2975 TEC courses delivered Live Online

Take your organisation’s presentations to the next level by truly engaging second language English speakers with our specific techniques. Help them communicate key messages with confidence and clarity to the whole audience. With lots of opportunities for practice in a very safe space, participants will build their skills in the guiding hands of our experts. This bespoke course will include: Presenter self-awareness Essential cultural etiquette Powerful PowerPoint strategies for second-language speakers Linguistic mindfulness A new understanding of ‘less is more’

Your grumpiest customers can become your biggest advocates if you solve their problems quickly, effectively and permanently. We supply the top tips for dealing with tricky customers so your teams can create positive outcomes from every interaction with some simple techniques that make a difference to relationships straight away. Bespoke courses include: Customer needs and expectations Communication styles and how to influence them Assertiveness The 4 psychological fears Dealing with difficult customer behaviour The power of your behaviour Five steps to customer problem solving

Our organisations are increasingly diverse and a cultural mix in training brings a fantastic variety of learning styles and sometimes barriers, too. Help managers and trainers understand the impact of different cultures and nationalities in the training room and make simple adjustments to ensure training is effective for all. Who are you training? Culture and its impact on learning Breaking down cultural learning barriers Intercultural communication Cultural competency and its importance in the training room Training techniques for the diverse classroom Effective questioning and concept checking Having a global mindset

Duration 3 Days 18 CPD hours This course is intended for This course is designed for existing Python programmers who have at least one year of Python experience and who want to expand their programming proficiency in Python 3. Overview In this course, you will expand your Python proficiencies. You will: Select an object-oriented programming approach for Python applications. Create object-oriented Python applications. Create a desktop application. Create data-driven applications. Create and secure web service-connected applications. Program Python for data science. Implement unit testing and exception handling. Package an application for distribution. Python© continues to be a popular programming language, perhaps owing to its easy learning curve, small code footprint, and versatility for business, web, and scientific uses. Python is useful for developing custom software tools, applications, web services, and cloud applications. In this course, you'll build upon your basic Python skills, learning more advanced topics such as object-oriented programming patterns, development of graphical user interfaces, data management, creating web service-connected apps, performing data science tasks, unit testing, and creating and installing packages and executable applications. Lesson 1: Selecting an Object-Oriented Programming Approach for Python Applications Topic A: Implement Object-Oriented Design Topic B: Leverage the Benefits of Object-Oriented Programming Lesson 2: Creating Object-Oriented Python Applications Topic A: Create a Class Topic B: Use Built-in Methods Topic C: Implement the Factory Design Pattern Lesson 3: Creating a Desktop Application Topic A: Design a Graphical User Interface (GUI) Topic B: Create Interactive Applications Lesson 4: Creating Data-Driven Applications Topic A: Connect to Data Topic B: Store, Update, and Delete Data in a Database Lesson 5: Creating and Securing a Web Service-Connected App Topic A: Select a Network Application Protocol Topic B: Create a RESTful Web Service Topic C: Create a Web Service Client Topic D: Secure Connected Applications Lesson 6: Programming Python for Data Science Topic A: Clean Data with Python Topic B: Visualize Data with Python Topic C: Perform Linear Regression with Machine Learning Lesson 7: Implementing Unit Testing and Exception Handling Topic A: Handle Exceptions Topic B: Write a Unit Test Topic C: Execute a Unit Test Lesson 8: Packaging an Application for Distribution Topic A: Create and Install a Package Topic B: Generate Alternative Distribution Files

Duration 3 Days 18 CPD hours This course is intended for This course is designed for existing Python programmers who have at least one year of Python experience and who want to expand their programming proficiency in Python 3. Overview In this course, you will expand your Python proficiencies. You will: Select an object-oriented programming approach for Python applications. Create object-oriented Python applications. Create a desktop application. Create data-driven applications. Create and secure web service-connected applications. Program Python for data science. Implement unit testing and exception handling. Package an application for distribution. Python continues to be a popular programming language, perhaps owing to its easy learning curve, small code footprint, and versatility for business, web, and scientific uses. Python is useful for developing custom software tools, applications, web services, and cloud applications. In this course, you'll build upon your basic Python skills, learning more advanced topics such as object-oriented programming patterns, development of graphical user interfaces, data management, creating web service-connected apps, performing data science tasks, unit testing, and creating and installing packages and executable applications. Lesson 1: Selecting an Object-Oriented Programming Approach for Python Applications Topic A: Implement Object-Oriented Design Topic B: Leverage the Benefits of Object-Oriented Programming Lesson 2: Creating Object-Oriented Python Applications Topic A: Create a Class Topic B: Use Built-in Methods Topic C: Implement the Factory Design Pattern Lesson 3: Creating a Desktop Application Topic A: Design a Graphical User Interface (GUI) Topic B: Create Interactive Applications Lesson 4: Creating Data-Driven Applications Topic A: Connect to Data Topic B: Store, Update, and Delete Data in a Database Lesson 5: Creating and Securing a Web Service-Connected App Topic A: Select a Network Application Protocol Topic B: Create a RESTful Web Service Topic C: Create a Web Service Client Topic D: Secure Connected Applications Lesson 6: Programming Python for Data Science Topic A: Clean Data with Python Topic B: Visualize Data with Python Topic C: Perform Linear Regression with Machine Learning Lesson 7: Implementing Unit Testing and Exception Handling Topic A: Handle Exceptions Topic B: Write a Unit Test Topic C: Execute a Unit Test Lesson 8: Packaging an Application for Distribution Topic A: Create and Install a Package Topic B: Generate Alternative Distribution Files

Duration 3.5 Days 21 CPD hours This course is intended for This course is for AWS Cloud Architects with expertise in designing and implementing solutions running on AWS who now want to design for Microsoft Azure. Overview After completing this course, students will be able to: Secure identities with Azure Active Directory and users and groups. Implement identity solutions spanning on-premises and cloud-based capabilities Apply monitoring solutions for collecting, combining, and analyzing data from different sources. Manage subscriptions, accounts, Azure policies, and Role-Based Access Control. Administer Azure using the Resource Manager, Azure portal, Cloud Shell, and CLI. Configure intersite connectivity solutions like VNet Peering, and virtual network gateways. Administer Azure App Service, Azure Container Instances, and Kubernetes. This course teaches Solutions Architects who have previously designed for Amazon Web Services how to translate business requirements into secure, scalable, and reliable solutions for Azure. Introduction to Azure Subscriptions and accounts Resource groups and templates in Azure Resource Manager Azure global infrastructure Azure regions Azure Availability Zones Comparison with AWS Implement Azure Active Directory Introduction to Azure Active Directory Domains and custom domains Safety features Guest users in Azure Active Directory Manage multiple directories Comparison with AWS Implement and manage hybrid identities Introduction to Azure AD Connect Comparison with AWS Implement virtual networking Azure Virtual Network and VNet peering VPN and ExpressRoute connections Comparison with AWS Implement VMs for Windows and Linux Configure high availability Comparison with AWS Implement load balancing and network security Implement Azure Load Balancer Implement an Azure Application Gateway Implement Azure Firewall Implement network security groups and application security groups Comparison with AWS Implement container-based applications Configure Azure Kubernetes Service Publish a solution on an Azure Container Instance Comparison with AWS Implement an application infrastructure Create an App Service plan Create and configure Azure App Service Configure networking for an App Service Introduction to Logic Apps and Azure Functions Comparison with AWS Implement storage accounts Azure Storage core concepts Managing the Azure Blob storage lifecycle Working with Azure Blob storage Comparison with AWS Implement NoSQL databases Introduction to Azure Cosmos DB Consistency Select appropriate CosmosDB APIs Set up replicas in CosmosDB Comparison with AWS DynamoDB Implement Azure SQL databases Configure Azure SQL database settings Implement Azure SQL Database managed instances Configure high availability for an Azure SQL database Comparison with AWS Implement cloud infrastructure monitoring Monitor security Monitor cost Configure a Log Analytics workspace Comparison with AWS Implement and manage Azure governance solutions Assign RBAC roles Configure management access to Azure Implement and configure an Azure Policy Comparison with AWS Manage security for applications Implement Azure Key Vault Implement and configure Azure AD Managed Identities Register and manage applications in Azure AD Comparison with AWS Migration, backup, and disaster recovery management Migrate workloads Implement Azure Backup for VMs Implement disaster recovery Comparison with AWS

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Course Duration: Half-day or full-day (can also be delivered as a 3-part virtual workshop series) Target Audience: Professionals in non-technical roles (e.g. executive assistants, HR, marketing, project managers, operations staff, trainers, and admin support) who want to use generative AI to enhance their work—without needing coding skills. Course Objectives By the end of this course, participants will be able to: Understand what generative AI is and how it works in plain language. Identify use cases relevant to their role or industry. Use popular generative AI tools (like ChatGPT, Gemini, and Copilot) confidently. Write effective prompts to get better, more relevant results. Apply AI ethically and responsibly in the workplace. Course Outline Module 1: Demystifying Generative AI What is generative AI? (Plain language explanation) How AI models like ChatGPT, Copilot, and Gemini work Examples of what generative AI can (and can’t) do Myths, risks, and benefits of AI in non-tech roles Module 2: Everyday Use Cases for Professionals Time-saving applications: Drafting emails, reports, meeting summaries Creating checklists, plans, or SOPs Enhancing creativity: Brainstorming ideas for events, campaigns, or training Writing social media posts, newsletters, or job ads Organising information: Summarising documents Structuring spreadsheets or creating templates Supporting communication: Improving tone and clarity Translating or simplifying content Module 3: Prompting Essentials What is a “prompt” and why does it matter? How to write clear, specific, and effective prompts Prompting frameworks (e.g., “Role–Task–Goal” method) Live practice: transforming a vague prompt into a powerful one Troubleshooting: when AI gives poor answers and how to improve them Module 4: Hands-On Exploration Try-it-yourself exercises using ChatGPT or Gemini (guided) Real workplace examples and team challenges Create an AI-generated email, checklist, or idea list Optional: use industry-specific examples (e.g., HR, admin, events, comms) Module 5: Responsible AI Use at Work Understanding AI limitations and biases Protecting privacy and sensitive data When not to use AI Workplace policies and guidelines (customisable for your organisation) Ethical use: attribution, transparency, and human review Module 6: Getting Started in Your Role Tools overview: free vs paid options (ChatGPT, Microsoft Copilot, Gemini) Building your own AI toolkit Tips for staying up to date as tools evolve 30-day challenge: how to build AI into your daily workflow Delivery Style Highly interactive, practical, and low-jargon No coding or tech background required Hands-on demos, guided practice, and scenario-based activities Group discussion and peer learning Course Materials Provided Quick-start guide: Top 10 prompts for non-tech roles AI Prompt Library for your job type Do’s and Don’ts for ethical use of AI at work “AI in Action” workbook with examples and checklists Personal AI Action Plan Optional Add-ons Team-based AI hackathon (mini workplace challenge) Tailored follow-up webinar for Q&A and deeper use cases Co-branded playbook for organisational AI use Integration with digital transformation or innovation initiatives

From Curiosity to Clarity: An exciting introduction to NLP Ready to dive into the world of Neuro-Linguistic Programming (NLP)? Join us for an engaging event where you'll discover the power of NLP techniques in communication, personal development, and more. Whether you're a seasoned pro or just curious, this is the perfect opportunity to explore the wonders of NLP.

Course Duration: Half-day or full-day (can also be delivered as a 3-part virtual workshop series) Target Audience: Professionals in non-technical roles (e.g. executive assistants, HR, marketing, project managers, operations staff, trainers, and admin support) who want to use generative AI to enhance their work—without needing coding skills. Course Objectives By the end of this course, participants will be able to: Understand what generative AI is and how it works in plain language. Identify use cases relevant to their role or industry. Use popular generative AI tools (like ChatGPT, Gemini, and Copilot) confidently. Write effective prompts to get better, more relevant results. Apply AI ethically and responsibly in the workplace. Course Outline Module 1: Demystifying Generative AI What is generative AI? (Plain language explanation) How AI models like ChatGPT, Copilot, and Gemini work Examples of what generative AI can (and can’t) do Myths, risks, and benefits of AI in non-tech roles Module 2: Everyday Use Cases for Professionals Time-saving applications: Drafting emails, reports, meeting summaries Creating checklists, plans, or SOPs Enhancing creativity: Brainstorming ideas for events, campaigns, or training Writing social media posts, newsletters, or job ads Organising information: Summarising documents Structuring spreadsheets or creating templates Supporting communication: Improving tone and clarity Translating or simplifying content Module 3: Prompting Essentials What is a “prompt” and why does it matter? How to write clear, specific, and effective prompts Prompting frameworks (e.g., “Role–Task–Goal” method) Live practice: transforming a vague prompt into a powerful one Troubleshooting: when AI gives poor answers and how to improve them Module 4: Hands-On Exploration Try-it-yourself exercises using ChatGPT or Gemini (guided) Real workplace examples and team challenges Create an AI-generated email, checklist, or idea list Optional: use industry-specific examples (e.g., HR, admin, events, comms) Module 5: Responsible AI Use at Work Understanding AI limitations and biases Protecting privacy and sensitive data When not to use AI Workplace policies and guidelines (customisable for your organisation) Ethical use: attribution, transparency, and human review Module 6: Getting Started in Your Role Tools overview: free vs paid options (ChatGPT, Microsoft Copilot, Gemini) Building your own AI toolkit Tips for staying up to date as tools evolve 30-day challenge: how to build AI into your daily workflow Delivery Style Highly interactive, practical, and low-jargon No coding or tech background required Hands-on demos, guided practice, and scenario-based activities Group discussion and peer learning Course Materials Provided Quick-start guide: Top 10 prompts for non-tech roles AI Prompt Library for your job type Do’s and Don’ts for ethical use of AI at work “AI in Action” workbook with examples and checklists Personal AI Action Plan Optional Add-ons Team-based AI hackathon (mini workplace challenge) Tailored follow-up webinar for Q&A and deeper use cases Co-branded playbook for organisational AI use Integration with digital transformation or innovation initiatives