Об этом курсе
4.5
15,933 ratings
3,308 reviews
In this course you will get an introduction to the main tools and ideas in the data scientist's toolbox. The course gives an overview of the data, questions, and tools that data analysts and data scientists work with. There are two components to this course. The first is a conceptual introduction to the ideas behind turning data into actionable knowledge. The second is a practical introduction to the tools that will be used in the program like version control, markdown, git, GitHub, R, and RStudio....
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Предполагаемая нагрузка: 1-4 hours/week

Прибл. 8 ч. на завершение
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English

Субтитры: English, French, Chinese (Simplified), Greek, Italian, Portuguese (Brazilian), Vietnamese, Russian, Turkish, Hebrew

Чему вы научитесь

  • Check
    Create a Github repository
  • Check
    Explain essential study design concepts
  • Check
    Set up R, R-Studio, Github and other useful tools
  • Check
    Understand the data, problems, and tools that data analysts work with

Приобретаемые навыки

Data ScienceGithubR ProgrammingRstudio
Globe

Только онлайн-курсы

Начните сейчас и учитесь по собственному графику.
Calendar

Гибкие сроки

Назначьте сроки сдачи в соответствии со своим графиком.
Clock

Предполагаемая нагрузка: 1-4 hours/week

Прибл. 8 ч. на завершение
Comment Dots

English

Субтитры: English, French, Chinese (Simplified), Greek, Italian, Portuguese (Brazilian), Vietnamese, Russian, Turkish, Hebrew

Программа курса: что вы изучите

1

Раздел
Clock
2 ч. на завершение

Week 1

During Week 1, you'll learn about the goals and objectives of the Data Science Specialization and each of its components. You'll also get an overview of the field as well as instructions on how to install R....
Reading
16 видео (всего 51 мин.), 5 материалов для самостоятельного изучения, 1 тест
Video16 видео
The Data Scientist's Toolbox5мин
Getting Help8мин
Finding Answers4мин
R Programming Overview2мин
Getting Data Overview1мин
Exploratory Data Analysis Overview1мин
Reproducible Research Overview1мин
Statistical Inference Overview1мин
Regression Models Overview1мин
Practical Machine Learning Overview1мин
Building Data Products Overview1мин
Installing R on Windows {Roger Peng}3мин
Install R on a Mac {Roger Peng}2мин
Installing Rstudio {Roger Peng}1мин
Installing Outside Software on Mac (OS X Mavericks)1мин
Reading5 материала для самостоятельного изучения
Welcome to the Data Scientist's Toolbox10мин
Pre-Course Survey10мин
Syllabus10мин
Specialization Textbooks10мин
The Elements of Data Analytic Style10мин
Quiz1 практическое упражнение
Week 1 Quiz10мин

2

Раздел
Clock
1 ч. на завершение

Week 2: Installing the Toolbox

This is the most lecture-intensive week of the course. The primary goal is to get you set up with R, Rstudio, Github, and the other tools we will use throughout the Data Science Specialization and your ongoing work as a data scientist. ...
Reading
9 видео (всего 51 мин.), 1 тест
Video9 видео
Command Line Interface16мин
Introduction to Git4мин
Introduction to Github3мин
Creating a Github Repository5мин
Basic Git Commands5мин
Basic Markdown2мин
Installing R Packages5мин
Installing Rtools2мин
Quiz1 практическое упражнение
Week 2 Quiz10мин

3

Раздел
Clock
1 ч. на завершение

Week 3: Conceptual Issues

The Week 3 lectures focus on conceptual issues behind study design and turning data into knowledge. If you have trouble or want to explore issues in more depth, please seek out answers on the forums. They are a great resource! If you happen to be a superstar who already gets it, please take the time to help your classmates by answering their questions as well. This is one of the best ways to practice using and explaining your skills to others. These are two of the key characteristics of excellent data scientists. ...
Reading
4 видео (всего 35 мин.), 1 тест
Video4 видео
What is Data?5мин
What About Big Data?4мин
Experimental Design15мин
Quiz1 практическое упражнение
Week 3 Quiz10мин

4

Раздел
Clock
2 ч. на завершение

Week 4: Course Project Submission & Evaluation

In Week 4, we'll focus on the Course Project. This is your opportunity to install the tools and set up the accounts that you'll need for the rest of the specialization and for work in data science....
Reading
1 материал для самостоятельного изучения, 1 тест
Reading1 материал для самостоятельного изучения
Post-Course Survey10мин
4.5
Direction Signs

36%

начал новую карьеру, пройдя эти курсы
Briefcase

83%

получил значимые преимущества в карьере благодаря этому курсу

Лучшие рецензии

Основные моменты
Introductory course
(1056)
Foundational tools
(243)
автор: LRSep 8th 2017

It was really insightful, coming from knowing almost nothing about statistics or experimental design, it was easy to understand while not feeling shallow. Just the right amount of information density.

автор: AMJul 22nd 2017

Great Primer for what Data Science is about. It also provides the infrastructure of tools needed. This was what I was after, a way to provide other data scientist hardware and infrastructure support.

Преподавателя

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

О Johns Hopkins University

The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world....

О специализации ''Data Science'

Ask the right questions, manipulate data sets, and create visualizations to communicate results. This Specialization covers the concepts and tools you'll need throughout the entire data science pipeline, from asking the right kinds of questions to making inferences and publishing results. In the final Capstone Project, you’ll apply the skills learned by building a data product using real-world data. At completion, students will have a portfolio demonstrating their mastery of the material....
Data Science

Часто задаваемые вопросы

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

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