3129 Development courses in Manchester delivered Live Online

Duration 1 Days 6 CPD hours This course is intended for Individuals taking this course are business professionals seeking to develop or increase their emotional intelligence. Overview In this course, you will explore the concept of emotional intelligence. You will: Identify the components of emotional intelligence and recognize how emotional intelligence benefits organizations. Assess and develop your personal emotional intelligence competencies. Assess and develop your social emotional intelligence competencies. Practice emotional intelligence in common workplace scenarios. It was once believed that intelligence was the metric that would determine a person's success in the workplace. Intelligence matters because it contributes to your ability to do your job. But intelligence is not the best indicator of whether or not you'll succeed. Your ability to understand and manage your own emotions, and get along well with others, has at least as much impact on your performance and effectiveness as intelligence. In this course, you'll explore strategies to increase your awareness of your emotions, develop your ability to manage your emotions, and improve your social skills. Recognizing the Benefits of Emotional Intelligence Define Emotional Intelligence Recognize EQ's Impact on Work Experience Increasing Your Personal Emotional Intelligence in the Workplace Develop Your Level of Self-Awareness Develop Your Self-Regulation Skills Develop Your Motivation Increasing Your Social Emotional Intelligence in the Workplace Develop Your Empathy Develop Your Social Skills Practicing Emotional Intelligence in the Workplace Practice Emotionally Intelligent Leadership Build an Emotionally Intelligent Team Manage Change Manage Conflict Coach for Performance Additional course details: Nexus Humans Emotional Intelligence for Business Professionals (Second Edition) 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 Emotional Intelligence for Business Professionals (Second Edition) 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 intended for: A technical audience at an intermediate level Overview Using Amazon SageMaker, this course teaches you how to: Prepare a dataset for training. Train and evaluate a machine learning model. Automatically tune a machine learning model. Prepare a machine learning model for production. Think critically about machine learning model results In this course, learn how to solve a real-world use case with machine learning and produce actionable results using Amazon SageMaker. This course teaches you how to use Amazon SageMaker to cover the different stages of the typical data science process, from analyzing and visualizing a data set, to preparing the data and feature engineering, down to the practical aspects of model building, training, tuning and deployment. Day 1 Business problem: Churn prediction Load and display the dataset Assess features and determine which Amazon SageMaker algorithm to use Use Amazon Sagemaker to train, evaluate, and automatically tune the model Deploy the model Assess relative cost of errors Additional course details: Nexus Humans Practical Data Science with Amazon SageMaker 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 Practical Data Science with Amazon SageMaker 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 business professionals who leverage data to address business issues. The typical student in this course will have several years of experience with computing technology, including some aptitude in computer programming. However, there is not necessarily a single organizational role that this course targets. A prospective student might be a programmer looking to expand their knowledge of how to guide business decisions by collecting, wrangling, analyzing, and manipulating data through code; or a data analyst with a background in applied math and statistics who wants to take their skills to the next level; or any number of other data-driven situations. Ultimately, the target student is someone who wants to learn how to more effectively extract insights from their work and leverage that insight in addressing business issues, thereby bringing greater value to the business. Overview In this course, you will learn to: Use data science principles to address business issues. Apply the extract, transform, and load (ETL) process to prepare datasets. Use multiple techniques to analyze data and extract valuable insights. Design a machine learning approach to address business issues. Train, tune, and evaluate classification models. Train, tune, and evaluate regression and forecasting models. Train, tune, and evaluate clustering models. Finalize a data science project by presenting models to an audience, putting models into production, and monitoring model performance. For a business to thrive in our data-driven world, it must treat data as one of its most important assets. Data is crucial for understanding where the business is and where it's headed. Not only can data reveal insights, it can also inform?by guiding decisions and influencing day-to-day operations. This calls for a robust workforce of professionals who can analyze, understand, manipulate, and present data within an effective and repeatable process framework. In other words, the business world needs data science practitioners. This course will enable you to bring value to the business by putting data science concepts into practice Addressing Business Issues with Data Science Topic A: Initiate a Data Science Project Topic B: Formulate a Data Science Problem Extracting, Transforming, and Loading Data Topic A: Extract Data Topic B: Transform Data Topic C: Load Data Analyzing Data Topic A: Examine Data Topic B: Explore the Underlying Distribution of Data Topic C: Use Visualizations to Analyze Data Topic D: Preprocess Data Designing a Machine Learning Approach Topic A: Identify Machine Learning Concepts Topic B: Test a Hypothesis Developing Classification Models Topic A: Train and Tune Classification Models Topic B: Evaluate Classification Models Developing Regression Models Topic A: Train and Tune Regression Models Topic B: Evaluate Regression Models Developing Clustering Models Topic A: Train and Tune Clustering Models Topic B: Evaluate Clustering Models Finalizing a Data Science Project Topic A: Communicate Results to Stakeholders Topic B: Demonstrate Models in a Web App Topic C: Implement and Test Production Pipelines

Chairing or facilitating a panel discussion is a particular skill. When many experts and specialists in their field are asked to do this, they discover that it is not as easy as they imagined. Pitching and introducing the session, involving everyone, promoting audience engagement, dealing with difficult panellists and ending the discussion can all be a challenge for inexperienced facilitators. Our panel facilitation training workshop focuses on providing delegates with the techniques and confidence they need to chair panel debates effectively. It is delivered by BBC presenter Martine Croxall and is highly interactive, blending theory with practical exercises. During the course, you will learn: the best way to prepare, including audience analysis and research how to pitch a panel how to introduce a panel how to involve everyone in the discussion the best way to promote audience engagement how to deal with difficult panellists how to end a discussion Each delegate will have the chance to chair a panel discussion, with the other delegates and Martine playing different roles as panellists.

Pushy boardroom bullies... battling agendas... conflicts of interest. Here are the most common drivers of trouble in the boardroom, and tools for making things right.

Duration 3 Days 18 CPD hours This course is intended for This course is intended for: Intermediate software developers Overview In this course, you will learn to: Set up the AWS SDK and developer credentials for Java, C#/.NET, Python, and JavaScript Interact with AWS services and develop solutions by using the AWS SDK Use AWS Identity and Access Management (IAM) for service authentication Use Amazon Simple Storage Service (Amazon S3) and Amazon DynamoDB as data stores Integrate applications and data by using AWS Lambda, Amazon API Gateway, Amazon Simple Queue Service (Amazon SQS), Amazon Simple Notification Service (Amazon SNS), and AWS Step Functions Use Amazon Cognito for user authentication Use Amazon ElastiCache to improve application scalability Leverage the CI/CD pipeline to deploy applications on AWS In this course, you learn how to use the AWS SDK to develop secure and scalable cloud applications using multiple AWS services such as Amazon DynamoDB, Amazon Simple Storage Service, and AWS Lambda. You explore how to interact with AWS using code and learn about key concepts, best practices, and troubleshooting tips. Module 0: Course Overview Agenda Introductions Student resources Module 1: Introduction to AWS Introduction to the AWS Cloud Cloud scenarios Infrastructure overview Introduction to AWS foundation services Module 2: Introduction to Developing on AWS Getting started with developing on AWS Introduction to developer tools Introduction to management tools Module 3: Introduction to AWS Identity and Access Management Shared responsibility model Introduction to IAM Use authentication and authorization Module 4: Introduction to the Lab Environment Introduction to the lab environment Lab 1: Getting started and working with IAM Module 5: Developing Storage Solutions with Amazon Simple Storage Service Overview of AWS storage options Amazon S3 key concepts Best practices Troubleshooting Scenario: Building a complete application Lab 2: Developing storage solutions with Amazon S3 Module 6: Developing Flexible NoSQL Solutions with Amazon DynamoDB Introduction to AWS database options Introduction to Amazon DynamoDB Developing with DynamoDB Best practices Troubleshooting Scenario: Building an end-to-end app Lab 3: Developing flexible NoSQL solutions with Amazon DynamoDB Module 7: Developing Event-Driven Solutions with AWS Lambda What is serverless computing? Introduction to AWS Lambda Key concepts How Lambda works Use cases Best practices Scenario: Build an end-to-end app Module 8: Developing Solutions with Amazon API Gateway Introduction to Amazon API Gateway Developing with API Gateway Best practices Introduction to AWS Serverless Application Model Scenario: Building an end-to-end app Lab 4: Developing event-driven solutions with AWS Lambda Module 9: Developing Solutions with AWS Step Functions Understanding the need for Step Functions Introduction to AWS Step Functions Use cases Module 10: Developing Solutions with Amazon Simple Queue Service and Amazon Simple Notification Service Why use a queueing service? Developing with Amazon Simple Queue Service Developing with Amazon Simple Notification Service Developing with Amazon MQ Lab 5: Developing messaging solutions with Amazon SQS and Amazon SNS Module 11: Caching Information with Amazon ElastiCache Caching overview Caching with Amazon ElastiCache Caching strategies Module 12: Developing Secure Applications Securing your applications Authenticating your applications to AWS Authenticating your customers Scenario: Building an end-to-end app Module 13: Deploying Applications Introduction to DevOps Introduction to deployment and testing strategies Deploying applications with AWS Elastic Beanstalk Scenario: Building an end-to-end app Lab 6: Building an end-to-end app Module 14: Course wrap-up Course overview AWS training courses Certifications Course feedback

Duration 1 Days 6 CPD hours In this hands on workshop for Agile Scrum Masters, Release Train Engineers and anyone serving as Jira Administrators, Jira experts will lead you through advanced configuration and customization settings in Jira, from installation through to customized screens, workflows, filters and reports. Jira Administration Adding and managing Users Administering and managing Groups Global Jira Settings Jira layout and interface customization User authentication and security Jira Customization Customization of screens and fields Customization of workflows Project and Board Administration Configuring and managing Projects Configuring and managing Boards Creating and managing Filters JQL Jira Integration Integrating Jira with Atlassian Tools Retrospectives and Documentation in Confluence Code management with Bitbucket Integration management with Bamboo Building a Dashboard with gadgets Jira Plug-ins and Marketplace

Duration 1 Days 6 CPD hours This course is intended for This course is intended for: Data platform engineers Solutions architects IT professionals Overview In this course, you will learn to: Apply data lake methodologies in planning and designing a data lake Articulate the components and services required for building an AWS data lake Secure a data lake with appropriate permission Ingest, store, and transform data in a data lake Query, analyze, and visualize data within a data lake In this course, you will learn how to build an operational data lake that supports analysis of both structured and unstructured data. You will learn the components and functionality of the services involved in creating a data lake. You will use AWS Lake Formation to build a data lake, AWS Glue to build a data catalog, and Amazon Athena to analyze data. The course lectures and labs further your learning with the exploration of several common data lake Introduction to data lakes Describe the value of data lakes Compare data lakes and data warehouses Describe the components of a data lake Recognize common architectures built on data lakes Data ingestion, cataloging, and preparation Describe the relationship between data lake storage and data ingestion Describe AWS Glue crawlers and how they are used to create a data catalog Identify data formatting, partitioning, and compression for efficient storage and query Lab 1: Set up a simple data lake Data processing and analytics Recognize how data processing applies to a data lake Use AWS Glue to process data within a data lake Describe how to use Amazon Athena to analyze data in a data lake Building a data lake with AWS Lake Formation Describe the features and benefits of AWS Lake Formation Use AWS Lake Formation to create a data lake Understand the AWS Lake Formation security model Lab 2: Build a data lake using AWS Lake Formation Additional Lake Formation configurations Automate AWS Lake Formation using blueprints and workflows Apply security and access controls to AWS Lake Formation Match records with AWS Lake Formation FindMatches Visualize data with Amazon QuickSight Lab 3: Automate data lake creation using AWS Lake Formation blueprints Lab 4: Data visualization using Amazon QuickSight Architecture and course review Post course knowledge check Architecture review Course review

It is essential that those charged with responsibility for credit control and debt recovery have a full appreciation of the relevant law: no-one can negotiate effectively to recover a debt if they don't understand the ultimate sanctions they can apply. This programme is designed to give them a practical, up-to-date understanding of the law as it applies to your particular organisation. This course will help ensure that participants: Understand the relevant laws Know how and when to invoke legal processes Avoid legal pitfalls in debt collection negotiations Specific, practical learning points include: Definition of 'harassment' How to set up an in-house collection identity Whether cheques in 'full and final settlement' are binding The best steps to trace a 'gone away'... and many, many more. 1 Data protection and debt recovery There are a whole range of things which can be checked on members of the public and which are not affected by the restraints of the Data Protection Act. These will be explained in simple, clear terms so that staff can use this information immediately. 2 County Court suing The expert trainer will show how to sue for money owed, obtain judgment and commence enforcement action without leaving your desk. This module is aimed at showing how to make the Courts work for you instead of the other way around! 3 Enforcement of judgments There are many people who have a County Court Judgment (CCJ) against their debtor but who still remain unpaid. This session explains each of the enforcement methods and how to use them to best effect. Enforcement methods covered include: Warrant of Execution Using the sheriff (now known as High Court Enforcement Officers) Attachment of earnings Third Party Debt Orders Charging Orders (over property and goods) Winding-up companies and making individuals bankrupt 4 Office of Fair Trading rules on debt recovery Surprisingly few people are aware of the Office of Fair Trading rules on debt recovery and many of those that do know think they don't apply to them - but they do. Make sure you know what you need to! 5 New methods to trace elusive, absentee and 'gone away' debtors Why write the money off when you can trace the debtor and collect the money you are owed? 6 Credit checking of new and existing customers It makes sense to credit check would-be, new and existing customers to evaluate the likelihood of payment delays or perhaps not being paid at all. This session shows a range of credit checking steps, many of which can be done completely free of charge, including a sample credit application/ account opening form. 7 Late Payment of Commercial Debts Regulations Do your staff understand this legislation and how to use it to make people pay quicker than ever before? The trainer shows how. 8 The Enterprise Act The Enterprise Act made some startling changes to corporate and personal insolvency. What are the implications for credit control and debt recovery within your organisation?

This workshop is very practical in its nature and aims to give delegates an opportunity to not only learn about the key aspects of successful bid writing, but to also put them into practice. The workshop helps delegates understand what is most important to buyers and how to successfully convey they proposition to them. 1 Welcome and introductions 2 The mindset of successful bid writing The mindset needed for successful bid writing Thinking from the buyer's perspective and not your own 3 Decision making The way buyers make decisions - rational and emotional Understanding buying motives Looking at how to present ideas against those motives The idea of cognitive fluency How to pitch an idea in a way that leads to a positive decision 4 To bid or not to bid? Writing a bid is a big commitment; a clear understanding of the chances of winning is required Understanding of the implications of winning and the impact it will have on the organisation 5 Understanding your value proposition Framework to help identify unique proposition and how that fits in with the requirements of the bid 6 The tender process Understanding the process to enable a successful chance of winning the bid Different types of tender processes Evaluation of criteria and the impact on bid writing 7 Writing skills Different ways of writing and structuring bids to ensure their messages gets across well in a way that will be looked on favourably by the buyer 8 Summarise 9 Close