport System (CTS+) works Understand the basic concepts of Enterprise Portal and how it is supported by CTS+ Describe the best practices for the setup and usage of CTS+ in different scenarios Configuration Validation Understand the concepts and architecture of E2E Change Diagnostics Find current configuration information with the Change Reporting tool Find recent changes in the solution landscape with the E2E Change Analysis tool Compare multiple systems with the Configuration Validation tool Create targets, use operators and run validation reports Know how to use predefined reports in the report directory Transport and Execution Analysis Service and Transport and Execution Analysis Service for Projects Know how to run and use this self-check services within SAP Solution Manager Understand how to interpret the software change management KPIïs that are collected for your landscape Software Change Strategy Understand the limitations of a three-system landscape Understand the benefits of bundling changes in cycles and synchronized releases Transport Management with SAP Solution Manager Understand the change control landscape concept for transport management in SAP Solution Manager 7.2 Understand the usage of critical objects, cross system object locking and downgrade protection Know how to use retrofit in a dual landscape Understand the features of cCTS, which can be used for Quality Gate Management and Change Request Management parallel to CTS. Quality Gate Management Explain the concept of Solution Transports and Track Synchronization Setup and use Quality Gate Scenario as a central Transport Management Tool Create and release transport requests centrally in SAP Solution Manager for ABAP and Non-ABAP environments Know how to work within the Quality Gate Scenario Change Request Management Understand the different use cases for Change Request Management Describe the various elements of Change Request Management as part of SAP Solution Manager Understand SAP?s best practices for transport management which are implemented in Change Request Management Know how to work with Change Request Management Release Management Learn how to manage Release Management with SAP Solution Manager Understand how to manage the successful deployment of all related changes into the productive environment.

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 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 5 Days 30 CPD hours This course is intended for This course is recommended for technical professionals who support, install, deploy or administer Check Point products. This course is recommended for technical professionals who perform advanced deployment configurations of Check Point products. Overview CCSA Know how to perform periodic administrator tasks. Describe the basic functions of the Gaia operating system. Recognize SmartConsole features, functions, and tools. Understand how SmartConsole is used by administrators to give user access. Learn how Check Point security solutions and products work and how they protect networks. Understand licensing and contract requirements for Check Point security products. Describe the essential elements of a Security Policy. Understand the Check Point policy layer concept. Understand how to enable the Application Control and URL Filtering software. Blades to block access to various applications. Describe how to configure manual and automatic NAT. Identify tools designed to monitor data, determine threats and recognize opportunities for performance improvements. Describe different Check Point Threat Prevention solutions for network attacks. Articulate how the Intrusion Prevention System is configured, maintained and tuned. Understand the Infinity Threat Prevention system. Knowledge about Check Point's IoT Protect. CCSE Provide an overview of the upgrade service and options available. Explain how to perform management upgrade and migration. Articulate the process using CPUSE features. Articulate the purpose and function of Management High Availability. Explain Primary vs Secondary, Active vs Standby and Synchronization. Explain disaster recovery steps in case the primary management server becomes unavailable. Provide overview of Central Deployment in SmartConsole. Articulate an understanding of Security Gateway cluster upgrade methods. Explain about Multi Version Cluster (MVC) upgrades. Discuss Gaia Commands and how they are used. Explain the main processes on s and s. Describe how to work with scripts and SmartTasks to configure automatic actions. Explain the Management Data Plane Separation (MDPS) Explain kernel operations and traffic flow Articulate Dynamic and Updatable Objects in Security Gateways Explain the policy installation flow and files used. Describe the use of policy installation history. Explain concurrent and accelerated install policy. Describe an overview of APIs and ways to use and authenticate. Explain how to make changes in GAIA and management configuration. Explain how to install policy using API. Explain how the SecureXL acceleration technology enhances and optimizes Security Gateway performance. Learn basic concepts and develop skills necessary to administer IT security fundamental tasks. CCSA Outline Configure the Security Management Server. Use the WebUI to run the First Time Wizard. Install the Smart Console. Install the Alpha Gateway using the network detailed in the course topology. Demonstrate how the Security Management Server and Gateway communicate. Test SIC Status. Create multiple administrators and apply different roles and permissions for simultaneous administration. Validate existing licenses for products installed on the network. Create and configure host, network and group objects. Create a simplified Security Policy. Demonstrate how to use Security Zones in policy. Demonstrate how to share a layer between Security Polices. Configure Network Address Translation for server and network objects. Enable Identity Awareness. Deploy user access roles for more granular control of the security Policy. Generate network Traffic and use traffic visibility tools to monitor the data. Use SmartConsole and SmartView Monitor to view status, alerts, and block suspicious traffic. CCSE Outline Prepare for a Security Management Server Upgrade Upgrade the Security Management Server Deploy a Secondary Security Management Server Configure a Distributed Log Server Upgrade a Security Gateway from SmartConsole Work with the Command Line Use Scripts and SmartTasks Configure Dynamic Objects Monitor Traffic Verify Policy Installation and Status Work with Gaia and Management APIs Work with Acceleration Features Configure a Locally Managed Site to Site VPN Configure a Site to Site VPN with an Interoperable Device Configure Remote Access VPN Configure Mobile Access VPN Configure a High Availability Cluster Work with ClusterXL Configure Policy Compliance Deploy SmartEvent

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 3 Days 18 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 brandnew 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 dversarial 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 5 Days 30 CPD hours This course is intended for This is a basic-level programming course designed for attendees with prior development experience in another language, such as COBOL, 4GL, Mainframe or other non-object oriented languages. This course is not geared for non-developers. Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, designed to train attendees in core OO coding and Java development skills, 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 within in a hands-on learning environment, guided by our expert team, attendees will learn to: Understand what OO programming is and what the advantages of OO are in today's world Work with objects, classes, and OO implementations Understand the basic concepts of OO such as encapsulation, inheritance, polymorphism, and abstraction Understand not only the fundamentals of the Java language, but also its importance, uses, strengths and weaknesses Understand the basics of the Java language and how it relates to OO programming and the Object Model Work with the Modular system (Project Jigsaw) Understand and use classes, inheritance and polymorphism Understand and use collections, generics, autoboxing, and enumerations Process large amount of data using Lambda expressions and the Stream API Abstract, static and private methods in interfaces Take advantage of the Java tooling that is available with the programming environment being used in the class Java 11 features covered: Using the Local Variable Type in Lambda expressions; Updates made to the String API This course provides hands-on Java 11 training for developers who have little or no prior working knowledge of object-oriented programming languages such as C, COBOL, and 4GL. You will learn the best practices for writing great object-oriented programs in Java 11, using sound development techniques, new improved features for better performance, and new capabilities for addressing rapid application development. Special emphasis is placed on object oriented concepts and best practices. A First Look The Java Platform Using the JDK The Eclipse Paradigm Getting Started with Java Writing a Simple Class Adding Methods to the Class OO Concepts Object-Oriented Programming Inheritance, Abstraction, and Polymorphism Essential Java Programming Language Statements Using Strings Specializing in a Subclass Fields and Variables Using Arrays Local-Variable Type Inference Java Packages and Visibility Object Oriented Development Inheritance and Polymorphism Interfaces and Abstract Classes Introduction to Exception Handling Exceptions Java Developer's Toolboxÿ Utility Classes Java Date/Time Advanced Java Programming Introduction to Generics Lambda Expressions and Functional Interface Working with Collections Collections Using Collections Stream APIÿ Streams Collectors The Java Module System Introduction to the Module System Time Permitting Formatting Strings Introduction to Annotations Java 12 and beyond Additional course details: Nexus Humans Basic Java 11 and OO Programming for Developers New to OO (TT2120-J11) 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 Basic Java 11 and OO Programming for Developers New to OO (TT2120-J11) 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 This skills-focused combines 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. 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. 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 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 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.

Duration 5 Days 30 CPD hours This course is intended for This course is designed for technology leaders, solution developers, project managers, organizational decision makers, and other individuals seeking to demonstrate a vendor-neutral, cross-industry understanding of ethics in emerging data-driven technologies, such as AI, robotics, IoT, and data science. This course is also designed for professionals who want to pursue the CertNexus Certification Exam CET-110: Certified Ethical Emerging Technologies. Overview In this course, you will incorporate ethics into data-driven technologies such as AI, IoT, and data science. You will: Describe general concepts, theories, and challenges related to ethics and emerging technologies. Identify ethical risks. Practice ethical reasoning. Identify and mitigate safety and security risks. Identify and mitigate privacy risks. Identify and mitigate fairness and bias risks. Identify and mitigate transparency and explainability risks. Identify and mitigate accountability risks. Build an ethical organization. Develop ethical systems in technology-focused organizations. Mutually reinforcing innovations in computing and engineering are catapulting advances in technological production. From blockchain and artificial intelligence (AI) to gene editing and the Internet of Things (IoT), these advances come with tremendous opportunities for improvement in productivity, efficiency, and human well-being. But as scandals increasingly demonstrate, these advances also introduce new and serious risks of conflict and harm.Technology professionals now face growing demands to identify and mitigate ethical risks to human rights and the environment, as well as to navigate ethical tradeoffs between qualities such as privacy and accuracy, fairness and utility, and safety and accountability. This course provides the tools to identify and manage common ethical risks in the development of emerging data-driven technologies. It distills ethical theory, public regulations, and industry best practices into concrete skills and guidelines needed for the responsible development of digital products and services. By following the course's practical, problems-based approach, learners will become adept at applying theories, principles, frameworks, and techniques in their own roles and organizations. Introduction to Ethics of Emerging Technologies Topic A: What?s at Stake Topic B: Ethics and Why It Matters Topic C: Ethical Decision-Making in Practice Topic D: Causes of Ethical Failures Identifying Ethical Risks Topic A: Ethical Reasons Topic B: Stumbling Blocks for Ethical Reasoning Topic C: Identify Ethical Risks in Product Development Topic D: Tools for Identifying Ethical Risks Topic E: Use Regulations, Standards, and Human Rights to Identify Ethical Risks Ethical Reasoning in Practice Topic A: Ethical Theories Topic B: Use Ethical Decision-Making Frameworks Topic C: Select Options for Action Topic D: Avoid Problems in Ethical Decision-Making Identifying and Mitigating Security Risks Topic A: What Is Security? Topic B: Identify Security Risks Topic C: Security Tradeoffs Topic D: Mitigate Security Risks Identifying and Mitigating Privacy Risks Topic A: What Is Privacy? Topic B: Identify Privacy Risks Topic C: Privacy Tradeoffs Topic D: Mitigate Privacy Risks Identifying and Mitigating Fairness and Bias Risks Topic A: What Are Fairness and Bias? Topic B: Identify Bias Risks Topic C: Fairness Tradeoffs Topic D: Mitigate Bias Risks Identifying and Mitigating Transparency and Explainability Risks Topic A: What Are Transparency and Explainability? Topic B: Identify Transparency and Explainability Risks Topic C: Transparency and Explainability Tradeoffs Topic D: Mitigate Transparency and Explainability Risks Identifying and Mitigating Accountability Risks Topic A: What Is Accountability? Topic B: Identify Accountability Risks Topic C: Accountability Tradeoffs Topic D: Mitigate Accountability Risks Building an Ethical Organization Topic A: What Are Ethical Organizations? Topic B: Organizational Purpose Topic C: Ethics Awareness Topic D: Develop Professional Ethics within Organizations Developing Ethical Systems in Technology-Focused Organizations Topic A: Policy and Compliance Topic B: Metrics and Monitoring Topic C: Communication and Stakeholder Engagement Topic D: Ethical Leadership