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Foundations of Data Science: K-Means Clustering in Python

Курс от University of London, Goldsmiths, University of London

Начальный≈ 29.1 чАнглийский

О курсе

Organisations all around the world are using data to predict behaviours and extract valuable real-world insights to inform decisions. Managing and analysing big data has become an essential part of modern finance, retail, marketing, social science, development and research, medicine and government. This MOOC, designed by an academic team from Goldsmiths, University of London, will quickly introduce you to the core concepts of Data Science to prepare you for intermediate and advanced Data Science courses. It focuses on the basic mathematics, statistics and programming skills that are necessary for typical data analysis tasks. You will consider these fundamental concepts on an example data clustering task, and you will use this example to learn basic programming skills that are necessary for mastering Data Science techniques. During the course, you will be asked to do a series of mathematical and programming exercises and a small data clustering project for a given dataset.

Навыки, которые вы освоите

Python Programming NumPy Pandas (Python Package)Descriptive Statistics Unsupervised Learning Plot (Graphics)Statistics Data Literacy Machine Learning Statistical Methods Data Visualization Data Science Data Manipulation Applied Machine Learning Data Analysis Data Processing Machine Learning Algorithms Analytics

Программа курса

5 модулей · 129 учебных материалов

01Week 1: Foundations of Data Science: K-Means Clustering in Python16 материалов

Учитесь у экспертов

Professor Matthew Yee-King

Lecturer

Dr Betty Fyn-Sydney

Lecturer in Mathematics

Dr Jamie A Ward

Lecturer in Computer Science

Dr Larisa Soldatova

Reader in Data Science

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Обучение на Coursera

≈ 29.1 ч

5 модулей

Язык: Английский

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

Foundations of Data Science: K-Means Clustering in Python

О курсе

Навыки, которые вы освоите

Программа курса

Welcome and Introduction

Week 1 Introduction

Data

Учитесь у экспертов

Professor Matthew Yee-King

Dr Betty Fyn-Sydney

Dr Jamie A Ward

Dr Larisa Soldatova

Machine Learning

Supervised vs Unsupervised Learning

Clustering with K-Means

Week 1 Outro and Assessment

Week 2 Introduction

Mean, Variance and Standard Deviation

Development Environment: Jupyter Notebooks

Computing Basic Statistics in Python

Week 2 Outro and Assessment

Week 3 Introduction

Mathematics for Multidimensional Data

Working with Multidimensional Data in Python

Week 3 Outro and Assessment

Week 4 Introduction

Using the Pandas Library to Read, Sort and Filter Data

Plotting and Labelling the Data

Interpreting the Data

Week 4 Outro and Assessment

Welcome and Introduction

Understanding Your Task

Organising Your Work on a Data Science Project

Doing the Project

Presenting the Results of Your Project

Week 5 Outro and Assessment