3353 Design courses in Fraserburgh delivered Live Online

Duration 2 Days 12 CPD hours This course is intended for This course is intended for individuals who want to gain basic and intermediate knowledge of working on AutoCAD Overview Upon successful completion of this course, students will be able to create basic and intermediate drawings utilizing the AutoCAD software In this course, you will learn to navigate the AutoCAD user interfaces and use the fundamental features of AutoCAD. You will learn to use the precision drafting tools in AutoCAD to develop accurate technical drawings. Utilizing the AutoCAD Software Startup Screen The Application Menu The AutoCAD User Interface AutoCAD Options [OP] Saving the Drawing ?Places? for Quicker Access of Drawings Wheel Mouse Tidbits The Governing Body of Workspaces Ribbon Management Layer Properties Manager Assigning a Linetype to a New Layer Off vs. Freeze Practical Features of Layer Walk Creating a Layer State Freezing Individual Layers with Layer Freeze Layer Lock Creating Drawings with AutoCAD Accuracy Measuring a Distance Measuring an Area Creating Basic Objects Object Selection Options Basic Editing Commands Polar Tracking Editing Polylines Variable Width Polyline Command Aliases Move and Copy with ?CTRL? Customizing Rollover Tooltips Cycle Through Stacked Objects Additional Selection Options Stretch Midpoint Between Two Points [M2P] Snap From Hatch Stuff Additional course details: Nexus Humans AutoCAD Essentials 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 AutoCAD Essentials 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.

Learn how to channel your inner activist, increase your resilience, communicate directly and be happy not to take no for an answer.

So often change fails because of our own pursuit of perfection. Learning to love imperfect change will improve your resilience and help you deliver positive change.

Learn how to create a digital and data transformation strategy, using system thinking.

Learn how to create people and planet strategies that identify the lifecycles that exist within your business, and promote them widely, helping your business and the planet flourish.

Are you interested in learning how to make polymer clay jewellery? Join us for a fun and informative workshop that will teach you everything you need to know about conditioning the clay, texturing, cutting, shaping the clay, forming and moulding. You'll create a range of finished jewellery pieces that you can take home with you afterwards. This is a great way to learn some new skills and explore a wide variety of style and techniques that are easy enough for beginners but also have room for more advanced learners!

Introduction to Safeguarding Adults and Children The Role of the Designated Person About this event Introduction to Safeguarding Adults and Children The Role of the Designated Person Latest policies, legislation and guidance relating to safeguarding Collaboration and Partnership Training Requirements and Levels Adult training skills enhancement Tools for creating effective sessions

BOHS P903 - Management and control of evaporative cooling and other high risk industrial systems is there to provide background and an overview of the risk of Legionella infection and how it can be controlled in Evaporative Cooling and other high risk Industrial type systems. It is a requirement of this course that candidates have successfully completed P901 - Legionella- Management and Control of Building Hot and Cold Water Services. Where both P901 and P903 courses are run on subsequent days or as a combined course then this prerequisite is waived.

Duration 3 Days 18 CPD hours This course is intended for This course is intended for: Those who will provide container orchestration management in the AWS Cloud including: DevOps engineers Systems administrators Overview In this course, you will learn to: Review and examine containers, Kubernetes and Amazon EKS fundamentals and the impact of containers on workflows. Build an Amazon EKS cluster by selecting the correct compute resources to support worker nodes. Secure your environment with AWS Identity and Access Management (IAM) authentication by creating an Amazon EKS service role for your cluster Deploy an application on the cluster. Publish container images to ECR and secure access via IAM policy. Automate and deploy applications, examine automation tools and pipelines. Create a GitOps pipeline using WeaveFlux. Collect monitoring data through metrics, logs, tracing with AWS X-Ray and identify metrics for performance tuning. Review scenarios where bottlenecks require the best scaling approach using horizontal or vertical scaling. Assess the tradeoffs between efficiency, resiliency, and cost and impact for tuning one over the other. Describe and outline a holistic, iterative approach to optimizing your environment. Design for cost, efficiency, and resiliency. Configure the AWS networking services to support the cluster. Describe how EKS/Amazon Virtual Private Cloud (VPC) functions and simplifies inter-node communications. Describe the function of VPC Container Network Interface (CNI). Review the benefits of a service mesh. Upgrade your Kubernetes, Amazon EKS, and third party tools Amazon EKS makes it easy for you to run Kubernetes on AWS without needing to install, operate, and maintain your own Kubernetes control plane. In this course, you will learn container management and orchestration for Kubernetes using Amazon EKS. You will build an Amazon EKS cluster, configure the environment, deploy the cluster, and then add applications to your cluster. You will manage container images using Amazon Elastic Container Registry (ECR) and learn how to automate application deployment. You will deploy applications using CI/CD tools. You will learn how to monitor and scale your environment by using metrics, logging, tracing, and horizontal/vertical scaling. You will learn how to design and manage a large container environment by designing for efficiency, cost, and resiliency. You will configure AWS networking services to support the cluster and learn how to secure your Amazon EKS environment. Module 0: Course Introduction Course preparation activities and agenda Module 1: Container Fundamentals Best practices for building applications Container fundamentals Components of a container Module 2: Kubernetes Fundamentals Container orchestration Kubernetes objects Kubernetes internals Preparing for Lab 1: Deploying Kubernetes Pods Module 3: Amazon EKS Fundamentals Introduction to Amazon EKS Amazon EKS control plane Amazon EKS data plane Fundamentals of Amazon EKS security Amazon EKS API Module 4: Building an Amazon EKS Cluster Configuring your environment Creating an Amazon EKS cluster Demo: Configuring and deploying clusters in the AWS Management Console Working with eksctl Preparing for Lab 2: Building an Amazon EKS Cluster Module 5: Deploying Applications to Your Amazon EKS Cluster Configuring Amazon Elastic Container Registry (Amazon ECR) Demo: Configuring Amazon ECR Deploying applications with Helm Demo: Deploying applications with Helm Continuous deployment in Amazon EKS GitOps and Amazon EKS Preparing for Lab 3: Deploying App Module 6: Configuring Observability in Amazon EKS Configuring observability in an Amazon EKS cluster Collecting metrics Using metrics for automatic scaling Managing logs Application tracing in Amazon EKS Gaining and applying insight from observability Preparing for Lab 4: Monitoring Amazon EKS Module 7: Balancing Efficiency, Resilience, and Cost Optimization in Amazon EKS The high level overview Designing for resilience Designing for cost optimization Designing for efficiency Module 8: Managing Networking in Amazon EKS Review: Networking in AWS Communicating in Amazon EKS Managing your IP space Deploying a service mesh Preparing for Lab 5: Exploring Amazon EKS Communication Module 9: Managing Authentication and Authorization in Amazon EKS Understanding the AWS shared responsibility model Authentication and authorization Managing IAM and RBAC Demo: Customizing RBAC roles Managing pod permissions using RBAC service accounts Module 10: Implementing Secure Workflows Securing cluster endpoint access Improving the security of your workflows Improving host and network security Managing secrets Preparing for Lab 6: Securing Amazon EKS Module 11: Managing Upgrades in Amazon EKS Planning for an upgrade Upgrading your Kubernetes version Amazon EKS platform versions Additional course details: Nexus Humans Running Containers on Amazon Elastic Kubernetes Service (Amazon EKS) 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 Running Containers on Amazon Elastic Kubernetes Service (Amazon EKS) 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 3 Days 18 CPD hours This course is intended for This course is geared for attendees with solid Python skills who wish to learn and use basic machine learning algorithms and concepts Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course. Topics Covered: This is a high-level list of topics covered in this course. Please see the detailed Agenda below Getting Started & Optional Python Quick Refresher Statistics and Probability Refresher and Python Practice Probability Density Function; Probability Mass Function; Naive Bayes Predictive Models Machine Learning with Python Recommender Systems KNN and PCA Reinforcement Learning Dealing with Real-World Data Experimental Design / ML in the Real World Time Permitting: Deep Learning and Neural Networks Machine Learning Essentials with Python is a foundation-level, three-day hands-on course that teaches students core skills and concepts in modern machine learning practices. This course is geared for attendees experienced with Python, but new to machine learning, who need introductory level coverage of these topics, rather than a deep dive of the math and statistics behind Machine Learning. Students will learn basic algorithms from scratch. For each machine learning concept, students will first learn about and discuss the foundations, its applicability and limitations, and then explore the implementation and use, reviewing and working with specific use casesWorking in a hands-on learning environment, led by our Machine Learning expert instructor, students will learn about and explore:Popular machine learning algorithms, their applicability and limitationsPractical application of these methods in a machine learning environmentPractical use cases and limitations of algorithms Getting Started Installation: Getting Started and Overview LINUX jump start: Installing and Using Anaconda & Course Materials (or reference the default container) Python Refresher Introducing the Pandas, NumPy and Scikit-Learn Library Statistics and Probability Refresher and Python Practice Types of Data Mean, Median, Mode Using mean, median, and mode in Python Variation and Standard Deviation Probability Density Function; Probability Mass Function; Naive Bayes Common Data Distributions Percentiles and Moments A Crash Course in matplotlib Advanced Visualization with Seaborn Covariance and Correlation Conditional Probability Naive Bayes: Concepts Bayes? Theorem Naive Bayes Spam Classifier with Naive Bayes Predictive Models Linear Regression Polynomial Regression Multiple Regression, and Predicting Car Prices Logistic Regression Logistic Regression Machine Learning with Python Supervised vs. Unsupervised Learning, and Train/Test Using Train/Test to Prevent Overfitting Understanding a Confusion Matrix Measuring Classifiers (Precision, Recall, F1, AUC, ROC) K-Means Clustering K-Means: Clustering People Based on Age and Income Measuring Entropy LINUX: Installing GraphViz Decision Trees: Concepts Decision Trees: Predicting Hiring Decisions Ensemble Learning Support Vector Machines (SVM) Overview Using SVM to Cluster People using scikit-learn Recommender Systems User-Based Collaborative Filtering Item-Based Collaborative Filtering Finding Similar Movie Better Accuracy for Similar Movies Recommending movies to People Improving your recommendations KNN and PCA K-Nearest-Neighbors: Concepts Using KNN to Predict a Rating for a Movie Dimensionality Reduction; Principal Component Analysis (PCA) PCA with the Iris Data Set Reinforcement Learning Reinforcement Learning with Q-Learning and Gym Dealing with Real-World Data Bias / Variance Tradeoff K-Fold Cross-Validation Data Cleaning and Normalization Cleaning Web Log Data Normalizing Numerical Data Detecting Outliers Feature Engineering and the Curse of Dimensionality Imputation Techniques for Missing Data Handling Unbalanced Data: Oversampling, Undersampling, and SMOTE Binning, Transforming, Encoding, Scaling, and Shuffling Experimental Design / ML in the Real World Deploying Models to Real-Time Systems A/B Testing Concepts T-Tests and P-Values Hands-on With T-Tests Determining How Long to Run an Experiment A/B Test Gotchas Capstone Project Group Project & Presentation or Review Deep Learning and Neural Networks Deep Learning Prerequisites The History of Artificial Neural Networks Deep Learning in the TensorFlow Playground Deep Learning Details Introducing TensorFlow Using TensorFlow Introducing Keras Using Keras to Predict Political Affiliations Convolutional Neural Networks (CNN?s) Using CNN?s for Handwriting Recognition Recurrent Neural Networks (RNN?s) Using an RNN for Sentiment Analysis Transfer Learning Tuning Neural Networks: Learning Rate and Batch Size Hyperparameters Deep Learning Regularization with Dropout and Early Stopping The Ethics of Deep Learning Learning More about Deep Learning Additional course details: Nexus Humans Machine Learning Essentials with Python (TTML5506-P) 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 Machine Learning Essentials with Python (TTML5506-P) 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.