1 The Purpose of Data Science
Purpose of Data Science quiz
1 attempt allowed
2 Translating Questions to Data Science Questions
Translating Questions quiz
1 attempt allowed
3 Do I Have The Data I Need?
Do I Have the Data quiz
1 attempt allowed
4 Descriptive Analysis
Descriptive Analysis quiz
1 attempt allowed
5 Exploratory Analysis
Exploratory Analysis quiz
1 attempt allowed
6 Inference: Overview
Inferential Analysis quiz
1 attempt allowed
7 Inference: Linear Regression
Linear Regression quiz
1 attempt allowed
8 Inference: Multiple Regression
Multiple Regression quiz
1 attempt allowed
9 Inference: Examples
Inference: Examples quiz
1 attempt allowed
10 Inference: Practice
Inference: Practice quiz
1 attempt allowed
11 Prediction and Machine Learning
Prediction & Machine Learning quiz
1 attempt allowed
12 Data Analysis Workflow
Data Analysis Workflow quiz
1 attempt allowed
13 Data Analysis Pipelines
Data Analysis Pipelines quiz
1 attempt allowed
14 Final Project
Final Project
16 References
About this Course
About the Authors
Retired
This course is no longer available for purchase.
Data Analysis
Data Analysis
266Readers
About
About the Course
Description
Data science is one of the most exciting and fastest growing careers in the world. The goal of this series is to help people with no background and limited resources transition into data science. It would be helpful to have already taken the previous courses Organizing Data Projects, Introduction to R, Version Control, Data Tidying and Getting Data. We guide you through the rest!
Learning objectives
After taking this course you will be able to:
- Translate a general question into a data science question
- Identify the type of data science question you are answering
- Use data visualization and linear models to answer descriptive, exploratory, inferential and predictive questions
- Implement your answers in code.
Things you need to do this course
This course is designed for people with no background with Chromebooks and no background in data science. So it is a great introduction for high-school students or people looking for a career change into the tech industry. The only requirements are:
- A computer with a web browser and an internet connection.
- The ability to type and follow instructions.
- The accounts you have set up in previous courses.
How you will be graded
The course has a series of short quizzes, one for each chapter. You will get two attempts at each quiz and your best score for each quiz will count toward your final score. If you receive more than 70% of the points across all quizzes you will pass. If you receive more than 90% of the points across all quizzes you will pass with honors. You get two attempts at the class with each class purchase.
How to report an error
If you find a bug, typo, or issue in the material, feel free to contact us using this form.
Instructors
About the Instructors
Jeffrey Leek
Jeff is Chief Data Officer, Vice President, and J Orin Edson Foundation Chair of Biostatistics at the Fred Hutchinson Cancer Center. Previously, he was a professor of Biostatistics and Oncology at the Johns Hopkins Bloomberg School of Public Health and co-director of the Johns Hopkins Data Science Lab. His group develops statistical methods, software, data resources, and data analyses that help people make sense of massive-scale genomic and biomedical data. As the co-director of the Johns Hopkins Data Science Lab he helped to develop massive online open programs that have enrolled more than 8 million individuals and partnered with community-based non-profits to use data science education for economic and public health development. He is a Fellow of the American Statistical Association and a recipient of the Mortimer Spiegelman Award and Committee of Presidents of Statistical Societies Presidential Award.
Episode 19
An Interview with Jeffrey Leek
Shannon Ellis
Shannon Ellis is an Associate Teaching Professor in the Cognitive Science Department at UC San Diego.
Aboozar Hadavand
Aboozar Hadavand is a postdoctoral fellow at Johns Hopkins Bloomberg School of Public Health. His current research involves analyzing MOOC data. He has previously taught at Barnard College (Columbia University), Brooklyn College, and Yeshiva University.
Davon Person
Material
Course Material
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