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Opiniones y comentarios de aprendices correspondientes a Building a Data Science Team por parte de Universidad Johns Hopkins

4.5
2,569 calificaciones
341 revisiones

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Data science is a team sport. As a data science executive it is your job to recruit, organize, and manage the team to success. In this one-week course, we will cover how you can find the right people to fill out your data science team, how to organize them to give them the best chance to feel empowered and successful, and how to manage your team as it grows. This is a focused course designed to rapidly get you up to speed on the process of building and managing a data science team. 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. The different roles in the data science team including data scientist and data engineer 2. How the data science team relates to other teams in an organization 3. What are the expected qualifications of different data science team members 4. Relevant questions for interviewing data scientists 5. How to manage the onboarding process for the team 6. How to guide data science teams to success 7. How to encourage and empower data science teams Commitment: 1 week of study, 4-6 hours Course cover image by JaredZammit. Creative Commons BY-SA. https://flic.kr/p/5vuWZz...
Aspectos destacados
Applicable teachings
(79 revisiones)
Brief, helpful lectures
(11 revisiones)

Principales revisiones

NN

Dec 15, 2017

This course was an exceptional experience where it introduces me to building a data science team, its challenges, nuances and also what kind of approach to take while building and sustaining the team.

JS

Mar 12, 2017

Extremely practical and essentially human, this was really interesting to better understand the different roles and how to help data science teams to work together, highly recommended

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226 - 250 de 334 revisiones para Building a Data Science Team

por Scott K

Oct 11, 2015

Good overview of the different roles and skills needed for the roles of a data science team.

por Vaughan W

Jan 31, 2017

Good overview of the roles and skills needed, but loses a little momentum when it gets into the team management side of things, which is covered in many other business courses.

por SIVA A M

Oct 14, 2015

Topics are explained pretty good

por Ankush B

Nov 04, 2015

Covers theory of basics for building the team very well.

por Luis C

Feb 16, 2016

A good overview on how to build and manage data science teams.

por Karthik S N

Apr 24, 2016

Great for a someone who wants to build or invest in a data science team.

por GIacomo V

Dec 21, 2015

I really enjoyed this course and I have found a lot of similarities with issues and challenges that I face every day at work. This has been very useful to me bot as a way to get inspired on new ideas and techniques, and as a way to confirm what I am already doing.

However, there were few occasions where I found the quizzes not to be clear enough.

In some instances this was due to the fact that the question asked required some extra knowledge that couldn't possibly be achieved only by reading the course material or listening to the class. I was lucky I new the answers because of my personal experience but it seemed quite unfair in my opinion. Also lectures materials are very short and don;t provide any extra information.

In other cases, the answers, especially when there were multiple answers didn't seem to be clear enough and sometimes contradicting what I had listened in the class. I don't remember specific cases at the moment, however I have left feedbacks throughout the course. You should have my feedbacks where I mentioned specific questions that in my opinion were confusing.

Hope this helps,

Giacomo

por Chris G

Jun 18, 2016

This is a great course and a daring venture for what is really an art form, beyond it's scientific requirements. This part of the specialization needs a little refinement.

I posted this in the discussion forum.

· 7 days ago · Edited

First of all.....these guys running this data science department have their hands full. They are teaching live classes for students who have spent OODLES (lots) of money to attend this prestigious college . Johns Hopkins is about as good as it gets for a medical degree. Then they are doing experiments and other data science for the research division of Johns Hopkins which is also as good as it gets........THEN they are doing these MOOC courses on top of all their other responsibilities......Dr. Leek is a University of Washington Alumni, which is also top notch for Data Science.

The video lesson is flawed, there is no denying it. But I must say these teachers are very open to improvement in the course and your comments on what could be better done are received and acted upon, so I would include them in your thank you letter to the teachers.

ALSO I think these MOOC courses are best done by all members of the department contributing. Truly this field IS a team sport. I feel this course was good, but the videos need to be edited and scripted, so unnecessary language, which dilutes the core knowledge, that must be learned, is not diluted where questions are left in the students head about content when being tested. I learned long ago in a college calculus class that if your mark isn't perfect, it's OK, so long as you pass with a high score......even if it is the teachers fault. The course could use better video production with teleprompter scripting......maybe some AV students at Johns Hopkins could get on board. it will happen eventually I'm sure.

You want to take a course that is absolutely one of the best courses I've taken anywhere and truly the best online. Try the number one business course on Coursera:

GROW TO GREATNESS, either part 1 or 2, University of Virginia, Darden School Of Business...........A team created course with one helluva a teacher who is a business person, researcher and award-winning writer. I would recommend this course to ANY student and especially E-Teachers.

The problem with this course is that there is a lot of information that can be included but may not be absolutely necessary as a "core concept". Needless to say, the more technical skills any employee has, the more insight they will have into their teammate's skills, as well, as the overall mission of the data department and the business it serves. I'm more of a tech and infrastructure person, I'm not real passionate about coding. I find it tedious. The more I learn about it, the more I enjoy it, albeit, from a distance. I can't see myself creating great blocks of scripts, but the more I know about how they are created AND what rules the code in a project must abide by, the better my skills will be as a data center manager. So I'm trying to learn as much as possible about R, Python, and companion programs like ggvis for creating visualizations. I'd say visualizations are an essential skill for a data manager, since you have to present results and projects, questions, and answers to higher ups and other departments.

this link comes from the resource section of this course:

https://www.datacamp.com/courses/ggvis-data-visualization-r-tutorial

This link or URL is of much more value to me, than a flawed test question and a reduction in my 100 percent average in the specialization.

Without this lesson, in this course, I would not have this valuable resource.

Another great link, which has a great FREE print publication as well:

http://www.processor.com/ ...these people have been advising data center managers longer than just about anybody !

Verbally and in the transcript are some nebulous statements that point toward the main idea, that concept being: the more any employee, on any data science or technical team member IS, a "jack of all trades", the better. So that could have been included in some more general way on the quiz, because really that is pretty much a general rule, I've found, working in ANY capacity in the tech industry. I have done a great deal of audio editing, working at numerous radio stations, with Adobe Audition. With others like: Pro Tools, or any other really good quality AV digital editor the result is streamlined, near seamless, audio-video, or one or the other. You just learn how to read and edit wave forms of all kinds.

Years ago, in Dallas, Texas, attending Richland College. I learned a valuable lesson. I was taking a college level Calc-Trig math class being taught by the regular professor's WIFE. I don't know if the professor was sick, but this woman, who was teaching the class for the whole semester, frankly, was not qualified. I had always been considered an illiterate by my high school math teachers, a married couple who, frankly, were highly abnormal even on the geekiest scale. These people were acting like they were a world above most people in the class. Needless to say, I assumed, by their "adult" opinions, they were sent by God Himself, to educate me thru denigration.

I was amazed, how 10 years later, in College math how well I was doing. I was carrying a 100 percent average ! So midterm this faux professor declares, "I'll be prefiguring all the arithmetic to be easy, so you won't have to bring your calculators !"

SO I DIDN'T.......and of course the teacher's wife proclaims....."I didn't have time to make the arithmetic easy so you'd better use your calculators !" I literally had pages and pages of figuring in handwriting accompanying my 3 page test. The result was a C plus on the test. I angrily told the sub teacher "I did not bring a calculator to this test because you said it wouldn't be necessary, therefore I must be allowed to redo this test with a calculator !" She of course relented, "No that won't be possible...that's not a bad grade...." she continued, "what are you worried about ?"........

I was so peeved, I was going to drop the class. It was too late in the semester, and I was so disgusted with this woman's cavalier dismissal of my perfect grade that I just stopped going to class. The result was a failing final grade.

Who ultimately suffered from this dilemma ? That, albeit, unfairly was me.....who created this "academic" tragedy, by the aggravation of a deeply flawed situation. Once again, that would be me.

por Stephanie G

May 21, 2018

A brush up on management 101 with a data twist

por Ben W

Oct 10, 2016

A good, enjoyable course with some interesting additional reading. I think I would have preferred a little more detail/content to have given it a full five stars. That said...I am very happy to have taken and passed the course. Thank you all involved. Now on to 'Managing Data Analysis'!!

por Julien N

Feb 20, 2018

Nice explications of a data science team, its players and how they interact within their team and the other departments of their organisation.

The Capstone project is the perfect application of this class

por Ryan V

May 22, 2016

Good but should come after the Managing Data Analysis for understanding better what the people you hire are actually going to do. Preventing the "Dilbertification" of the data science manager.

por Azran O

Jan 12, 2017

Good pointers but not a lot of unique new insights. A lot of this is based on building any team, not unique to Data Science

por Rubén D C R

Sep 25, 2016

I will like a little more of excersices, "real"/"simulate" problems.

por Thomas A

May 09, 2016

Gives a good overview for newbies in the field and provides a few great link

por Cyril B

Feb 22, 2017

A very interesting course focus on the true life with data science teams. This course is more about the day to day life and problem to manage a data science team and less about pure organization. The financial aspects are not covered by Jeff nor the complex problems of people organization. I have noticed that I was the sole person to post on the forum.

por Anand P

Jan 21, 2017

Very useful for learners who do not have a background in Data Science or, Software engineering

por Richard B

Jul 19, 2017

really good practical content

por Sergey V

Feb 13, 2018

Most of what has been said can be applied for building Software Engineering Team. Nothing special if you have experience in managing Software Engineers.

por Alfredo P J

Jan 13, 2018

Great summary of mangement a Data Science Team!-. Includes roles on multiple entrepreneur configurations depending on size.

por VERONICA C

Sep 16, 2017

Great ad

por Nilay B

Dec 18, 2016

Material presented was succinct and easily understandable.

por Juliana A

Jul 12, 2017

Very informative but a bit repetitive ate some points.

por Ravi K S

Apr 04, 2018

1 start less because of the ever-confusing quiz questions. Hit and trials make you go mad, and insance when you figure out the correct answer that you couldn't have imagined.

por Usman A

Jan 17, 2018

There are too many variations in how teams get built, recruited and ramped up.