2858 Learning courses in Cardiff delivered Live Online

This week long CPD accredited training is ideal for those Real Estate professionals, who are looking to bolster the DCF modelling skills. This course covers Real Estate Investment, Development, Finance & Risk.

Leading People through Change: In-House Training Research shows that 70% of change initiatives fail in large organizations. The largest factor contributing to this failure rate is leadership - the inability to plan and lead people through change. In many change situations, tremendous focus is put on strategy, processes, and systems, while the issue of changing people's behavior is assumed it will 'just happen'. In this interactive course, you will learn why the people side of change is crucial. We will begin by understanding why and how people resist change, and how important it is to become strong and effective change champions. Next, we will focus on critical change management practices - creating our vision of the future state, planning for acceptance in our change audience and stakeholders, mitigating threats, and capitalizing on opportunities. We will use metrics to plan, show progress, and confirm success. Lastly, we will focus on the need to reinforce and sustain change, and to prevent relapse to old ways and methods. What you will Learn At the end of this program, you will be able to: Realize the nature of change and describe how resistance manifests in people Compare prevalent change models and categorize their similarities Identify and rate the skills, traits, and behaviors of effective change champions Envision the future state and assess stakeholders Plan for change communication, training, and risks Evaluate change effectiveness using feedback and metrics Develop reinforcement practices for benefits and communication Foundation Concepts What is Change? Resistance to Change Common Change Management Theories Becoming a Change Champion Plan Envisioning the future state Planning for people Change management plan Do Change communication Training Piloting Risks Study Feedback Metrics Variance analysis Act Benefits realization Change sustainment Reinforcement messaging and communications

E-Learning courses are self study courses which students can join from anywhere in the world.

Join us for this one-day online course and discover what makes quality teaching of history by exploring how to ensure coverage of the National Curriculum through practical creative methods.

Duration 3 Days 18 CPD hours This course is intended for This course is geared for experienced Scala developers who are new to the world of machine learning and are eager to expand their skillset. Professionals such as data engineers, data scientists, and software engineers who want to harness the power of machine learning in their Scala-based projects will greatly benefit from attending. Additionally, team leads and technical managers who oversee Scala development projects and want to integrate machine learning capabilities into their workflows can gain valuable insights from this course Overview Working in a hands-on learning environment led by our expert instructor you'll: Grasp the fundamentals of machine learning and its various categories, empowering you to make informed decisions about which techniques to apply in different situations. Master the use of Scala-specific tools and libraries, such as Breeze, Saddle, and DeepLearning.scala, allowing you to efficiently process, analyze, and visualize data for machine learning projects. Develop a strong understanding of supervised and unsupervised learning algorithms, enabling you to confidently choose the right approach for your data and effectively build predictive models Gain hands-on experience with neural networks and deep learning, equipping you with the know-how to create advanced applications in areas like natural language processing and image recognition. Explore the world of generative AI and learn how to utilize GPT-Scala for creative text generation tasks, broadening your skill set and making you a more versatile developer. Conquer the realm of scalable machine learning with Scala, learning the secrets to tackling large-scale data processing and analysis challenges with ease. Sharpen your skills in model evaluation, validation, and optimization, ensuring that your machine learning models perform reliably and effectively in any situation. Machine Learning Essentials for Scala Developers is a three-day course designed to provide a solid introduction to the world of machine learning using the Scala language. Throughout the hands-on course, you?ll explore a range of machine learning algorithms and techniques, from supervised and unsupervised learning to neural networks and deep learning, all specifically crafted for Scala developers. Our expert trainer will guide you through real-world, focused hands-on labs designed to help you apply the knowledge you gain in real-world scenarios, giving you the confidence to tackle machine learning challenges in your own projects. You'll dive into innovative tools and libraries such as Breeze, Saddle, DeepLearning.scala, GPT-Scala (and Generative AI with Scala), and TensorFlow-Scala. These cutting-edge resources will enable you to build and deploy machine learning models for a wide range of projects, including data analysis, natural language processing, image recognition and more. Upon completing this course, you'll have the skills required to tackle complex projects and confidently develop intelligent applications. You?ll be able to drive business outcomes, optimize processes, and contribute to innovative projects that leverage the power of data-driven insights and predictions. Introduction to Machine Learning and Scala Learning Outcome: Understand the fundamentals of machine learning and Scala's role in this domain. What is Machine Learning? Machine Learning with Scala: Advantages and Use Cases Supervised Learning in Scala Learn the basics of supervised learning and how to apply it using Scala. Supervised Learning: Regression and Classification Linear Regression in Scala Logistic Regression in Scala Unsupervised Learning in Scala Understand unsupervised learning and how to apply it using Scala. Unsupervised Learning:Clustering and Dimensionality Reduction K-means Clustering in Scala Principal Component Analysis in Scala Neural Networks and Deep Learning in Scala Learning Outcome: Learn the basics of neural networks and deep learning with a focus on implementing them in Scala. Introduction to Neural Networks Feedforward Neural Networks in Scala Deep Learning and Convolutional Neural Networks Introduction to Generative AI and GPT in Scala Gain a basic understanding of generative AI and GPT, and how to utilize GPT-Scala for natural language tasks. Generative AI: Overview and Use Cases Introduction to GPT (Generative Pre-trained Transformer) GPT-Scala: A Library for GPT in Scala Reinforcement Learning in Scala Understand the basics of reinforcement learning and its implementation in Scala. Introduction to Reinforcement Learning Q-learning and Value Iteration Reinforcement Learning with Scala Time Series Analysis using Scala Learn time series analysis techniques and how to apply them in Scala. Introduction to Time Series Analysis Autoregressive Integrated Moving Average (ARIMA) Models Time Series Analysis in Scala Natural Language Processing (NLP) with Scala Gain an understanding of natural language processing techniques and their application in Scala. Introduction to NLP: Techniques and Applications Text Processing and Feature Extraction NLP Libraries and Tools for Scala Image Processing and Computer Vision with Scala Learn image processing techniques and computer vision concepts with a focus on implementing them in Scala. Introduction to Image Processing and Computer Vision Feature Extraction and Image Classification Image Processing Libraries for Scala Model Evaluation and Validation Understand the importance of model evaluation and validation, and how to apply these concepts using Scala. Model Evaluation Metrics Cross-Validation Techniques Model Selection and Tuning in Scala Scalable Machine Learning with Scala Learn how to handle large-scale machine learning problems using Scala. Challenges of Large-Scale Machine Learning Data Partitioning and Parallelization Distributed Machine Learning with Scala Machine Learning Deployment and Production Understand the process of deploying machine learning models into production using Scala. Deployment Challenges and Best Practices Model Serialization and Deserialization Monitoring and Updating Models in Production Ensemble Learning Techniques in Scala Discover ensemble learning techniques and their implementation in Scala. Introduction to Ensemble Learning Bagging and Boosting Techniques Implementing Ensemble Models in Scala Feature Engineering for Machine Learning in Scala Learn advanced feature engineering techniques to improve machine learning model performance in Scala. Importance of Feature Engineering in Machine Learning Feature Scaling and Normalization Techniques Handling Missing Data and Categorical Features Advanced Optimization Techniques for Machine Learning Understand advanced optimization techniques for machine learning models and their application in Scala. Gradient Descent and Variants Regularization Techniques (L1 and L2) Hyperparameter Tuning Strategies

Learn and practice the skills needed to deliver a brilliant presentation.

This half-day workshop delivered face-to-face or online is designed for anyone in your organisation that wants to become a Neurodiversity Champion - someone who wants to educate and change the way that Neurodiversity is viewed in the workplace.

Formation officielle BRCGS Food v9 (Norme Mondiale pour la Sécurité des Denrées Alimentaires version 9) pour les sites en français. Dispensée en ligne (Zoom) en direct par un partenaire de formation agréé BRCGS. Frais d'examen et de certificat inclus dans le prix.

Duration 1 Days 6 CPD hours This course is intended for This course is intended for individuals who want to develop a core set of soft skill. Overview Upon successful completion of this course, students will be able to better interact and communicate in the workplace. In this course, students will develop a core set of soft skills by managing and looking at the way people interact and seeing things in a new light. 1 - GETTING STARTED Housekeeping Items Pre-Assignment Review Workshop Objectives The Parking Lot Action Plan 2 - WHAT ARE SOFT SKILLS? Definition of Soft Skills Empathy and the Emotional Intelligence Quotient Professionalism Learned vs. Inborn Traits 3 - SOFT SKILL 1: COMMUNICATION Ways We Communicate Improving Non-Verbal Communication Listening Openness and Honesty 4 - SOFT SKILL 2: TEAMWORK Identifying Capabilities Get Into Your Role Learn the Whole Process The Power of Flow 5 - SOFT SKILL 3: PROBLEM SOLVING Define the Problem Generate Alternative Solutions Evaluate the Plans Implementation and Re-evaluation 6 - SOFT SKILL 4: TIME MANAGEMENT The Art of Scheduling Prioritizing Managing Distractions The Multitasking Myth 7 - SOFT SKILL 5 AND 6: ATTITUDE AND WORK ETHIC What Are You Working For? Caring for Others vs. Self Building Trust Work Is Its Own Reward 8 - SOFT SKILL 7: ADAPTABILITY/FLEXIBILITY Getting over the Good Old Days Syndrome Changing to Manage Process Changing to Manage People Showing You're Worth Your Weight in Adaptability 9 - SOFT SKILL 8: SELF-CONFIDENCE Confident Traits Self-Questionnaire Surefire Confidence Building Tactics Build Up Others 10 - SOFT SKILL 9: ABILITY TO LEARN FROM CRITICISM Wow, You Mean I'm Not Perfect? Listen With An Open Mind Analyze and Learn Clear the Air and Don't Hold Any Grudges 11 - SOFT SKILL 10: NETWORKING Redefining Need Identifying Others' Interests Reaching Out When to Back Off 12 - WRAPPING UP Words From The Wise Review Of The Parking Lot Lessons Learned Recommended Reading Completion Of Action Plans And Evaluations Additional course details: Nexus Humans 10 Soft Skills You Need 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 10 Soft Skills You Need course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 4 Days 24 CPD hours This course is intended for This course is intended for: Developers Solutions Architects Data Engineers Anyone with little to no experience with ML and wants to learn about the ML pipeline using Amazon SageMaker Overview In this course, you will learn to: Select and justify the appropriate ML approach for a given business problem Use the ML pipeline to solve a specific business problem Train, evaluate, deploy, and tune an ML model using Amazon SageMaker Describe some of the best practices for designing scalable, cost-optimized, and secure ML pipelines in AWS Apply machine learning to a real-life business problem after the course is complete This course explores how to use the machine learning (ML) pipeline to solve a real business problem in a project-based learning environment. Students will learn about each phase of the pipeline from instructor presentations and demonstrations and then apply that knowledge to complete a project solving one of three business problems: fraud detection, recommendation engines, or flight delays. By the end of the course, students will have successfully built, trained, evaluated, tuned, and deployed an ML model using Amazon SageMaker that solves their selected business problem. Module 0: Introduction Pre-assessment Module 1: Introduction to Machine Learning and the ML Pipeline Overview of machine learning, including use cases, types of machine learning, and key concepts Overview of the ML pipeline Introduction to course projects and approach Module 2: Introduction to Amazon SageMaker Introduction to Amazon SageMaker Demo: Amazon SageMaker and Jupyter notebooks Hands-on: Amazon SageMaker and Jupyter notebooks Module 3: Problem Formulation Overview of problem formulation and deciding if ML is the right solution Converting a business problem into an ML problem Demo: Amazon SageMaker Ground Truth Hands-on: Amazon SageMaker Ground Truth Practice problem formulation Formulate problems for projects Module 4: Preprocessing Overview of data collection and integration, and techniques for data preprocessing and visualization Practice preprocessing Preprocess project data Class discussion about projects Module 5: Model Training Choosing the right algorithm Formatting and splitting your data for training Loss functions and gradient descent for improving your model Demo: Create a training job in Amazon SageMaker Module 6: Model Evaluation How to evaluate classification models How to evaluate regression models Practice model training and evaluation Train and evaluate project models Initial project presentations Module 7: Feature Engineering and Model Tuning Feature extraction, selection, creation, and transformation Hyperparameter tuning Demo: SageMaker hyperparameter optimization Practice feature engineering and model tuning Apply feature engineering and model tuning to projects Final project presentations Module 8: Deployment How to deploy, inference, and monitor your model on Amazon SageMaker Deploying ML at the edge Demo: Creating an Amazon SageMaker endpoint Post-assessment Course wrap-up Additional course details: Nexus Humans The Machine Learning Pipeline on AWS 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 The Machine Learning Pipeline on AWS 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.