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Вернуться к Managing Data Analysis

Отзывы учащихся о курсе Managing Data Analysis от партнера Университет Джонса Хопкинса

4.6
звезд
Оценки: 3,001
Рецензии: 421

О курсе

This one-week course describes the process of analyzing data and how to manage that process. We describe the iterative nature of data analysis and the role of stating a sharp question, exploratory data analysis, inference, formal statistical modeling, interpretation, and communication. In addition, we will describe how to direct analytic activities within a team and to drive the data analysis process towards coherent and useful results. This is a focused course designed to rapidly get you up to speed on the process of data analysis and how it can be managed. 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 basic data analysis iteration 2. Identify different types of questions and translate them to specific datasets 3. Describe different types of data pulls 4. Explore datasets to determine if data are appropriate for a given question 5. Direct model building efforts in common data analyses 6. Interpret the results from common data analyses 7. Integrate statistical findings to form coherent data analysis presentations Commitment: 1 week of study, 4-6 hours Course cover image by fdecomite. Creative Commons BY https://flic.kr/p/4HjmvD...
Основные моменты
Helpful quizzes
(рецензий: 3)
Well-organized content
(рецензий: 24)

Лучшие рецензии

EL
28 февр. 2017 г.

A long course compared to others in the specialization, but a lot of great material. Very well presented, the instructors know how to present this material and make it easy to grasp and understand.

ST
22 нояб. 2016 г.

The course is full of the cases and the real life examples coupled with the theory background. Its very simple to understand and the course will definitely be of an value for people looking for

Фильтр по:

301–325 из 418 отзывов о курсе Managing Data Analysis

автор: Benjamin T C

31 дек. 2019 г.

Like other reviewers said, this course is larger than the two previous courses. The content is excellent but I am giving 4/5 stars because I found many misspelled words throughout the course lectures.

автор: RANJITH D

7 апр. 2019 г.

This course is not for a person without any idea of Data analysis or Statistics. This course isn't for beginners. The content could have been presented even better with lucid examples.

автор: Vipul G

26 июля 2017 г.

Good overview of the process. Helped me in bridging data analysis processes with things that I already do as part of project management or business analytics/decision support projects.

автор: jose a z r

11 нояб. 2015 г.

Critical thinking is essential at the moment of working over data. This was a nice course with a very good theory about all the process,which a data analyst has to perform.

автор: Kevin C

31 окт. 2017 г.

Well defined strategies for getting a handle on the data analysis process. Short and concise class that hit on relevant points required to be successful in this area.

автор: George K

16 сент. 2017 г.

sometime it was not easy to understand the lecturer. also, it would be good to try some things out versus reading the expamples. other than that - a great course!

автор: Bernard D V

19 мар. 2020 г.

A great course with a lot of information. However, the course might be more concise sometimes due to the complexity of the information brought by the instructor.

автор: Scott K

10 окт. 2015 г.

Good course for the fundamentals of making sure data analysis is done correctly. These are good things to keep in mind when you are managing a data science team.

автор: Prabal T

27 дек. 2020 г.

Course is very good and concise from a business owner point of view. Other technical courses will definitely add to the nuances of full fledged insights.

автор: Kian G L

12 авг. 2016 г.

Comprehensive overview to understand activities involved in the iterations and epicycles of Data Analysis and to manage it with correct expectation.

автор: Victor D R L

24 апр. 2020 г.

It is a very good course but challenging, I had to make a lot of notes to understand the concepts and follow the lectures. It is a good investment.

автор: Deleted A

19 февр. 2019 г.

While it was good, a lot of overlapping information and I wish it had more specific examples (rather than theoretical) in public health standpoint.

автор: Sarah A M A

14 авг. 2020 г.

a lot of information, in a short period of time, I think it would be better if they use presentations and graphs and would be more easy to follow

автор: Abhi k

8 дек. 2015 г.

If you can make the assignments nearer to the real world scenario and a little more detailed explanations for some parts, it would be great!

автор: Siddharth T

3 апр. 2016 г.

The content is covered in great depth in this course but pre-reads may help as the course moves up a few notches in technical content.

автор: Filipe G

30 мар. 2018 г.

Useful overview of considerations when managing data analytics work. A bit superficial, but still a useful reminder of the basics.

автор: Jason C

10 июля 2016 г.

I would have preferred that the course and/or accompanying textbook contain examples of templates used to manage data analysis.

автор: Luciano C

28 июля 2017 г.

great course. i just thin there should be more real examples to help us to understand (for exemple types of questions), etc

автор: Chantelle N M

25 дек. 2015 г.

Teaches how to think about a problem more than the specific tools that can be used to solve them. Good practical examples.

автор: Aman U A

3 сент. 2020 г.

the English accent is hard for me to keep the focus on the topic, although all the lectures are informative and helpful.

автор: Daniel C d F

20 нояб. 2016 г.

Great course overall. Should only explain better a few related concepts such as the p-value and confidence interval.

автор: Rafael T

27 авг. 2017 г.

Course material is fantastic. However, materials could be better presented so that the videos are easier to follow.

автор: ABDELRAHIM A

6 янв. 2018 г.

Super and Really very Technical. It is One of the most important with this Specialization. I give the effect 87%

автор: prasanna v

31 янв. 2017 г.

EDA approach and steps to analyse is excellently taught. The formal modelling take the course to a lot of depth.

автор: Nina R

25 янв. 2020 г.

It is hard to manage the presentation. There is no option to replay and you cant go back if you missed a term.