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學生對 约翰霍普金斯大学 提供的 生活中的数据科学 的評價和反饋

4.4
2,288 個評分
277 條評論

課程概述

Have you ever had the perfect data science experience? The data pull went perfectly. There were no merging errors or missing data. Hypotheses were clearly defined prior to analyses. Randomization was performed for the treatment of interest. The analytic plan was outlined prior to analysis and followed exactly. The conclusions were clear and actionable decisions were obvious. Has that every happened to you? Of course not. Data analysis in real life is messy. How does one manage a team facing real data analyses? In this one-week course, we contrast the ideal with what happens in real life. By contrasting the ideal, you will learn key concepts that will help you manage real life analyses. This is a focused course designed to rapidly get you up to speed on doing data science in real life. 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 how to: 1, Describe the “perfect” data science experience 2. Identify strengths and weaknesses in experimental designs 3. Describe possible pitfalls when pulling / assembling data and learn solutions for managing data pulls. 4. Challenge statistical modeling assumptions and drive feedback to data analysts 5. Describe common pitfalls in communicating data analyses 6. Get a glimpse into a day in the life of a data analysis manager. The course will be taught at a conceptual level for active managers of data scientists and statisticians. Some key concepts being discussed include: 1. Experimental design, randomization, A/B testing 2. Causal inference, counterfactuals, 3. Strategies for managing data quality. 4. Bias and confounding 5. Contrasting machine learning versus classical statistical inference Course promo: https://www.youtube.com/watch?v=9BIYmw5wnBI Course cover image by Jonathan Gross. Creative Commons BY-ND https://flic.kr/p/q1vudb...
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Statistics review
(44 條評論)

熱門審閱

SM
2017年8月19日

A very good and concise course that helps to understand the basics of the Data Science and its applications. The examples are very relevant and helps to understand the topic easily.

ES
2017年11月11日

Highly educational course on the realities of data analysis. Many good tips for your own analyses as well as for managing others responsible for coherent and accurate analyses.

篩選依據:

226 - 生活中的数据科学 的 250 個評論(共 279 個)

創建者 Luis A S E

2021年3月15日

Good

創建者 Parag

2021年2月7日

.

創建者 David T

2016年11月14日

Some good tips, nothing terribly new for those who have had a course in statistics. Materials made easy to digest. The variety from the 3 instructors was nice. Missed opportunity: to combine the best aspects from each. The course notes were either excerpts from R.Peng's books /blogs (good) or automated transcripts (complete with typical AI typos... "wait" instead of "weight"). Some lectures were repetitive from one course to another. Slides with examples were useful, slides with clip-art and comic stips less so. Tries to be something for everyone. Would be better to aim either at former DS analysts aspiring to be managers or seasoned managers trying to better understand DS.

創建者 Ruben S

2016年8月17日

Brian tries to achieve too much in too little time. It addresses important issues and it gives a good overview, including some hidden gems (Machine Learning vs Stats, for example), but it feels mostly too rushed and superficial for my taste/expectations, and it fails to connect to my previous knowledge (and I have a PhD in Maths, although no strong Stats background), hence little added value for me when I cannot relate to what is being discussed.

創建者 Rajeev R

2015年12月7日

Lectures themselves were OK, but presentation needs work. Intro session was very repetitive. Lot of jargon introduced without explanation. Pop-ups w text showed up but disappeared before I was able to finish reading them. Best part of course was actually the text notes at the beginning of each sesssion. A minor nitpick: course description suggests that there are 3 instructors presenting, but I only saw one.

創建者 Gonzalo G A

2016年12月16日

It's sometimes difficult to follow professors beacuse they take for granted information about the examples they use that is not evident for the learners. They should take a minute to explain a little bit more what the examples consist of and what are the charts they show. As it happens when Brian Caffo explains the blocking adjustments part.

創建者 Cauri J

2017年7月4日

I found this course used a lot of jargon without explanation. It seems like the instructor understands the content so well that he assumes a level of knowledge from students that do not match the expectations of the rest of the content in this track. At the same time I found the content well presented.

創建者 Michail C

2019年7月17日

This course is an excellent effort to document the issues faced in real-life data science. However, the flow of the videos seems to be a bit confusing and some of the content is explained in a weird manner.

創建者 Daniel C d F

2016年12月5日

I missed several concepts to better understand some of the discussions and explanations. It was valid, but I think the statistics background should be better explored.

創建者 Peter L

2018年8月14日

The course is valuable but highly focussed on scientific applications (inference) and less on business application (i.e. prediction). I hoped for a more even mix.

創建者 Astolfo

2020年7月5日

It was good, but the content is harder to understand in this course.

I would prefer a similar format and emphasis as the other two last courses.

創建者 Sean H

2015年11月24日

The video quality and content were good. Unfortunately, there were a lot of spelling errors and grammatical mistakes in the written portions.

創建者 Chong K M

2018年3月18日

Very difficult and time consuming course which contains a lot of technical words and jargon. Not recommended for the average beginner.

創建者 Jean-Michel M

2019年2月22日

I would drop some of the cartoons. They are funny but they seem to distract Bryan and overall it's distracting for us students too.

創建者 PAVITHRA.T

2020年7月28日

First of all it's too tough to understand but day by day I understood something I got it ..tq.it is very helpful for my studies

創建者 Rong-Rong C

2017年12月14日

There is a lot of technical jargon covered which made the course more challenging than the other courses in the series.

創建者 Alberto M B

2019年3月20日

It wasn't as focus on Managing Data Scientists as I was expecting, but rather focus on tips for Data Scientist.

創建者 Marco A P

2017年1月2日

Much theorical with few examples. Could incorporate examples outside the health world as well.

創建者 Giovany G

2020年7月15日

I would prefer that the examples be expressed with statistical and mathematical calculations

創建者 Gilson F

2019年8月2日

Não gostei muito da didatica do instrutor e os slides não ajudam no entendimento

創建者 emilio z

2017年6月6日

Explanations in videos qere not very clear nor very well connecetd with the Quiz

創建者 Christopher L

2018年5月3日

Would have liked a bit more examples and math in some cases. Others were fine.

創建者 Ioannis L

2017年4月9日

A bit less engaging than the other parts of the Executive Data Science course.

創建者 Patricia S

2020年1月2日

good content but could be simplified and presented in a more focused man

創建者 Gowtham V

2020年5月2日

Would like to have simpler examples to understand some of the concepts.