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Machine Learning

Master machine learning fundamentals in four hands-on courses

About This Specialization This Specialization from leading researchers at the University of Washington introduces you to the exciting, high-demand field of Machine Learning. Through a series of practical case studies, you will gain applied experience in major areas of Machine Learning including Prediction, Classification, Clustering, and Information Retrieval. You will learn to analyze large and complex datasets, create systems that adapt and improve over time, and build intelligent applications that can make predictions from data. Created by: Industry Partners: 4 courses Follow the suggested order or choose your own. Projects Designed to help you practice and apply the skills you learn. Certificates Highlight your new skills on your resume or

A Crash Course in Data Science

A Crash Course in Data Science

About this course: By now you have definitely heard about data science and big data. In this one-week class, we will provide a crash course in what these terms mean and how they play a role in successful organizations. This class is for anyone who wants to learn what all the data science action is about, including those who will eventually need to manage data scientists. The goal is to get you up to speed as quickly as possible on data science without all the fluff. We've designed this course to be as convenient as possible without sacrificing any of the essentials. This is a focused course designed to rapidly get you up to speed on the field of data science. Our goal was to make this as convenient as possible for you without sacrificing any essential content. We've left the technical information aside so that you can focus on managing your team and moving it forward. After completing this course you will know. 1. How to describe the role data science plays in various contexts 2. How statistics, machine learning, and software engineering play a role in data science 3. How to describe the structure of a data science project 4. Know the key terms and tools used by data scientists 5. How to identify a successful and an unsuccessful data science project 3. The role of a data science manager

Created by:  Johns Hopkins University

  • Jeff Leek, PhD
    Taught by:  Jeff Leek, PhD, Associate Professor, Biostatistics
    Bloomberg School of Public Health

  • Brian Caffo, PhD
    Taught by:  Brian Caffo, PhD, Professor, Biostatistics
    Bloomberg School of Public Health

  • Roger D. Peng, PhD
    Taught by:  Roger D. Peng, PhD, Associate Professor, Biostatistics
    Bloomberg School of Public Health
Basic Info
Commitment1 week of study, 4-6 hours
Language
EnglishSubtitles: Turkish, Russian
How To PassPass all graded assignments to complete the course.
User Ratings
Average User Rating 4.4See what learners said
Syllabus
WEEK 1
A Crash Course in Data Science
This one-module course constitutes the first "week" of the Executive Data Science Specialization. This is an intensive introduction to what you need to know about data science itself. You'll learn important terminology and how successful organizations use data science.
11 videos8 readings
  1. Video: About Your Instructors
  2. Reading: Specialization Textbook
  3. Reading: Grading
  4. Reading: Pre-Course Survey
  5. Video: What is Data Science?
  6. Reading: Statistics by example activities
  7. Video: Statistics by example activities
  8. Reading: Machine learning
  9. Video: Machine learning, the basics
  10. Video: Machine learning further reading
  11. Video: What is Software Engineering for Data Science?
  12. Video: The Structure of a Data Science Project
  13. Reading: The outputs of a data science experiment
  14. Video: The outputs of a data science experiment
  15. Reading: The four secrets of a successful data science experiment
  16. Video: The four secrets of a successful data science experiment
  17. Video: Data Scientist Toolbox
  18. Video: Separating Hype from Value
  19. Reading: Post-Course Survey
Graded: What is data science?
Graded: What is statistics good for?
Graded: Machine learning
Graded: Quiz: Software Engineering
Graded: Structure of a Data Science Project
Graded: The outputs of a data science experiment
Graded: Defining Success in Data Science
Graded: Data scientist toolbox
Graded: Separating hype from value
How It Works
Coursework
Coursework
Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.
Help from Your Peers
Help from Your Peers
Connect with thousands of other learners and debate ideas, discuss course material, and get help mastering concepts.
Certificates
Certificates
Earn official recognition for your work, and share your success with friends, colleagues, and employers.
Creators
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.

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