This capstone project course will give you a taste of what data scientists go through in real life when working with data. You will learn about location data and different location data providers, such as Foursquare. You will learn how to make RESTful API calls to the Foursquare API to retrieve data about venues in different neighborhoods around the world. You will also learn how to be creative in situations where data are not readily available by scraping web data and parsing HTML code. You will utilize Python and its pandas library to manipulate data, which will help you refine your skills for exploring and analyzing data. Finally, you will be required to use the Folium library to great maps of geospatial data and to communicate your results and findings. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge upon successful completion of the course. LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate.
от партнера
- Data Analysts
- Data Scientists
- Auditors
- Technical Leads
- Systems Analysts
Программа курса: что вы изучите
Introduction
In this module, you will learn about the scope of this capstone course and the context of the project that you will be working on. You will learn about different location data providers and what location data is normally composed of. Finally, you will be required to submit a link to a new repository on your Github account dedicated to this course.
Foursquare API
In this module, you will learn in details about Foursquare, which is the location data provider we will be using in this course, and its API. Essentially, you will learn how to create a Foursquare developer account, and use your credentials to search for nearby venues of a specific type, explore a particular venue, and search for trending venues around a location.
Neighborhood Segmentation and Clustering
In this module, you will learn about k-means clustering, which is a form of unsupervised learning. Then you will use clustering and the Foursquare API to segment and cluster the neighborhoods in the city of New York. Furthermore, you will learn how to scrape website and parse HTML code using the Python package Beautifulsoup, and convert data into a pandas dataframe.
The Battle of Neighborhoods
In this module, you will start working on the capstone project. You will clearly define a problem and discuss the data that you will be using to solve the problem.
45%
37%
Лучшие отзывы о курсе Applied Data Science Capstone
This is a great course and lots of fun. But it is a big commitment and you need to take it seriously. To get the most out of this course you will need to spend at least 30 hours doing it.
This course is instructive and challenging at the same time. Now I do wish I know a bit more about python and pandas before I jump in this course. But in the end I managed to get through.
Преподаватели
Alex Aklson
Ph.D., Data ScientistО IBM
Часто задаваемые вопросы
Когда я получу доступ к лекциям и заданиям?
Зарегистрировавшись на сертификацию, вы получите доступ ко всем видео, тестам и заданиям по программированию (если они предусмотрены). Задания по взаимной оценке сокурсниками можно сдавать и проверять только после начала сессии. Если вы проходите курс без оплаты, некоторые задания могут быть недоступны.
Что я получу, оформив подписку на сертификацию?
Записавшись на курс, вы получите доступ ко всем курсам в сертификации, а также возможность получить сертификат о его прохождении. После успешного прохождения курса на странице ваших достижений появится электронный сертификат. Оттуда его можно распечатать или прикрепить к профилю LinkedIn. Просто ознакомиться с содержанием курса можно бесплатно.
Какие правила возврата средств?
Остались вопросы? Посетите Центр поддержки учащихся.