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.
Этот курс входит в специализацию ''Специализация Наука о данных для руководителей'
Managing Data Analysis
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Курс 3 из 5 в программе
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Прибл. 6 часа на выполнение
Английский
Субтитры: Английский, Японский
Чему вы научитесь
Differentiate between various types of data pulls
Describe the basic data analysis iteration
Explore datasets to determine if data is appropriate for a project
Use statistical findings to create convincing data analysis presentations
Приобретаемые навыки
Data AnalysisCommunicationInterpretationExploratory Data Analysis
Карьерные результаты учащихся
29%
начал новую карьеру, пройдя эти курсы
30%
получил значимые преимущества в карьере благодаря этому курсу
10%
стал больше зарабатывать или получил повышение
Сертификат, ссылками на который можно делиться с другими людьми
Получите сертификат по завершении
100% онлайн
Начните сейчас и учитесь по собственному графику.
Курс 3 из 5 в программе
Гибкие сроки
Назначьте сроки сдачи в соответствии со своим графиком.
Прибл. 6 часа на выполнение
Английский
Субтитры: Английский, Японский
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Университет Джонса Хопкинса
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.
Программа курса: что вы изучите
6 ч. на завершение
Managing Data Analysis
Welcome to Managing Data Analysis! This course is one module, intended to be taken in one week. The course works best if you follow along with the material in the order it is presented. Each lecture consists of videos and reading materials that expand on the lecture. I'm excited to have you in the class and look forward to your contributions to the learning community. If you have questions about course content, please post them in the forums to get help from others in the course community. For technical problems with the Coursera platform, visit the Learner Help Center. Good luck as you get started, and I hope you enjoy the course!
6 ч. на завершение
19 видео ((всего 144 мин.)), 17 материалов для самостоятельного изучения, 7 тестов
19 видео
Data Analysis Iteration8мин
Stages of Data Analysis1мин
Six Types of Questions6мин
Characteristics of a Good Question6мин
Exploratory Data Analysis Goals & Expectations11мин
Using Statistical Models to Explore Your Data (Part 1)13мин
Using Statistical Models to Explore Your Data (Part 2)5мин
Exploratory Data Analysis: When to Stop6мин
Making Inferences from Data: Introduction5мин
Populations Come in Many Forms4мин
Inference: What Can Go Wrong7мин
General Framework8мин
Associational Analyses10мин
Prediction Analyses10мин
Inference vs. Prediction12мин
Interpreting Your Results10мин
Routine Communication in Data Analysis6мин
Making a Data Analysis Presentation5мин
17 материала для самостоятельного изучения
Pre-Course Survey10мин
Course Textbook: The Art of Data Science10мин
Conversations on Data Science10мин
Data Science as Art10мин
Epicycles of Analysis10мин
Six Types of Questions10мин
Characteristics of a Good Question10мин
EDA Check List10мин
Assessing a Distribution10мин
Assessing Linear Relationships10мин
Exploratory Data Analysis: When Do We Stop?10мин
Factors Affecting the Quality of Inference10мин
A Note on Populations10мин
Inference vs. Prediction10мин
Interpreting Your Results10мин
Routine Communication10мин
Post-Course Survey10мин
7 практического упражнения
Data Analysis Iteration10мин
Stating and Refining the Question16мин
Exploratory Data Analysis10мин
Inference10мин
Formal Modeling, Inference vs. Prediction10мин
Interpretation10мин
Communication10мин
Рецензии
Основные моменты
"Helpful quizzes" в отзывах (3)
"Well-organized content" в отзывах (24)
Лучшие отзывы о курсе MANAGING DATA ANALYSIS
от партнера BCDec 30, 2019
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.
от партнера ELFeb 28, 2017
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.
от партнера STNov 22, 2016
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
от партнера KLApr 16, 2018
Great course for those who want a comprehensive overview of an analysis from A-Z. The professor explains each aspect in perfect detail, gives easy to understand examples, very comprehensive.
от партнера MMJan 20, 2017
Overall, the course is well structured. The topics covered are very significant in my day to day operations. I can apply everything I learnt from this course with greater understandability.
от партнера MBSep 3, 2017
One of the best courses I've taken. The instructor presented a clear approach and variety of suggestions for improving the consistency and quality of data science projects. Very useful!
от партнера RDApr 6, 2019
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.
от партнера VGJul 25, 2017
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.
от партнера LLOct 31, 2015
professor Peng gave very practical advice on the design of the statistical model, and generalized procedure to conduct data analysis.and he gave very informative written reviews too!
от партнера JWMay 29, 2016
This is a challenging and excellent course ! This course really tunes you into the nuances of Data Analysis.\n\nI would recommend this course for anyone in Data Management.
от партнера VWJan 31, 2017
Good review of the data analysis process, though it loses momentum when it gets into the communication & presentation areas. On to the next course in the specialization!
от партнера JFJan 11, 2018
This felt a lot more detailed that the previous courses (which was great!) and I feel like I've genuinely learned some stuff (the six type of questions) that I can use!
от партнера KCOct 30, 2017
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.
от партнера AFAug 24, 2018
This was the best part of Specialization until now. As Product Manager I do think it's was great to understand concepts about data analysis and how to manage a team.
от партнера CTFeb 7, 2020
Excellent course. Really enjoyed the instructor. Finally getting into some analysis. Made me want to refresh my stat skills and get working on a challenging project!
от партнера GKSep 15, 2017
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!
от партнера SKOct 10, 2015
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.
от партнера BMar 18, 2020
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.
от партнера SSSep 21, 2016
Great examples about difference between 'association' and 'predictive' understanding and pitfalls of decision making without knowing which one to be used where!
от партнера EWJul 31, 2017
Excellent summary of the data analysis process. As the leader of a data science team, this class makes me want to tell my team to keep up the great work!
Специализация Наука о данных для руководителей: общие сведения
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.
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