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Machine Learning for All · LearnSpace
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Machine Learning for All

Курс от University of London
Начальный≈ 20.6 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

Machine Learning, often called Artificial Intelligence or AI, is one of the most exciting areas of technology at the moment. We see daily news stories that herald new breakthroughs in facial recognition technology, self driving cars or computers that can have a conversation just like a real person. Machine Learning technology is set to revolutionise almost any area of human life and work, and so will affect all our lives, and so you are likely to want to find out more about it. Machine Learning has a reputation for being one of the most complex areas of computer science, requiring advanced mathematics and engineering skills to understand it. While it is true that working as a Machine Learning engineer does involve a lot of mathematics and programming, we believe that anyone can understand the basic concepts of Machine Learning, and given the importance of this technology, everyone should. The big AI breakthroughs sound like science fiction, but they come down to a simple idea: the use of data to train statistical algorithms. In this course you will learn to understand the basic idea of machine learning, even if you don't have any background in math or programming. Not only that, you will get hands on and use user friendly tools developed at Goldsmiths, University of London to actually do a machine learning project: training a computer to recognise images. This course is for a lot of different people. It could be a good first step into a technical career in Machine Learning, after all it is always better to start with the high level concepts before the technical details, but it is also great if your role is non-technical. You might be a manager or other non-technical role in a company that is considering using Machine Learning. You really need to understand this technology, and this course is a great place to get that understanding. Or you might just be following the news reports about AI and interested in finding out more about the hottest new technology of the moment. Whoever you are, we are looking forward to guiding you through you first machine learning project. NB this course is designed to introduce you to Machine Learning without needing any programming. That means that we don't cover the programming based machine learning tools like python and TensorFlow.

Навыки, которые вы освоите

Model TrainingModel EvaluationMachine LearningFeature EngineeringArtificial Intelligence and Machine Learning (AI/ML)Machine Learning AlgorithmsData CollectionApplied Machine LearningAI literacyStatistical Machine LearningArtificial IntelligenceData LiteracyResponsible AI

Программа курса

4 модулей · 58 учебных материалов

01Machine learning18 материалов

Lesson 1.0 Introduction

Course structure and navigationЧтениеLearn effectively on this courseЧтениеIntroduction: Computers that seeВидеоComputers that seeЗадание

Учитесь у экспертов

Prof Marco Gillies

Professor

Machine Learning for All
В каталоге вашей программы

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Новые знания — в удобное для вас время.

Начать на Coursera

Обучение откроется на Coursera
в новой вкладке

Обучение на Coursera

≈ 20.6 ч

4 модулей

Язык: Английский

Субтитры: Арабский, Французский, Бенгальский, Узбекский, Украинский, Китайский (Китай), Греческий, Итальянский, Бразильский португальский, Вьетнамский, Нидерландский, Корейский, Немецкий, Пушту, Урду, Русский, Тайский, Индонезийский, Шведский, Турецкий, Азербайджанский, Испанский, Дари, Хинди, Японский, Казахский, Венгерский, Польский

Часть программы вашего университета
What is AI?Обсуждение
Welcome to Machine Learning for AllЧтение

Lesson 1.1 Artificial intelligence

Artificial intelligenceВидеоWhat makes AI hard?ОбсуждениеPractice quiz – Alpha GoЗадание

Lesson 1.2 Machine learning

Machine learningВидеоMachine learning algorithmsВидеоMachine learning exerciseЧтениеMachine learningPLUGINHow did you find machine learning?ОбсуждениеInterview with Machine learning expertsВидео

Lesson 1.3 Summary

Machine learning summative quizЗаданиеA machine learning applicationОбсуждениеWeek 1 summaryВидео
02Data Features12 материалов

Lesson 2.1 Data Representation

The bitВидеоData representation in bitsОбсуждениеBytes and numbersВидеоOther types of dataВидео

Lesson 2.2 Data features

Introduction to Data FeaturesВидеоData featuresВидеоData featuresОбсуждениеPractice quiz – Bag of wordsЗаданиеNeural networksВидеоInterview: Data FeaturesВидео

Lesson 2.3 Summary

What have you learned?ОбсуждениеData features summative quizЗадание
03Machine Learning in Practice15 материалов

Lesson 3.1 Testing

Introduction to Machine Learning in practiceВидеоTestingВидеоTrying different datasetsЧтениеTrying different datasetsPLUGINEvaluating the four datasetsЧтениеHow does machine learning go wrong?ОбсуждениеProblems with machine learningВидео

Lesson 3.2 Societal Impact of Machine Learning

Applications of machine learningВидеоApplications of machine learningОбсуждениеDangers of machine learningВидеоDangers of machine learningОбсуждениеInterview: Benefits and dangers of machine learningВидеоFurther ReadingЧтение

Lesson 3.3: Summary

What have you learned?ОбсуждениеMachine learning in practice summative quizЗадание
04Your Machine Learning Project13 материалов

Lesson 4.0 Introduction

Introduction: Collecting your own datasetВидеоYour machine learning projectОбсуждение

Lesson 4.1 Your machine learning project

Preparing for your machine learning projectЗаданиеCollecting a datasetВидеоAdvice on data collectionОбсуждениеInterview: Advice for your first Machine Learning ProjectВидеоCollecting a datasetЧтениеTraining a model using your datasetPLUGINReflecting on your projectЧтениеEvaluating your machine learning projectЗадание

Lesson 4.2 Summary

What have you learned?ОбсуждениеSummaryВидеоWhat's next?Чтение