486 Machine Learning (ML) courses

Learn the smart way of using machine learning in Flutter to build smart android and iOS applications with

Begin your machine learning journey by learning all about linear regression, logistic regression, and cluster analysis

Implement machine learning-based clustering and classification in Python for pattern recognition and data analysis

Python for Data Science and Machine Learning Bootcamp online course is suitable for anyone interested in learning Python for data science and machine learning. It is especially ideal for aspiring data scientists and professionals seeking to enhance their data analysis skills.

This course will be mainly focusing on machine learning algorithms. Throughout this course, we are preparing our machine to make it ready for a prediction test.

Welcome to the Bootcamp course. You will obtain a firm understanding of machine learning with this course. By doing so, you will be able to develop machine learning solutions for various challenges you might encounter and be prepared to start using machine learning at work or in technical interviews.

Duration 3 Days 18 CPD hours This course is intended for The EXIN BCS Artificial Intelligence Foundation certification is focused on individuals with an interest in, (or need to implement) AI in an organization, especially those working in areas such as science, engineering, knowledge engineering, finance, education or IT services. Overview You will be able to Describe how Artificial (AI) is Part of 'Universal Design', and 'The Fourth Industrial Revolution' Demonstrate Understanding of the Artificial Intelligence (AI) Intelligen Agent Description Explain the Benefits of Artificial Intelligence (AI) Describe how we Learn from Data - Functionality, Software and Hardware Demonstrate an Understanding that Artificial Intelligence (AI) (in Particular, Machine Learning (ML)) will Drive Humans and Machines to Work Together Describe a ''Learning from Experience'' Agile Approach to Projects Candidates should be able to demonstrate a knowledge and understanding in the application of ethical and sustainable Artificial Intelligence (AI):- Human-centric Ethical and Sustainable Human and Artificial Intelligence (AI) ETHICAL AND SUSTAINABLE HUMAN AND ARTIFICIAL INTELLIGENCE (AI) * Recall the General Definition of Human and Artificial Intelligence (AI) * Describe what are Ethics and Trustworthy Artificial Intelligence (AI) * Describe the Three Fundamental Areas of Sustainability and the United Nationïs Seventeen Sustainability Goals * Describe how Artificial Intelligence (AI) is Part of 'Universal Design', and 'The Fourth Industrial Revolution' * Understand that Machine Learning (ML) is a Significant Contribution to the Growth of Artificial Intelligence (AI) ARTIFICIAL INTELLIGENCE (AI) AND ROBOTICS * Demonstrate Understanding of the Artificial Intelligence (AI) Intelligent Agent Description * Describe what a Robot is * Describe what an intelligent Robot is APPLYING THE BENEFITS OF ARTIFICIAL INTELLIGENCE (AI) ? CHALLENGES AND RISKS * Describe how Sustainability Relates to Human-Centric Ethical Artificial Intelligence (AI) and how our Values will Drive our use of Artificial Intelligence (AI) and will Change Humans, Society and Organizations * Explain the Benefits of Artifical Intelligence (AI) * Describe the Challenges of Artificial Intelligence (AI) Projects * Demonstrate Understanding of the Risks of Artificial Intelligence (AI) Projects * List Opportunities for Artificial Intelligence (AI) * Identify a Typical Funding Source for Artificial Intelligence (AI) Projects and Relate to the NASA Technology Readiness Levels (TRLs) STARTING ARTIFICIAL INTELLIGENCE (AI): HOW TO BUILD A MACHINE LEARNING (ML) TOOLBOX ? THEORY AND PRACTICE * Describe how we Learn from Data - Functionality, Software and Hardware * Recall which Rypical, Narrow Artificial Intelligence (AI) Capability is Useful in Machine Learning (ML9 and Artificial Intelligence (AI) AgentsïFunctionality THE MANAGEMENT, ROLES AND RESPONSIBILITIES OF HUMANS AND MACHINES * Demonstrate an Understanding that Artificial Intelligence (AI) (in Particular, Machine Learning (ML)) will Drive Humans and Machines to Work Together * List Future Directions of Humans and Machines Working Together * Describe a ''Learning from Experience'' Agile Approach to Projects

In this course, you will learn how to perform data cleaning and data preparation with KNIME and without coding. You should be familiar with KNIME as no basics are covered in this course. Basic knowledge of machine learning is certainly helpful for the later lectures in this course.

In this course, you will learn Python fundamentals, and the concepts of the amazing pandas data science library needed to pre-process and prepare the data for machine learning algorithms.

Thinking about learning Big Data? The BCS Foundation Award in Big Data teaches learners to understand how to manage Big Data and its use with Machine Learning.