161 PIP courses delivered Live Online

For new users and the curious. Hello, For new users and the curious. IMPORTANT: Firstly, once you are signed up, send us your requests on what you would like to see within the demonstration and learn on the course. We will then cater for your needs and answer them during the session. This is designed to be an introduction into how to start a room by room survey using the Heat Engineer app, then sending this survey to the online dashboard. We will then go through the different steps to complete this heat loss report. Optional pages will also be worked through and shown. Examples of how to select the flow temperature and the heat source (heat pumps and boilers) will be presented once the heat loss result is completed.

For new users and the curious. Hello, For new users and the curious. IMPORTANT: Firstly, once you are signed up, send us your requests on what you would like to see within the demonstration and learn on the course. We will then cater for your needs and answer them during the session. This is designed to be an introduction into how to start a room by room survey using the Heat Engineer app, then sending this survey to the online dashboard. We will then go through the different steps to complete this heat loss report. Optional pages will also be worked through and shown. Examples of how to select the flow temperature and the heat source (heat pumps and boilers) will be presented once the heat loss result is completed.

For new users and the curious. Hello, For new users and the curious. IMPORTANT: Firstly, once you are signed up, send us your requests on what you would like to see within the demonstration and learn on the course. We will then cater for your needs and answer them during the session. This is designed to be an introduction into how to start a room by room survey using the Heat Engineer app, then sending this survey to the online dashboard. We will then go through the different steps to complete this heat loss report. Optional pages will also be worked through and shown. Examples of how to select the flow temperature and the heat source (heat pumps and boilers) will be presented once the heat loss result is completed.

For new users and the curious. Hello, For new users and the curious. IMPORTANT: Firstly, once you are signed up, send us your requests on what you would like to see within the demonstration and learn on the course. We will then cater for your needs and answer them during the session. This is designed to be an introduction into how to start a room by room survey using the Heat Engineer app, then sending this survey to the online dashboard. We will then go through the different steps to complete this heat loss report. Optional pages will also be worked through and shown. Examples of how to select the flow temperature and the heat source (heat pumps and boilers) will be presented once the heat loss result is completed.

For new users and the curious. Hello, For new users and the curious. IMPORTANT: Firstly, once you are signed up, send us your requests on what you would like to see within the demonstration and learn on the course. We will then cater for your needs and answer them during the session. This is designed to be an introduction into how to start a room by room survey using the Heat Engineer app, then sending this survey to the online dashboard. We will then go through the different steps to complete this heat loss report. Optional pages will also be worked through and shown. Examples of how to select the flow temperature and the heat source (heat pumps and boilers) will be presented once the heat loss result is completed.

For new users and the curious. Hello, For new users and the curious. IMPORTANT: Firstly, once you are signed up, send us your requests on what you would like to see within the demonstration and learn on the course. We will then cater for your needs and answer them during the session. This is designed to be an introduction into how to start a room by room survey using the Heat Engineer app, then sending this survey to the online dashboard. We will then go through the different steps to complete this heat loss report. Optional pages will also be worked through and shown. Examples of how to select the flow temperature and the heat source (heat pumps and boilers) will be presented once the heat loss result is completed.

For new users and the curious. Hello, For new users and the curious. IMPORTANT: Firstly, once you are signed up, send us your requests on what you would like to see within the demonstration and learn on the course. We will then cater for your needs and answer them during the session. This is designed to be an introduction into how to start a room by room survey using the Heat Engineer app, then sending this survey to the online dashboard. We will then go through the different steps to complete this heat loss report. Optional pages will also be worked through and shown. Examples of how to select the flow temperature and the heat source (heat pumps and boilers) will be presented once the heat loss result is completed.

Find ease in your posture and your natural balance on this 6 week online Yoga course with Pippa Graham. This is an experiential course that will bring awareness to the key postural structures in your body and integrate a new understanding of alignment and sensation.

​Learn how to make your very own candles with essential oils, fragrances & colour dyes, using 100% pure eco-soywax. You will learn about the different types of wax, oils, wicks and the methods to making beautiful candles.

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.