This course is part of the Executive Data Science Specialization

4.5
stars
7,718 ratings

Jeff Leek, PhD +2 more instructors

177,941 already enrolled

Offered By

Executive Data Science SpecializationJohns Hopkins University

About this Course

49,704 recent views

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


Course cover image by r2hox. Creative Commons BY-SA: https://flic.kr/p/gdMuhT

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Course 1 of 5 in the

Executive Data Science Specialization

Approx. 7 hours to complete

English

Subtitles: Chinese (Traditional), Arabic, French, Portuguese (European), Italian, Vietnamese, German, Urdu, Russian, Turkish, English, Spanish, Hindi

What you will learn

Describe Data Science’s role in various contexts

Understand how Statistics and Machine Learning affect Data Science

Use the key terms used by data scientist

Predict whether a Data Science project will be successful

Skills you will gain

Data ScienceData AnalysisMachine LearningProject

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Course 1 of 5 in the

Executive Data Science Specialization

Approx. 7 hours to complete

English

Subtitles: Chinese (Traditional), Arabic, French, Portuguese (European), Italian, Vietnamese, German, Urdu, Russian, Turkish, English, Spanish, Hindi

Instructors

Instructor rating

4.55/5 (722 Ratings)

Offered by

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.

Syllabus - What you will learn from this course

Content Rating93%(17,295 ratings)

Week

Week 1

7 hours to complete

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.

7 hours to complete

11 videos (Total 78 min), 8 readings, 9 quizzes

11 videos

About Your Instructors1m

What is Data Science?5m

Statistics by example activities11m

Machine learning, the basics13m

Machine learning further reading3m

What is Software Engineering for Data Science?6m

The Structure of a Data Science Project6m

The outputs of a data science experiment6m

The four secrets of a successful data science experiment14m

Data Scientist Toolbox5m

Separating Hype from Value3m

8 readings

Specialization Textbook10m

Grading10m

Pre-Course Survey10m

Statistics by example activities10m

Machine learning10m

The outputs of a data science experiment10m

The four secrets of a successful data science experiment10m

Post-Course Survey10m

9 practice exercises

What is data science?30m

What is statistics good for?30m

Machine learning30m

Quiz: Software Engineering30m

Structure of a Data Science Project30m

The outputs of a data science experiment30m

Defining Success in Data Science30m

Data scientist toolbox30m

Separating hype from value30m

Reviews

4.5

1460 reviews

5 stars
62.24%
4 stars
29.13%
3 stars
6.58%
2 stars
1.25%
1 star
0.78%

HIGHLIGHTS

"Basic course" in 76 reviews

"Well taught" in 48 reviews

TOP REVIEWS FROM A CRASH COURSE IN DATA SCIENCE

by NGJan 8, 2018

Questions could have been more difficult. Plus, I'm frustrated that I was taken into a 25-question survey ranking me with other data scientists, but when I clicked out of it I wasn't able to get back.

by SKJul 18, 2017

This course introduced me to the concepts of Data Science and the key words mainly. Some lecturers spoke very fast, and I had listen to them two or three times to keep up with their pace of speaking.

by JXJun 20, 2016

fairly general concepts of data science, but may be quite helpful l for people totally new to the field of data (e.g. not having any idea), or as material to review the big picture of data science

by RADec 29, 2019

Enjoyed the pace at which the course moved. Teachers were qualified and relevant. Video Production quality could be better, some of the presentation graph were illegible - thus the lack of 1 star.

View all reviews

About the Executive Data Science Specialization

Assemble the right team, ask the right questions, and avoid the mistakes that derail data science projects.

In four intensive courses, you will learn what you need to know to begin assembling and leading a data science enterprise, even if you have never worked in data science before. You’ll get a crash course in data science so that you’ll be conversant in the field and understand your role as a leader. You’ll also learn how to recruit, assemble, evaluate, and develop a team with complementary skill sets and roles. You’ll learn the structure of the data science pipeline, the goals of each stage, and how to keep your team on target throughout. Finally, you’ll learn some down-to-earth practical skills that will help you overcome the common challenges that frequently derail data science projects.

Frequently Asked Questions

When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
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.
Is financial aid available?
Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.

More questions? Visit the Learner Help Center.

A Crash Course in Data Science