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.
提供方
约翰霍普金斯大学
課程信息
341,525 次近期查看
您將學到的內容有
Create a Github repository
Explain essential study design concepts
Set up R, R-Studio, Github and other useful tools
Understand the data, problems, and tools that data analysts work with
您將獲得的技能
Data ScienceGithubR ProgrammingRstudio
學習Course的學生是
- Data Analysts
- Scientists
- Biostatisticians
- Researchers
- Economists
教學大綱 - 您將從這門課程中學到什麼
週
1完成時間為 2 小時
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.
16 個視頻 （總計 51 分鐘）, 5 個閱讀材料, 1 個測驗
16 個視頻
The Data Scientist's Toolbox5分鐘
Getting Help8分鐘
Finding Answers4分鐘
R Programming Overview2分鐘
Getting Data Overview1分鐘
Exploratory Data Analysis Overview1分鐘
Reproducible Research Overview1分鐘
Statistical Inference Overview1分鐘
Regression Models Overview1分鐘
Practical Machine Learning Overview1分鐘
Building Data Products Overview1分鐘
Installing R on Windows {Roger Peng}3分鐘
Install R on a Mac {Roger Peng}2分鐘
Installing Rstudio {Roger Peng}1分鐘
Installing Outside Software on Mac (OS X Mavericks)1分鐘
5 個閱讀材料
Welcome to the Data Scientist's Toolbox10分鐘
Pre-Course Survey10分鐘
Syllabus10分鐘
Specialization Textbooks10分鐘
The Elements of Data Analytic Style10分鐘
1 個練習
Week 1 Quiz10分鐘
週
2完成時間為 1 小時
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.
9 個視頻 （總計 51 分鐘）, 1 個測驗
9 個視頻
Command Line Interface16分鐘
Introduction to Git4分鐘
Introduction to Github3分鐘
Creating a Github Repository5分鐘
Basic Git Commands5分鐘
Basic Markdown2分鐘
Installing R Packages5分鐘
Installing Rtools2分鐘
1 個練習
Week 2 Quiz10分鐘
週
3完成時間為 1 小時
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.
4 個視頻 （總計 35 分鐘）, 1 個測驗
1 個練習
Week 3 Quiz10分鐘
週
4完成時間為 2 小時
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.
1 個閱讀材料, 1 個測驗
1 個閱讀材料
Post-Course Survey10分鐘
4.5
4135 個審閱38%
完成這些課程後已開始新的職業生涯
35%
通過此課程獲得實實在在的工作福利
來自数据科学家的工具箱（中文版）的熱門評論
突出顯示
Foundational tools
(243)Introductory course
(1056)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.
This course was a good intro especially in setting all the necessary software for future courses. I suggest to read the manuals, books and other readings the profs suggest. The resources are helpful.
講師
Jeff Leek, PhD
Associate Professor, BiostatisticsBloomberg School of Public Health
Roger D. Peng, PhD
Associate Professor, BiostatisticsBloomberg School of Public Health
Brian Caffo, PhD
Professor, BiostatisticsBloomberg School of Public Health
關於 约翰霍普金斯大学
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.
常見問題
我什么时候能够访问课程视频和作业？
注册以便获得证书后，您将有权访问所有视频、测验和编程作业（如果适用）。只有在您的班次开课之后，才可以提交和审阅同学互评作业。如果您选择在不购买的情况下浏览课程，可能无法访问某些作业。
我订阅此专项课程后会得到什么？
您注册课程后，将有权访问专项课程中的所有课程，并且会在完成课程后获得证书。您的电子课程证书将添加到您的成就页中，您可以通过该页打印您的课程证书或将其添加到您的领英档案中。如果您只想阅读和查看课程内容，可以免费旁听课程。
退款政策是如何规定的？
有助学金吗？
還有其他問題嗎？請訪問 學生幫助中心。
