1233 AI courses in Coventry delivered Live Online

RQF level 1 Awareness of First Aid for Mental Health Each year approximately 1 in 4 people in the UK will experience a mental health condition and at least 1 in 6 employees experience common mental health problems in the workplace. Research has shown that work is the biggest cause of stress which can stop people performing at their best. Mental health conditions are often hidden due to stigma and fear of discrimination and research has shown that a culture of fear and silence around mental health is costly to employers. The HSE guidance 'First aid needs assessment’ refers to mental health in the workplace. This 4-hour qualification provides learners with the knowledge to recognise a range of mental health conditions, how to start a supportive conversation and when and how to signpost a person to seek appropriate professional help. Learners will know how to recognise and manage stress. Learners will not diagnose or treat mental health conditions as this can only be carried out by healthcare professionals but will gain the knowledge to identify when a person may have a condition and know where they can go to get help. Suitability - Who should attend? Here are some examples of who may benefit from attending the RQF Level 1 Award in Awareness of First Aid for Mental Health: Employees and workers: This course is relevant for individuals in any industry who may encounter colleagues or clients experiencing mental health difficulties. It can be particularly valuable for human resources personnel, line managers, supervisors, or team leaders responsible for the well-being of employees. Teachers and educators: Professionals working in schools, colleges, or other educational institutions can benefit from this training to better understand and support the mental health needs of students. Healthcare and social care workers: Individuals working in healthcare or social care settings, such as nurses, care assistants, support workers, or counsellors, can enhance their understanding of mental health issues and improve their ability to provide appropriate support. Community and voluntary workers: People involved in community or voluntary organizations, including youth workers, social workers, volunteers, or community leaders, can gain valuable insights into mental health awareness and support. Personal relationships and caregivers: The Level 1 training can also be beneficial for individuals who have personal relationships with someone experiencing mental health challenges. This may include family members, friends, or caregivers who want to enhance their understanding and offer appropriate assistance. It is important to note that the Level 1 Award in Awareness of First Aid for Mental Health RQF is an introductory course and does not qualify participants to provide formal mental health interventions or therapy. However, it serves as a foundation for further training and can contribute to creating a more mentally healthy and supportive environment in various settings. Outcome / Qualification etc. Upon successful completion of the RQF Level 1 Awareness of First Aid for Mental Health course, participants can expect to achieve the following outcomes: Increased Awareness and Understanding: Participants will develop a basic awareness and understanding of mental health and mental health issues. They will gain knowledge about common mental health conditions, their signs and symptoms, and the importance of mental health in overall well-being. Recognition of Mental Health Signs: Participants will learn to recognize common signs of mental health issues in themselves and others. They will gain an understanding of the importance of early identification and intervention in promoting mental health and seeking appropriate support. Reduced Stigma and Improved Attitudes: The course aims to challenge stigmas and stereotypes associated with mental health. Participants will develop a more empathetic and supportive attitude towards individuals experiencing mental health challenges, promoting a positive and inclusive environment. Enhanced Communication Skills: Participants will learn basic communication skills for engaging with individuals experiencing mental health issues. They will gain an understanding of the importance of active listening, empathy, and non-judgmental communication in providing initial support. Signposting and Seeking Help: Participants will be equipped with knowledge about available resources, services, and support networks for mental health. They will learn about signposting individuals to appropriate professional help and self-help resources. Self-Care and Well-being Strategies: The course may provide participants with practical strategies for maintaining their own mental well-being. They may learn basic self-care techniques and stress management strategies to support their own mental health. Certificate of Completion: Upon successful completion of the course, participants will receive a certificate indicating their achievement of the RQF Level 1 Awareness of First Aid for Mental Health qualification. It's important to note that the Level 1 course provides a basic introduction to mental health awareness and first aid. It is not intended to provide participants with the qualifications or skills to diagnose or treat mental health conditions. Instead, it aims to promote mental health literacy, reduce stigma, and provide individuals with the knowledge to offer initial support and signposting to individuals in need. The Level 1 course can serve as a foundation for further learning and progression in the field of mental health. Individuals may choose to pursue higher-level courses or qualifications to develop more advanced skills and knowledge in mental health first aid or other related areas. Training Course Content MODULE 1 INTRODUCTION Session content Trainer/assessor introduction Learner introductions Course information • Administration • Learning outcomes and assessment criteria • Reasonable adjustments • Certification • Complaints and appeals • Assessment information Session duration 15 minutes MODULE 2 WHAT IS FIRST AID FOR MENTAL HEALTH? Session content Definitions Role and responsibilities of a First Aider The impact of mental health issues Mental health stigma Statistics Session duration 25 minutes MODULE 3 IDENTIFYING MENTAL HEALTH CONDITIONS Session content Mental health continuum Mental health risk factors Early warning signs Session duration 25 minutes MODULE 4 PROVIDING ADVICE AND STARTING A CONVERSATION Session content How to start a difficult conversation Non-judgemental listening skills When to contact the emergency services The First Aider’s own health and emotions Session duration 40 minutes MODULE 5 STRESS Session content What is stress? Causes of stress Effects of stress Coping strategies Session duration 25 minutes MODULE 6 MENTAL HEALTH CONDITIONS Session content Depression Anxiety Psychosis Eating disorders Suicide Self-harm Session duration 70 minutes MODULE 7 ASSESSMENT AND COURSE CLOSURE Session content Written assessment paper Course administration Course closure Session duration 40 minute Course delivery details Classroom-Based A minimum of 4 hours spread over at least one day. Ideally, the course should be run in one day, but must be completed within 2 weeks of starting the course, with each training session a minimum of two hours. Online/Virtual classroom The qualification has 2 assigned guided learning hours (GLH) and 5 hours total qualification time (TQT). GLH indicates the number of contact hours that the learner will have with the trainer/assessor. TQT includes GLH but considers unsupervised learning and is an estimate of how long the average learner will take to achieve the qualification. Why choose Madeleys First Aid Plus Founded in 2021 after Louise left 30 years in the NHS as an Advanced practitioner in A&E/ITU, had spent 1.5 years in Covid ITU Won FSB Best start-up business in the West Midlands in May 2023 Now trained 100's of delegates in Physical and Mental Health First Aid Expenses Travel costs and lunch required, there are many cafes and sandwich bars here in Much Wenlock to buy your lunch, you may eat it in the training room. All training material, books, qualification certificates are included in the price. Continuing Studies After completing the RQF Level 1 Awareness of First Aid for Mental Health course, individuals can consider various progression options to further their knowledge and skills in mental health support. Here are some potential pathways: RQF Level 2 Award in First Aid for Mental Health: This qualification builds upon the knowledge gained in the Level 1 course and provides a more comprehensive understanding of mental health issues and how to provide appropriate support. It covers topics such as recognizing mental health conditions, promoting well-being, and providing initial support to those in crisis. RQF Level 3 Award in Supervising First Aid for Mental Health: For individuals who aspire to take on leadership or supervisory roles in mental health support, the Level 3 qualification is a logical progression. It provides in-depth knowledge and skills to supervise and manage a team of individuals providing first aid for mental health. Continued Professional Development (CPD): Engaging in ongoing CPD activities is essential for staying updated with the latest developments in mental health support. Individuals can attend workshops, seminars, or conferences related to mental health, trauma, or specific areas of interest within the field. Applied Practice: Applying the knowledge gained from the Level 1 course in real-world settings is crucial for developing practical skills. Individuals can seek opportunities to work or volunteer in environments where mental health support is needed, such as community organizations, schools, or helplines. Mental Health Support Training Programs: There are various specialized training programs available that focus on specific aspects of mental health support, such as suicide prevention, trauma-informed care, or supporting individuals with specific mental health conditions. These programs can provide individuals with additional expertise and deepen their understanding of specific areas within mental health support. Higher Education: Individuals who wish to pursue a more in-depth study of mental health can consider higher education programs in psychology, counseling, social work, or related fields. These programs provide comprehensive knowledge and training in mental health support and may lead to professional certifications or degrees. It's important for individuals to research and explore progression options that align with their specific career goals, interests, and local requirements. Different countries or regions may have varying certification or training requirements for mental health support roles, so it's advisable to check with relevant regulatory bodies or professional associations for specific guidance.

Duration 1 Days 6 CPD hours This course is intended for The audience for this course includes software developers and data scientists who need to use large language models for generative AI. Some programming experience is recommended, but the course will be valuable to anyone seeking to understand how the Azure OpenAI service can be used to implement generative AI solutions. Note Generative AI is a fast-evolving field of artificial intelligence, and the Azure OpenAI service is subject to frequent changes. The course materials are maintained to reflect the latest version of the service at the time of writing. Azure OpenAI Service provides access to OpenAI's powerful large language models such as GPT; the model behind the popular ChatGPT service. These models enable various natural language processing (NLP) solutions to understand, converse, and generate content. Users can access the service through REST APIs, SDKs, and Azure OpenAI Studio. In this course, you'll learn how to provision Azure OpenAI service, deploy models, and use them in generative AI applications. Prerequisites Familiarity with Azure and the Azure portal. Experience programming with C# or Python. 1 - Get started with Azure OpenAI Service Access Azure OpenAI Service Use Azure OpenAI Studio Explore types of generative AI models Deploy generative AI models Use prompts to get completions from models Test models in Azure OpenAI Studio's playgrounds 2 - Build natural language solutions with Azure OpenAI Service Integrate Azure OpenAI into your app Use Azure OpenAI REST API Use Azure OpenAI SDK 3 - Apply prompt engineering with Azure OpenAI Service Understand prompt engineering Write more effective prompts Provide context to improve accuracy 4 - Generate code with Azure OpenAI Service Construct code from natural language Complete code and assist the development process Fix bugs and improve your code 5 - Generate images with Azure OpenAI Service What is DALL-E? Explore DALL-E in Azure OpenAI Studio Use the Azure OpenAI REST API to consume DALL-E models 6 - Use your own data with Azure OpenAI Service Understand how to use your own data Add your own data source Chat with your model using your own data Additional course details: Nexus Humans AI-050T00: Develop Generative AI Solutions with Azure OpenAI Service 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 AI-050T00: Develop Generative AI Solutions with Azure OpenAI Service 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.

Introduction to AI for Business

The Mechanics of Mediumship. A beginners guide to everything you need to know. How to become a professional psychic medium. Able to give short, accurate, evidential messages. This course runs over 5 weeks and during our time together we will explore five easy to follow parts. 1: What mediumship is and the different types, including your role as a professional medium and the differences between working in the psychic modality and when you are connected to spirit. 2: Activating and building your power within, and the difference between meditation, and attunement both to the spirit world and using your psychic modality. 3: The six different senses available to you, which are your strongest and whether you are perceiving them objectively or subjectively. 4: What is and what is not evidence in mediumship, understanding the different types of evidence available and defining practical and emotional evidence. 5: Surrendering to spirit, building confidence to receive specific unique information, and understanding the reasons why you receive a no response. Guidance on making positive, strong, statements filling your sitter with confidence, building a truly extraordinary professional reading.

Duration 2 Days 12 CPD hours This course is intended for This course is intended for software testers, architects, engineers, or other related roles, who wish to apply AI to software testing practices within their enterprise. While there are no specific pre-requisites for this course, it would be helpful is the attendee has familiarity with basic scripting (Python preferred) and be comfortable with working from the command line (for courses that add the optional hands-on labs). Attendees without basic scripting skills can follow along with the hands-on labs or demos. Overview This course introduces AI and related technologies from a practical applied software testing perspective. Through engaging lecture and demonstrations presented by our expert facilitator, students will explore: Exploring AI Introduction to Machine Learning Introduction to Deep Learning Introduction to Data Science Artificial Intelligence (AI) in Software Testing Implementing AI in Test Automation Innovative AI Test Automation Tools for the Future Implementing AI in Software Testing / AI in Test Automation is an introductory-level course for attendees new to AI, Machine Learning or Deep Learning who wish to automate software testing tasks leveraging AI. The course explores the essentials of AI, ML and DL and how the integrate into IT business operations and initiatives. Then the course moves to specifics about the skills, techniques and tools used to apply AI to common software testing requirements. Exploring AI AI-Initiatives The Priority: Excellence AI- Intelligence Types The Machine Learning Types The Quality Learning Initiative The Inception in Academics AI - Importance & Applications The Re-visit Learning Re-visited via AI Teaching in the world of AI Exploring AI for Self-Development AI In Academics Beyond Academics Introduction to Machine Learning What is Machine Learning? Why Machine Learning? Examples - Algorithms behind Machine Learning Introduction to Deep Learning What is Deep Learning? Why Deep Learning? Example - Deep Learning Vs Machine Learning Introduction to Data Science What is Data Science? Why Data Science? Examples - Use Cases of Data Science Artificial Intelligence (AI) in Software Testing What is AI in Software Testing? The Role of AI Testing Why do we Need AI in Software Testing? Pros and Cons of AI in Software Testing Applications of AI in Software Testing Is it time for Testers or QA Teams to worry about AI? Automated Testing with Artificial Intelligence Implementing AI in Test Automation Training the AI Bots Challenges with AI-powered Applications Examples - Real World use cases using Artificial Intelligence Demo - Facial Emotion Detection Using Artificial Intelligence Demo - Text Analysis API Using Artificial Intelligence Demo - EYE SPY Mobile App Using Artificial Intelligence Innovative AI Test Automation Tools for the Future Tools used for Implementing AI in Automation Testing What is NEXT? AI Test Automation Demo using Testim

Duration 1 Days 6 CPD hours This course is intended for The Azure AI Fundamentals course is designed for anyone interested in learning about the types of solution artificial intelligence (AI) makes possible, and the services on Microsoft Azure that you can use to create them. You don?t need to have any experience of using Microsoft Azure before taking this course, but a basic level of familiarity with computer technology and the Internet is assumed. Some of the concepts covered in the course require a basic understanding of mathematics, such as the ability to interpret charts. The course includes hands-on activities that involve working with data and running code, so a knowledge of fundamental programming principles will be helpful. This course introduces fundamentals concepts related to artificial intelligence (AI), and the services in Microsoft Azure that can be used to create AI solutions. The course is not designed to teach students to become professional data scientists or software developers, but rather to build awareness of common AI workloads and the ability to identify Azure services to support them. Prerequisites Prerequisite certification is not required before taking this course. Successful Azure AI Fundamental students start with some basic awareness of computing and internet concepts, and an interest in using Azure AI services. Specifically: Experience using computers and the internet. Interest in use cases for AI applications and machine learning models. A willingness to learn through hands-on exp... 1 - Fundamental AI Concepts Understand machine learning Understand computer vision Understand natural language processing Understand document intelligence and knowledge mining Understand generative AI Challenges and risks with AI Understand Responsible AI 2 - Fundamentals of machine learning What is machine learning? Types of machine learning Regression Binary classification Multiclass classification Clustering Deep learning Azure Machine Learning 3 - Fundamentals of Azure AI services AI services on the Azure platform Create Azure AI service resources Use Azure AI services Understand authentication for Azure AI services 4 - Fundamentals of Computer Vision Images and image processing Machine learning for computer vision Azure AI Vision 5 - Fundamentals of Facial Recognition Understand Face analysis Get started with Face analysis on Azure 6 - Fundamentals of optical character recognition Get started with Vision Studio on Azure 7 - Fundamentals of Text Analysis with the Language Service Understand Text Analytics Get started with text analysis 8 - Fundamentals of question answering with the Language Service Understand question answering Get started with the Language service and Azure Bot Service 9 - Fundamentals of conversational language understanding Describe conversational language understanding Get started with conversational language understanding in Azure 10 - Fundamentals of Azure AI Speech Understand speech recognition and synthesis Get started with speech on Azure 11 - Fundamentals of Azure AI Document Intelligence Explore capabilities of document intelligence Get started with receipt analysis on Azure 12 - Fundamentals of Knowledge Mining with Azure Cognitive Search What is Azure Cognitive Search? Identify elements of a search solution Use a skillset to define an enrichment pipeline Understand indexes Use an indexer to build an index Persist enriched data in a knowledge store Create an index in the Azure portal Query data in an Azure Cognitive Search index 13 - Fundamentals of Generative AI What is generative AI? Large language models What is Azure OpenAI? What are copilots? Improve generative AI responses with prompt engineering 14 - Fundamentals of Azure OpenAI Service What is generative AI Describe Azure OpenAI How to use Azure OpenAI Understand OpenAI's natural language capabilities Understand OpenAI code generation capabilities Understand OpenAI's image generation capabilities Describe Azure OpenAI's access and responsible AI policies 15 - Fundamentals of Responsible Generative AI Plan a responsible generative AI solution Identify potential harms Measure potential harms Mitigate potential harms Operate a responsible generative AI solution Additional course details: Nexus Humans AI-900T00 - Microsoft Azure AI Fundamentals 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 AI-900T00 - Microsoft Azure AI Fundamentals 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 Software engineers concerned with building, managing and deploying AI solutions that leverage Azure AI Services, Azure AI Search, and Azure OpenAI. They are familiar with C# or Python and have knowledge on using REST-based APIs to build computer vision, language analysis, knowledge mining, intelligent search, and generative AI solutions on Azure. AI-102 Designing and Implementing an Azure AI Solution is intended for software developers wanting to build AI infused applications that leverage?Azure AI Services,?Azure AI Search, and?Azure OpenAI. The course will use C# or Python as the programming language. Prerequisites Before attending this course, students must have: Knowledge of Microsoft Azure and ability to navigate the Azure portal Knowledge of either C# or Python Familiarity with JSON and REST programming semantics Recommended course prerequisites AI-900T00: Microsoft Azure AI Fundamentals course 1 - Prepare to develop AI solutions on Azure Define artificial intelligence Understand AI-related terms Understand considerations for AI Engineers Understand considerations for responsible AI Understand capabilities of Azure Machine Learning Understand capabilities of Azure AI Services Understand capabilities of the Azure Bot Service Understand capabilities of Azure Cognitive Search 2 - Create and consume Azure AI services Provision an Azure AI services resource Identify endpoints and keys Use a REST API Use an SDK 3 - Secure Azure AI services Consider authentication Implement network security 4 - Monitor Azure AI services Monitor cost Create alerts View metrics Manage diagnostic logging 5 - Deploy Azure AI services in containers Understand containers Use Azure AI services containers 6 - Analyze images Provision an Azure AI Vision resource Analyze an image Generate a smart-cropped thumbnail 7 - Classify images Provision Azure resources for Azure AI Custom Vision Understand image classification Train an image classifier 8 - Detect, analyze, and recognize faces Identify options for face detection analysis and identification Understand considerations for face analysis Detect faces with the Azure AI Vision service Understand capabilities of the face service Compare and match detected faces Implement facial recognition 9 - Read Text in images and documents with the Azure AI Vision Service Explore Azure AI Vision options for reading text Use the Read API 10 - Analyze video Understand Azure Video Indexer capabilities Extract custom insights Use Video Analyzer widgets and APIs 11 - Analyze text with Azure AI Language Provision an Azure AI Language resource Detect language Extract key phrases Analyze sentiment Extract entities Extract linked entities 12 - Build a question answering solution Understand question answering Compare question answering to Azure AI Language understanding Create a knowledge base Implement multi-turn conversation Test and publish a knowledge base Use a knowledge base Improve question answering performance 13 - Build a conversational language understanding model Understand prebuilt capabilities of the Azure AI Language service Understand resources for building a conversational language understanding model Define intents, utterances, and entities Use patterns to differentiate similar utterances Use pre-built entity components Train, test, publish, and review a conversational language understanding model 14 - Create a custom text classification solution Understand types of classification projects Understand how to build text classification projects 15 - Create a custom named entity extraction solution Understand custom named entity recognition Label your data Train and evaluate your model 16 - Translate text with Azure AI Translator service Provision an Azure AI Translator resource Specify translation options Define custom translations 17 - Create speech-enabled apps with Azure AI services Provision an Azure resource for speech Use the Azure AI Speech to Text API Use the text to speech API Configure audio format and voices Use Speech Synthesis Markup Language 18 - Translate speech with the Azure AI Speech service Provision an Azure resource for speech translation Translate speech to text Synthesize translations 19 - Create an Azure AI Search solution Manage capacity Understand search components Understand the indexing process Search an index Apply filtering and sorting Enhance the index 20 - Create a custom skill for Azure AI Search Create a custom skill Add a custom skill to a skillset 21 - Create a knowledge store with Azure AI Search Define projections Define a knowledge store 22 - Plan an Azure AI Document Intelligence solution Understand AI Document Intelligence Plan Azure AI Document Intelligence resources Choose a model type 23 - Use prebuilt Azure AI Document Intelligence models Understand prebuilt models Use the General Document, Read, and Layout models Use financial, ID, and tax models 24 - Extract data from forms with Azure Document Intelligence What is Azure Document Intelligence? Get started with Azure Document Intelligence Train custom models Use Azure Document Intelligence models Use the Azure Document Intelligence Studio 25 - Get started with Azure OpenAI Service Access Azure OpenAI Service Use Azure OpenAI Studio Explore types of generative AI models Deploy generative AI models Use prompts to get completions from models Test models in Azure OpenAI Studio's playgrounds 26 - Build natural language solutions with Azure OpenAI Service Integrate Azure OpenAI into your app Use Azure OpenAI REST API Use Azure OpenAI SDK 27 - Apply prompt engineering with Azure OpenAI Service Understand prompt engineering Write more effective prompts Provide context to improve accuracy 28 - Generate code with Azure OpenAI Service Construct code from natural language Complete code and assist the development process Fix bugs and improve your code 29 - Generate images with Azure OpenAI Service What is DALL-E? Explore DALL-E in Azure OpenAI Studio Use the Azure OpenAI REST API to consume DALL-E models 30 - Use your own data with Azure OpenAI Service Understand how to use your own data Add your own data source Chat with your model using your own data 31 - Fundamentals of Responsible Generative AI Plan a responsible generative AI solution Identify potential harms Measure potential harms Mitigate potential harms Operate a responsible generative AI solution

Mental Health First Aid (MHFA) England Training with Mindmaps Wellbeing Enhance workplace wellbeing and mental health awareness with MHFA England-certified training by Mindmaps Wellbeing. Our expert-led courses, delivered by Registered Mental Health Nurses and Healthcare Educators, equip you with the skills to recognize, support, and respond to mental health challenges. Whether online or in-person, our training ensures flexible learning options without compromising quality. Join us to gain certification as a Mental Health First Aider and access exclusive benefits like ongoing peer support, expert forums, and resources for self-care. Book now with Mindmaps Wellbeing and take the first step toward a healthier, more supportive environment for all.

Aligned with the AIGP certification program, AI Governance Professional Training is for professionals tasked with implementing AI governance and risk management in their organizations. It provides baseline knowledge and strategies for responding to complex risks associated with the evolving AI landscape. This training meets the rapidly growing need for professionals who can develop, integrate and deploy trustworthy AI systems in line with emerging laws and policies. About This Course This training teaches critical artificial intelligence governance concepts that are also integral to the AIGP certification exam. While not purely a 'test prep' course, this training is appropriate for professionals who plan to certify, as well as for those who want to deepen their AI governance knowledge. Both the training and the exam are based on the same body of knowledge.   Module 1: Foundations of artificial intelligence Defines AI and machine learning, presents an overview of the different types of AI systems and their use cases, and positions AI models in the broader socio-cultural context. Module 2: AI impacts on people and responsible AI principles Outlines the core risks and harms posed by AI systems, the characteristics of trustworthy AI systems, and the principles essential to responsible and ethical AI. Module 3: AI development life cycle Describes the AI development life cycle and the broad context in which AI risks are managed. Module 4: Implementing responsible AI governance and risk management Explains how major AI stakeholders collaborate in a layered approach to manage AI risks while acknowledging AI systems' potential societal benefits. Module 5: Implementing AI projects and systems Outlines mapping, planning and scoping AI projects, testing and validating AI systems during development, and managing and monitoring AI systems after deployment. Module 6: Current laws that apply to AI systems Surveys the existing laws that govern the use of AI, outlines key GDPR intersections, and provides awareness of liability reform. Module 7: Existing and emerging AI laws and standards Describes global AI-specific laws and the major frameworks and standards that exemplify how AI systems can be responsibly governed. Module 8: Ongoing AI issues and concerns Presents current discussions and ideas about AI governance, including awareness of legal issues, user concerns, and AI auditing and accountability issues. Accreditation The associated exam is accredited by the IAPP under its ANSI Accreditation Who Should Attend? Any professionals tasked with developing AI governance and risk management in their operations, and anyone pursuing IAPP Artificial Intelligence Governance Professional certification. Prerequisites A general understanding of AI, Corporate Governance, and Business value would be of benefit to participants. Assessment As with all IAPP exams, the AIGP is a 90 question, multiple choice exam to be completed within 150 minutes. Exams are hosted by Pearsonvue and can be taken either remotely, or via any one of hundreds of exam venues globally. A passing score is achieved at 70% Our Guarantee We are an approved IAPP training provider Exam pass guarantee, or retrain until you do, for free What's Included? Participant Guide Study Guide Practice Exam Exam voucher Breakfast, lunch, coffees and snacks (Classroom courses only) Certification Logo

ChatGPT, along with other AI tools, aims not to replace the human touch in management, but to enhance it. By addressing repetitive, daily tasks, these tools free up managers to concentrate on core responsibilities like strategic decision-making, team development, and innovation. As we move further into the digital age, integrating tools such as ChatGPT isn't a luxury; it's the future of proactive leadership. In this guide, we'll delve into 10 practical ways through which AI can elevate your efficiency and refine the quality of your work. Gain familiarity with prominent AI tools in the market Efficiently compose and respond to emails Generate concise summaries of complex reports and data. Obtain quick insights, data, and research across varied topics Streamline the writing of articles, training notes, and posts Craft interview tests, form relevant questions, and design checklists for the hiring process 1 Streamlining emails An inbox can be a goldmine of information but also a significant time drain for managers. Here's how to optimise it: Drafting responses: Give the AI a brief, and watch it craft a well-structured response. Sorting and prioritising: By employing user-defined rules and keywords, ChatGPT can flag important emails, ensuring no vital communication slips through the cracks. 2 Efficient report writing Reports, especially routine ones, can be time-intensive. Here's a smarter approach: Automate content: Supply key data points to the AI, and let it weave them into an insightful report. Proofreading: Lean on ChatGPT for grammar checks and consistency, ensuring each report remains crisp and error-free. 3 Rapid research From competitor insights to market trends, research is a pivotal part of management. Data synthesis: Feed raw data to the AI and receive succinct summaries in return. Question-answering: Pose specific questions about a dataset to ChatGPT and extract swift insights without diving deep into the entire content. 4 Reinventing recruitment Hiring can be a lengthy process. Here's how to make it more efficient: Resume screening: Equip the AI to spot keywords and qualifications, ensuring that only the most fitting candidates are shortlisted. Preliminary interviews: Leverage ChatGPT for the initial rounds of interviews by framing critical questions and evaluating the responses. 5 Enhancing training Especially for extensive teams, training can be a monumental task. Here's how ChatGPT can assist: Customised content: Inform the AI of your training goals, and it will draft tailored content suitable for various roles. PowerPoint design: Create visually appealing slide presentations on any topic in minimal time.