31033 Development courses

Self Defence & Martial Arts Classes for 11-15 years old in Dartford, Bexleyheath

Self Defence & Martial Arts Classes for Adults

Duration 0.5 Days 3 CPD hours This course is intended for This course is primarily designed for business leaders, consultants, product and project managers, and other decision-makers who are interested in growing the business by leveraging the power of AI. Other individuals who wish to explore basic AI concepts are also candidates for this course. This course is also designed to assist students in preparing for the CertNexus AIBIZ™ (Exam AIZ-210) credential. Overview In this course, you will identify ways in which AI can bring significant value to the business. You will: Describe AI fundamentals. Identify the functions of AI in business. Implement business requirements for AI. Artificial intelligence (AI) is not just another technology or process for the business to consider?it is a truly disruptive force, one that delivers an entirely new level of results across business sectors. Even organizations that resist adopting AI will feel its impact. If the organization wants to thrive and survive in this transforming business landscape, it will need to harness the power of AI. This course is designed to help business professionals conquer and move beyond the basics of AI to apply AI concepts for the benefit of the business. It will give you the essential knowledge of AI you'll need to steer the business forward. Lesson 1: AI Fundamentals Topic A: A Brief History of AI Topic B: AI Concepts Lesson 2: Functions of AI in Business Topic A: Improve User Experiences Topic B: Segment Audiences Topic C: Secure Assets Topic D: Optimize Processes Lesson 3: Implementing Business Requirements for AI Topic A: Identify Design Requirements Topic B: Identify Data Requirements Topic C: Identify Risks in Implementing AI Topic D: Develop an AI Strategy

Duration 3 Days 18 CPD hours This course is intended for The EXIN BCS Artificial Intelligence Foundation certification is focused on individuals with an interest in, (or need to implement) AI in an organization, especially those working in areas such as science, engineering, knowledge engineering, finance, education or IT services. Overview You will be able to Describe how Artificial (AI) is Part of 'Universal Design', and 'The Fourth Industrial Revolution' Demonstrate Understanding of the Artificial Intelligence (AI) Intelligen Agent Description Explain the Benefits of Artificial Intelligence (AI) Describe how we Learn from Data - Functionality, Software and Hardware Demonstrate an Understanding that Artificial Intelligence (AI) (in Particular, Machine Learning (ML)) will Drive Humans and Machines to Work Together Describe a ''Learning from Experience'' Agile Approach to Projects Candidates should be able to demonstrate a knowledge and understanding in the application of ethical and sustainable Artificial Intelligence (AI):- Human-centric Ethical and Sustainable Human and Artificial Intelligence (AI) Ethical and Sustainable Human and Artificial Intelligence (AI) Recall the General Definition of Human and Artificial Intelligence (AI) Describe what are Ethics and Trustworthy Artificial Intelligence (AI) Describe the Three Fundamental Areas of Sustainability and the United Nationïs Seventeen Sustainability Goals Describe how Artificial Intelligence (AI) is Part of 'Universal Design', and 'The Fourth Industrial Revolution' Understand that Machine Learning (ML) is a Significant Contribution to the Growth of Artificial Intelligence (AI) Artificial Intelligence (AI) and Robotics Demonstrate Understanding of the Artificial Intelligence (AI) Intelligent Agent Description Describe what a Robot is Describe what an intelligent Robot is Applying the Benefits of Artificial Intelligence (AI) ? Challenges and Risks Describe how Sustainability Relates to Human-Centric Ethical Artificial Intelligence (AI) and how our Values will Drive our use of Artificial Intelligence (AI) and will Change Humans, Society and Organizations Explain the Benefits of Artifical Intelligence (AI) Describe the Challenges of Artificial Intelligence (AI) Projects Demonstrate Understanding of the Risks of Artificial Intelligence (AI) Projects List Opportunities for Artificial Intelligence (AI) Identify a Typical Funding Source for Artificial Intelligence (AI) Projects and Relate to the NASA Technology Readiness Levels (TRLs) Starting Artificial Intelligence (AI): how to Build a Machine Learning (ML) Toolbox ? Theory and Practice Describe how we Learn from Data - Functionality, Software and Hardware Recall which Rypical, Narrow Artificial Intelligence (AI) Capability is Useful in Machine Learning (ML9 and Artificial Intelligence (AI) AgentsïFunctionality The Management, Roles and Responsibilities of Humans and Machines Demonstrate an Understanding that Artificial Intelligence (AI) (in Particular, Machine Learning (ML)) will Drive Humans and Machines to Work Together List Future Directions of Humans and Machines Working Together Describe a ''Learning from Experience'' Agile Approach to Projects

Duration 2 Days 12 CPD hours This course is intended for The primary audience for this course is as follows: Network Video Engineer Voice/UC/Collaboration/Communications Engineer Collaboration Tools Engineer Collaboration Sales/Systems Engineer This is a two day instructor-led course that focuses on the skills and knowledge needed to implement and configure a Cisco TelePresence Management Suite and Cisco TelePresence Management Suite Extensions. Students will configure TMS, TMSPE, TMSXE, VCS and UCM for management of endpoints. Students will also learn to Configure and Schedule Conferencing, Administrative Tasks, Set up Microsoft Active Directory Users, Manage Conferences and Provision Devices. Installing Cisco Telepresence Management Server Windows Server Installation SQL Server Installation Server Pre-requisites and configuration Installing TMS Installing TMS Provisioning Extensions Release and Option Keys Upgrading TMS Backup TMS Configuring Cisco TelePresence Management Suite (TMS) Initial Configuration Endpoint Configuration Adding User Accounts and Profiles Groups and Permissions Active Directory Lookup Configuration Templates Setting Configuration VCS Configuration for TMS Direct Endpoint Management VCS/TMS Direct Managed Endpoint Features CUCM Configuration for TMS Direct Endpoint Management ? CUCM TMS Responsibilities CUCM Responsibilities Findme Configuration Phonebooks & Phonebook Sources Booking Conferencing Conference Creation Advanced Conference Settings Booking & Scheduling Conference Monitoring Dial Plans, Configuration Templates Scheduler/Smart Scheduler Reporting on TMS Reporting Basics Creating a Report Using Reporting Templates Bridge Utilization Call Detail Records Billing Code Statistics Conferences System Managing and Troubleshooting TMS Using the Logs Cisco TMS Ticketing System Troubleshooting VCS Registrations Troubleshooting CUCM Registrations System Maintenance

Duration 2 Days 12 CPD hours This course is intended for IBM SPSS Statistics users who want to familiarize themselves with the statistical capabilities of IBM SPSS StatisticsBase. Anyone who wants to refresh their knowledge and statistical experience. Overview Introduction to statistical analysis Describing individual variables Testing hypotheses Testing hypotheses on individual variables Testing on the relationship between categorical variables Testing on the difference between two group means Testing on differences between more than two group means Testing on the relationship between scale variables Predicting a scale variable: Regression Introduction to Bayesian statistics Overview of multivariate procedures This course provides an application-oriented introduction to the statistical component of IBM SPSS Statistics. Students will review several statistical techniques and discuss situations in which they would use each technique, how to set up the analysis, and how to interpret the results. This includes a broad range of techniques for exploring and summarizing data, as well as investigating and testing relationships. Students will gain an understanding of when and why to use these various techniques and how to apply them with confidence, interpret their output, and graphically display the results. Introduction to statistical analysis Identify the steps in the research process Identify measurement levels Describing individual variables Chart individual variables Summarize individual variables Identify the normal distributionIdentify standardized scores Testing hypotheses Principles of statistical testing One-sided versus two-sided testingType I, type II errors and power Testing hypotheses on individual variables Identify population parameters and sample statistics Examine the distribution of the sample mean Test a hypothesis on the population mean Construct confidence intervals Tests on a single variable Testing on the relationship between categorical variables Chart the relationship Describe the relationship Test the hypothesis of independence Assumptions Identify differences between the groups Measure the strength of the association Testing on the difference between two group meansChart the relationship Describe the relationship Test the hypothesis of two equal group means Assumptions Testing on differences between more than two group means Chart the relationship Describe the relationship Test the hypothesis of all group means being equal Assumptions Identify differences between the group means Testing on the relationship between scale variables Chart the relationship Describe the relationship Test the hypothesis of independence Assumptions Treatment of missing values Predicting a scale variable: Regression Explain linear regression Identify unstandardized and standardized coefficients Assess the fit Examine residuals Include 0-1 independent variables Include categorical independent variables Introduction to Bayesian statistics Bayesian statistics and classical test theory The Bayesian approach Evaluate a null hypothesis Overview of Bayesian procedures in IBM SPSS Statistics Overview of multivariate procedures Overview of supervised models Overview of models to create natural groupings

Duration 1 Days 6 CPD hours This course is intended for This course is intended for organizations engaged with remote workforce teams. Overview Upon successful completion of this course, participants will be able to identify and create high performance teams. In this course, teams will learn the importance of developing performance skills while working remotely. Getting Started Workshop Objectives Action Plan Remote Workforce What is a Remote Workforce? Types of Remote Workforce Benefits of a Remote Workforce Materials for Remote Workforce Practical Illustration High Performance Teams What is a High-Performance Team? Benefits of High-Performance Teams Leadership for High Performance Team Understanding Team Dynamics Practical Illustration Characteristics of High-Performance Teams Excellent Communication Goal-Oriented Flexibility Committed Practical Illustration How to Create Teamwork Identify Group & Individual Responsibilities Give Permission to Take Action Build Relationships between Team Members and Management Give Feedback Practical Illustration Types of Communication Virtual Team Meetings Telephone Conferences Email Communication Intranet, Webpage, and Social Media Communication Practical Illustration Training Your Team Telecommute Training Web-based Training Peer Training Training Assessment and Retraining Practical Illustration Types of Communication Tracking Team Performance Counseling Employees Positive Recognition for Employees Training Never Stops! Practical Illustration Effective Team Meeting How-to 43 Have a Clear Agenda Have a Clear Agenda Use Screen Shots or References Create a Safe Place Team Meeting Don?ts Practical Illustration Keep a Happy and Motivated High-Performance Team Watch for Signs of Conflict or Unhappiness Employee Feedback and Concerns Give Opportunities for Additional Education Impart Opportunities for Career Growth Practical Illustration Don?ts? with High Performance Teams Don't Forget to Share Success Don't Delay in Responding Don?t Assign Vague Responsibilities Don?t Lead as a Dictator Practical Illustration Wrapping Up Words from the Wise

This course discusses the care of indwelling male, female, and supra-pubic catheters in order to minimise the risks associated with indwelling catheters

This is an essential programme for any member of staff whose role requires a high level of attention to detail. The focus is specifically on the handling of text and data, whether at the input stage or when collating information into reports and documents for use by others. The session looks at both prevention and cure. For 'prevention', it focuses on understanding how common errors occur and on developing an awareness of the factors which influence our level of attentiveness. It introduces key psychological theories around attentiveness including the 'capacity' and 'bottleneck filter' models. And it looks at how working styles can affect attention to detail. For 'cure', the programme looks at how to minimise the effect of stress on concentration as well as introducing a number of tools and techniques for promoting accuracy - at both the input and the checking stages. Particular attention is paid to proof-reading techniques. By the end of the session, participants will: Appreciate why errors occur Understand how stress and other factors can affect focus and accuracy Know how to improve accuracy and reduce errors when handling text and data Be able to proof-read text and number-based documents more accurately 1 The importance of accuracy The impact of mistakes Why accuracy is so important Main reasons why errors occur 2 Attentiveness theory The 'capacity' and 'bottleneck filter' models Selective attention Chunking - big picture / little picture 3 Preparing for accuracy Working styles - how they affect detail-orientation Identifying and minimising the impact of stress on concentration 4 Practical strategies How to improve accuracy and reduce errors when inputting text Managing interruptions and distractions Proofing text and numbers

Duration 3 Days 18 CPD hours This course is intended for Java Fundamentals is designed for tech enthusiasts who are familiar with some programming languages and want a quick introduction to the most important principles of Java. Overview After completing this course, you will be able to: Create and run Java programs Use data types, data structures, and control flow in your code Implement best practices while creating objects Work with constructors and inheritance Understand advanced data structures to organize and store data Employ generics for stronger check-types during compilation Learn to handle exceptions in your code Since its inception, Java has stormed the programming world. Its features and functionalities provide developers with the tools needed to write robust cross-platform applications. Java Fundamentals introduces you to these tools and functionalities that will enable you to create Java programs. The course begins with an introduction to the language, its philosophy, and evolution over time, until the latest release. You'll learn how the javac/java tools work and what Java packages are - the way a Java program is usually organized. Once you are comfortable with this, you'll be introduced to advanced concepts of the language, such as control flow keywords. You'll explore object-oriented programming and the part it plays in making Java what it is. In the concluding lessons, you'll be familiarized with classes, typecasting, and interfaces, and understand the use of data structures, arrays, strings, handling exceptions, and creating generics. Introduction to Java The Java Ecosystem Our First Java Application Packages Variables, Data Types, and Operators Variables and Data Types Integral Data Types Type casting Control Flow Conditional Statements Looping Constructs Object-Oriented Programming Object-Oriented Principles Classes and Objects Constructors The this Keyword Inheritance Overloading Constructor Overloading Polymorphism and Overriding Annotations References OOP in Depth Interfaces Typecasting The Object Class Autoboxing and Unboxing Abstract Classes and Methods Data Structures, Arrays, and Strings Data Structures and Algorithms Strings The Java Collections Framework and Generics Reading Data from Files The Java Collections Framework Generics Collection Advanced Data Structures in Java Implementing a Custom Linked List Implementing Binary Search Tree Enumerations Set and Uniqueness in Set Exception Handling Motivation behind Exceptions Exception Sources Exception Mechanics Best Practices