A Crash Course in Data Science
Get a Reminder
Rating | 4.3★ based on 1,003 ratings |
---|---|
Length | 2 weeks |
Effort | 1 week of study, 4-6 hours |
Starts | Jul 3 (39 weeks ago) |
Cost | $49 |
From | Johns Hopkins University via Coursera |
Instructors | Roger D. Peng, PhD, Jeff Leek, PhD, Brian Caffo, PhD |
Download Videos | On all desktop and mobile devices |
Language | English |
Subjects | Data Science Business |
Tags | Data Science Data Analysis Business Leadership And Management |
Get a Reminder
Similar Courses
What people are saying
machine learning
As this is the first class of Executive data science specialization, I give it 4 stars because I believe (or should I say "hope") that someone who is planning to be executive data science manager should know what is statistics or machine learning, or what is the aim of exploratory data analysis.
The course serves as a very nice Q&A for anyone interested in machine learning.
A good course to start on your journey to understand DS and Machine LearningI am familar with most of terminology through my experience.
I liked the fact that it fused traditional analysis techniques with modern tools, infrastructures and approaches without taking sides (ie inferential statistics and hypothesis testing versus machine learning and deep learning algorithms).
This is a beautifully designed crash course on Data Science and gives you insight into Machine Learning and how it can be used effectively.
Great to do if, you want to dive into data science or machine learning.
I alreday feel that i h Interesting course but structure was a bit odd I thought, it was not clear why so much time was devoted at the outset to the difference between Machine Learning and data science.
I think the statistics vs Machine Learning wasn't totally relevant.
For example, they explain clearly the difference between statistical analysis and machine learning, although, a more detailed examples of when you only can use statistical analysis and when you only can use machine learning is missed.
If you're looking for an introduction to data science and machine learning which doesn't get your feet too wet this course is ideal.
G I really liked the content , the difference between machine learning and statistical modelling was nicely explained.I also like the topic hype from value and it was well explained.
Why machine learning is used or what problem it solved.
It doesn't really answer questions of what are data science, big data, machine learning, how they interact and how to use them.
Very basic course, gives a bird view of the Data Science Executive Summary: Do not spend time on this course if you have minimal common sense and have read at least one article on Data Science.I finished the 11 week course "Machine Learning - Stanford University - by Andrew Ng" 2 months ago, which was such a great course!
Read more
easy to understand
it was informative :) easy to understand and relate with.
Very easy to understand and insightful!
Very good introduction course course is easy to understand.
Easy to understand and I really got general idea of data science.
Easy to understand.
Great lecturers who make it easy to understand.
The course lays out the basics of Data Science in a very easy to understand manner for someone who is a beginner and gives an overview from where you can start scouring for more information either through the further courses or outside of them.
Good overview of Data Science - peaks interest but doesn't go into depth of any subjects The crash course was easy to understand.
very small and easy to understand and worth to take Fantastic overview of Data Science avaible to all public This course was truly a crash course with less crashing and more succeeding on the parts of the professors.
The technical terms are easy to understand and presented in such a way that it provides good understanding of Data Science and it is applied in various industries to for business benefit Boring and useless course..... Great job!
Very well structured and examples very straight-forward and easy to understand.
Easy to understand and shed light on how to making progress on more learnings.
Very informative and easy to understand.
Clear with easy to understand concepts.
Read more
aspects of data science
The course defines data science and then discusses different aspects of data science like statistics, machine learning and the structure, output and success metrics for data science projects.
It is a very good course even if you are familiar with some aspects of data science work.
This was really a crash course in various aspects of data science, with words being thrown around and defined for a lay person like myself.
It is really quite and easy course into various aspects of data science.
Very crash course that gives you a taste about the different aspects of data science and makes you want to dive in the specialization program right away!
great introduction to field, but there is lack of examples of bad usage data science methods and tools Great for an overview of the different aspects of data science.
A great way to better understand the fundamental aspects of data science.
Read more
crash course in data
A Crash Course in Data Science is a succinct, one-week overview of the field of data science produced by the same team from John Hopkins University that produced Coursera’s data science specialization.
It kept me busy for about 20 days (at about 4-6 hours per day) and I learned so much!This course "A Crash Course in Data Science - Johns Hopkins University" , Part of a 5-course series, the Executive Data Science Specialization, provided just some superficial obvious information, took me only 3 hours to complete and even this time I would could wasted time.Finally coursera now starts to make courses smaller and smaller and them adding multiple of them up to "Specialization", so that at the end you have to pay much more to get a certain amount of information and course time.
Too shallow in coverage Great and interesting material, worth investing the time Helps learn about Data Science objectives, process, structure, toolbox and hype in short with real-life examples Well it got the objective right which is only a crash course in data science for beginners, but I think the team could make a more engaging and practical videos with more of real life cases More of a lean-back course.
i was quite dissapointed from the 2nd half of the module "A Crash Course in Data Science".
It is exactly what you can expect from a "A Crash Course in Data Science". "
great refresher and takes aout the number of hours A great course for people who just s definitely useful for someone like me who has no prior background in this field A Crash Course in Data Science is a succinct, one-week overview of the field of data science produced by the same team from John Hopkins University that produced Coursera’s data science specialization.
A Crash Course in Data Science is good for what it is: a brief overview of a field taught at a high level so that anyone can follow along.
A Crash Course in Data Science is a well-made primer on the data science field, but its brevity may leave paying students wanting.
Read more
high level overview
Good high level overview -- lame that the quizzes are locked, there is essentially nothing to give you a sense of accomplishing anything unless you pay.
A quick and easy high level overview of data science.
This course is a very high level overview of Data Science and among other things reviews differences between machine learning and statistics and current disputes on the topic.
Aldo Really good quick and dirty high level overview of how to structure and talk about data science projects.
High level overview - not technical at all.
Excellent high level overview of data science The material is of a good level, it is a good first introduction to the field.
Great intro Provided a good, very high level overview.
it was a great learning experience,the lectures were good and excellently designed Really wonderful high level overview- quite helpful for me.
Read more
insight into
gives insight into the core concepts of data science but as is a crash course it does not get into the statistical or technical aspect of data science Excellent Course.With in Short time i have understood what is Data science and its core functionalities.Excellent Teaching faculty.
I also missed some insight into the step from the question to the search algorithm.
A good course for people, who want to get some insight into Data Science Good overview of Data Science but lacking a bit of meat.
Very Good course for understanding the Data science elements The first week gave me a good insight into the data science process.
Gives you good and short insight into what data science is all about.
This course have given me a an insight into what is this big name Data Science is all about.
Doesn't give much insight into data science.
Read more
starting point for
Very very good starting point for learning all about data sciences Crash course is the correct description; vast amount of material covered in a few segments.
A good starting point for those who feel that they have an interest in Data science.
A good starting point for other Data Analytics/Science coursework.
Great starting point for any experienced professional with no data science background to understand this growing in-demand field, its purpose, the various components that comprise data science, in addition to overall objectives and outcomes of data science.
Read more
john hopkins
Disappointed that this comes from John Hopkins.
Top scores for coursera.org &John Hopkins ... Too basic.
Good crash course, presents relevant concepts quickly Very basic level, nice talks though Thank you all professors of John Hopkins, for excellent explanations and relevant examples to help improve learning.
The content quality is a definite step up from the original John Hopkins data science track.
Read more
johns hopkins
Thanks to all instructors and Johns Hopkins, as well as Coursera, for offering this!
Thanks to the instructors and Johns Hopkins University.
Gives an excellent overview of key concepts in Data Science and whets your appetite for more This course is the 2nd certificate course I've completed through Johns Hopkins and Coursera, and the content is always excellent.
The instructors are well versed in the field and certainly have their hands full constructing software and analysis for what is quite possibly the number one research medical hospital/college in the country, Johns Hopkins.
Read more
well organized
Great, quick recap on the fast emerging science Good introduction course Very good material and well organized!
Well organized cou Quick and dirty rundown Excellent..
I do not have a statistics background and i was abit worried at first, but this was well organized and i am really glad i took it!
Very basic, for absolute beginners/ managers completely new to data (let alone data science) Very well organized course ..Short and to the point Solid introduction.
Highly Enlightening for those who just beginning to learn data science,The courses are very detailed and well organized,All the aspects of the data science are introduced in intriguing mannerThank you Too theoretical, e.g, comparison between statistics and ML is not at all useful.
Read more
other courses
Basic information on some of the terms you will encounter in other courses and in the real world.
More examples for each topic would be good.However it is a crash course, so it is more of an overall description of Data Science, which also gives you suggestions to enhance your knowledge in other courses The best course I ever had for the introduction to the hope of data science and giving a light over the future of data scientist.
I suggest pausing the videos and take notes to grasp everything, and for reference if you're going to take other courses along this path.
It answered a lot of basic questions and got me curious to pursue other courses on data science.
Read more
difference between
I am still wondering if there is 'any' difference between the two terms, what 'exactly' is it?
Excellent course coverage and helpful to understand the difference between hype and value.
Careers
An overview of related careers and their average salaries in the US. Bars indicate income percentile.
AD, Data Science $47k
Associate Data Science Supervisor $55k
Science writer / data analyst $63k
Genomic Data Science Programmer $75k
Volunteer Director of Data Science $78k
Expert Data Science Supervisor $79k
Supervisor 1 Data Science Supervisor $91k
Guest Director of Data Science $101k
Data Science Architect $105k
Head of Data Science $131k
Assistant Director 1 of Data Science $133k
Owner Director of Data Science $149k
Write a review
Your opinion matters. Tell us what you think.
Please login to leave a review
Rating | 4.3★ based on 1,003 ratings |
---|---|
Length | 2 weeks |
Effort | 1 week of study, 4-6 hours |
Starts | Jul 3 (39 weeks ago) |
Cost | $49 |
From | Johns Hopkins University via Coursera |
Instructors | Roger D. Peng, PhD, Jeff Leek, PhD, Brian Caffo, PhD |
Download Videos | On all desktop and mobile devices |
Language | English |
Subjects | Data Science Business |
Tags | Data Science Data Analysis Business Leadership And Management |
Similar Courses
Sorted by relevance
Like this course?
Here's what to do next:
- Save this course for later
- Get more details from the course provider
- Enroll in this course