
Важная информация
Резюме
The capstone project class will allow students to create a usable/public data product that can be used to show your skills to potential employers. Projects will be drawn from real-world problems and will be conducted with industry, government, and academic partners.
Программа
- Week 1 - Overview, Understanding the Problem, and Getting the Data
This week, we introduce the project so you can get a clear grip on the problem at hand and begin working with the dataset. - Week 2 - Exploratory Data Analysis and Modeling
This week, we move on to the next tasks, exploratory data analysis and modeling. You'll also submit your milestone report and review submissions from your classmates. - Week 3 - Prediction Model
This week, you'll build and evaluate your prediction model. The goal is to make your model efficient and accurate. - Week 4 - Creative Exploration
This week's goal is to improve the predictive accuracy while reducing computational runtime and model complexity. - Week 5 - Data Product
This week, you'll work on developing the first component of your final project, your data product. - Week 6 - Slide Deck
This week, you'll work on developing the second component of your final project, a slide deck to accompany your data product. - Week 7 - Final Project Submission and Evaluation
This week, you'll submit your final project and review the work of your classmates.
Пользователи
Jeff Leek, PhD
Associate Professor, Biostatistics
Bloomberg School of Public Health
Roger D. Peng, PhD
Associate Professor, Biostatistics
Bloomberg School of Public Health
Brian Caffo, PhD
Professor, Biostatistics
Bloomberg School of Public Health
Разработчик

Платформа

Coursera - это цифровая компания, предлагающая массовые открытые онлайн-курсы, основанные учителями компьютеров Эндрю Нгом и Стэнфордским университетом Дафни Коллер, расположенные в Маунтин-Вью, штат Калифорния.
Coursera работает с ведущими университетами и организациями, чтобы сделать некоторые из своих курсов доступными в Интернете, и предлагает курсы по многим предметам, включая: физику, инженерию, гуманитарные науки, медицину, биологию, социальные науки, математику, бизнес, информатику, цифровой маркетинг, науку о данных и другие предметы.