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.
Este curso faz parte do Programa de cursos integrados Executivo em ciência de dadosExecutivo em Ciência Dados
Ciência de Dados na Vida Real
oferecido por
Programa de cursos integrados Executivo em ciência de dadosExecutivo em Ciência Dados Universidade Johns Hopkins
Informações sobre o curso
19,726 visualizações recentes
Resultados de carreira do aprendiz
33%
comecei uma nova carreira após concluir estes cursos
14%
consegui um benefício significativo de carreira com este curso
O que você vai aprender
Identify strengths and weaknesses in experimental designs
Learn novel solutions for managing data pulls
Describe common pitfalls in communicating data analyses
Understand a typical day in the life of a data analysis manager
Habilidades que você terá
StatisticsData ScienceData AnalysisData Management
Resultados de carreira do aprendiz
33%
comecei uma nova carreira após concluir estes cursos
14%
consegui um benefício significativo de carreira com este curso
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Aprox. 7 horas para completar
Inglês
Legendas: Inglês
Programa - O que você aprenderá com este curso
5 horas para concluir
Introduction, the perfect data science experience
This course is one module, intended to be taken in one week. Please do the course roughly in the order presented. Each lecture has reading and videos. Except for the introductory lecture, every lecture has a 5 question quiz; get 4 out of 5 or better on the quiz.
5 horas para concluir
22 vídeos (Total 160 mín.), 10 leituras, 6 testes
22 videos
Data science in the ideal versus real life Part 14min
Data science in the ideal versus real life Part 23min
Examples7min
Machine Learning vs. Traditional Statistics Part 114min
Machine Learning vs. Traditional Statistics Part 23min
Managing the Data Pull11min
Experimental design and observational analysis10min
Causality part 18min
Causality Part 29min
What Can Go Wrong?: Confounding5min
A/B Testing9min
Sampling bias and random sampling5min
Blocking and adjustment11min
Multiplicity6min
Effect size, significance, & modeling7min
Comparison with benchmark effects4min
Negative controls5min
Non-significance5min
Estimation Target is Relevant10min
Report writing8min
Version control4min
10 leituras
Pre-Course Survey10min
Course structure10min
Grading10min
The data pull is clean10min
The experiment is carefully designed10min
The experiment is carefully designed, things to do10min
Results of analyses are clear10min
The decision is obvious10min
The analysis product is awesome10min
Post-Course Survey10min
6 exercícios práticos
The Data Pull is Clean10min
The experiment is carefully designed principles10min
The experiment is carefully designed, things to do10min
Results of analyses are clear8min
The Decision is Obvious10min
The analysis product is awesome10min
Avaliações
Principais avaliações do CIÊNCIA DE DADOS NA VIDA REAL
por SMAug 19, 2017
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.
por ESNov 11, 2017
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.
por YYOct 26, 2016
Dr.Caffo is really well-versed with his field but I feel like concepts should be given more concrete examples so that they seem more interesting. Respect him all the way!
por PEMar 11, 2017
Brian Caffo does a terrific job teaching some of more advanced material, I very much appreciate his jokes and humor, as well as his helpful explanations of the material.
por NJMar 4, 2018
Examples used in this course are related to Lifescience and candidates like me find it difficult to correlate. It would be beneficial to use some common life examples.
por KLAug 12, 2016
Is good to have some data science background to enroll in this course, overall still good to learn and get the hint of how real life data scientist life is.
por JAMay 8, 2018
Good course - I'm now confident to oversee an end-to-end data science experiment. Some interactivity would make this the perfect overview of data science.
por PFFeb 11, 2018
Another excellent Executive Data Science course. Brian gives clear and concise explanations of the ideal versus real world of the data science workplace.
por RFDec 22, 2017
I like that this course examples the many ways an experiment/analysis can go wrong and how to address these issues. Very practical for the practitioner.
por MMJan 6, 2017
Clear explanation of various concepts with good examples. Of course, reference to some cool cartoons from time to time made the concepts more memorable!
por AGNov 13, 2016
An amazing course for those who are not very familiar with statistics and a very refreshing perspective for those who actually knows statistics!
por STApr 2, 2016
Again a course with depth in content but the presentation of the course could improve , it seems a bit patchy and pre-reads would help.
por LLJan 28, 2019
This is a recommended course where you understand what are the requirements for a data engineer, data manager and data scientis
por VVMar 7, 2020
A very well crafted course, with apt messaging and good assessments. Was able to learn a lot about the nuances of Data Science
por EMOct 9, 2018
Great course, although, if you are not already working or have knowledge in this particular filed/topic, it is challenging.
por MLMar 30, 2018
An excellent overview of the topic material without a lot of unnecessary clutter. Well-organized and -communicated. Kudos.
por PSJul 7, 2019
The authors really present real situation and challenges that data scientists face in their daily activities. Very good.
por KNApr 30, 2016
Good concepts - apply to anyone new to data science.\n\nLot of good 'read further' links and materials. Learnt a lot.
por RASep 23, 2018
Very easy to follow with good examples. The focus on this course was on practicality and I really appreciated that
por WKJan 3, 2017
Excellent course. The material is good enough that will help me where to look for information, considerations, a
oferecido por
Universidade Johns Hopkins
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.
Sobre Programa de cursos integrados Executivo em ciência de dadosExecutivo em Ciência Dados
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.
Perguntas Frequentes – FAQ
Quando terei acesso às palestras e às tarefas?
Ao se inscrever para um Certificado, você terá acesso a todos os vídeos, testes e tarefas de programação (se aplicável). Tarefas avaliadas pelos colegas apenas podem ser enviadas e avaliadas após o início da sessão. Caso escolha explorar o curso sem adquiri-lo, talvez você não consiga acessar certas tarefas.
O que recebo ao me inscrever nesta Especialização?
Quando você se inscreve no curso, tem acesso a todos os cursos na Especialização e pode obter um certificado quando concluir o trabalho. Seu Certificado eletrônico será adicionado à sua página de Participações e você poderá imprimi-lo ou adicioná-lo ao seu perfil no LinkedIn. Se quiser apenas ler e assistir o conteúdo do curso, você poderá frequentá-lo como ouvinte sem custo.
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