Introduction to AI for Trainers and Assessors
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Duration 1 Days 6 CPD hours This course is intended for This course is designed for data scientists with experience of Python who need to learn how to apply their data science and machine learning skills on Azure Databricks. Overview After completing this course, you will be able to: Provision an Azure Databricks workspace and cluster Use Azure Databricks to train a machine learning model Use MLflow to track experiments and manage machine learning models Integrate Azure Databricks with Azure Machine Learning Azure Databricks is a cloud-scale platform for data analytics and machine learning. In this course, students will learn how to use Azure Databricks to explore, prepare, and model data; and integrate Databricks machine learning processes with Azure Machine Learning. Introduction to Azure Databricks Getting Started with Azure Databricks Working with Data in Azure Databricks Training and Evaluating Machine Learning Models Preparing Data for Machine Learning Training a Machine Learning Model Managing Experiments and Models Using MLflow to Track Experiments Managing Models Managing Experiments and Models Using MLflow to Track Experiments Managing Models Integrating Azure Databricks and Azure Machine Learning Tracking Experiments with Azure Machine Learning Deploying Models
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Machine learning is a vital aspect of data science, and it is the fundamental building block of artificial intelligence. This course is designed to help you master the basics of machine learning by taking you through ten comprehensive modules. Learning outcomes: Understand the basic principles of machine learning and its significance in today's world. Learn how to use Minitab for data analysis and data cleaning. Understand how regression trees and classification trees work and how to apply them. Understand binary logistic regression and its applications. Understand data modelling and how to use different predictors. Learn how to evaluate and improve the performance of machine learning models. The Machine Learning Basics course is designed to help individuals develop a fundamental understanding of machine learning. In this course, you will learn about the basics of machine learning, including regression, predictors, data cleaning, and data models. Additionally, you will learn how to use Minitab for data analysis and how to apply binary logistic regression, regression trees, and classification trees. The course includes ten comprehensive modules that will help you develop the skills you need to become a machine learning expert. This course is for anyone who wants to learn the basics of machine learning, including students, data analysts, and business professionals. By the end of the course, you will have a deep understanding of machine learning principles, including how to apply machine learning algorithms to solve real-world problems. Certification Upon completion of the course, learners can obtain a certificate as proof of their achievement. You can receive a £4.99 PDF Certificate sent via email, a £9.99 Printed Hardcopy Certificate for delivery in the UK, or a £19.99 Printed Hardcopy Certificate for international delivery. Each option depends on individual preferences and locations. CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Students who want to learn about machine learning. Data analysts who want to enhance their skills. Business professionals who want to understand machine learning. Anyone who wants to develop a fundamental understanding of machine learning. Career path Career paths related to this industry are: Data analyst: £20,000 - £50,000 per year Machine learning engineer: £30,000 - £90,000 per year Data scientist: £35,000 - £80,000 per year Business intelligence analyst: £25,000 - £55,000 per year Artificial intelligence (AI) specialist: £45,000 - £100,000 per year Software engineer: £25,000 - £70,000 per year