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.
Programa especializado Executive Data Science
Be The Leader Your Data Team Needs. Learn to lead a data science team that generates first-rate analyses in four courses.
ofrecido por
Acerca de este Programa Especializado
Qué aprenderás
Become conversant in the field and understand your role as a leader.
Recruit, assemble, evaluate, and develop a team with complementary skill sets and roles.
Navigate the structure of the data science pipeline by understanding the goals of each stage and keeping your team on target throughout.
Overcome the common challenges that frequently derail data science projects.
Habilidades que obtendrás
Data ScienceData ManagementData AnalysisCommunicationLeadership
Cómo funciona Programa Especializado
Toma cursos
Un programa especializado de Coursera es un conjunto de cursos que te ayudan a dominar una aptitud. Para comenzar, inscríbete en el programa especializado directamente o échale un vistazo a sus cursos y elige uno con el que te gustaría comenzar. Al suscribirte a un curso que forme parte de un programa especializado, quedarás suscrito de manera automática al programa especializado completo. Puedes completar solo un curso: puedes pausar tu aprendizaje o cancelar tu suscripción en cualquier momento. Visita el panel principal del estudiante para realizar un seguimiento de tus inscripciones a cursos y tu progreso.
Proyecto práctico
Cada programa especializado incluye un proyecto práctico. Necesitarás completar correctamente el proyecto para completar el programa especializado y obtener tu certificado. Si el programa especializado incluye un curso separado para el proyecto práctico, necesitarás completar cada uno de los otros cursos antes de poder comenzarlo.
Obtén un certificado
Cuando completes todos los cursos y el proyecto práctico, obtendrás un Certificado que puedes compartir con posibles empleadores y tu red profesional.
Hay 5 cursos en este Programa Especializado
Curso1
A Crash Course in Data Science
4.5
4,677 calificaciones
By now you have definitely heard about data science and big data. In this one-week class, we will provide a crash course in what these terms mean and how they play a role in successful organizations. This class is for anyone who wants to learn what all the data science action is about, including those who will eventually need to manage data scientists. The goal is to get you up to speed as quickly as possible on data science without all the fluff. We've designed this course to be as convenient as possible without sacrificing any of the essentials.
This is a focused course designed to rapidly get you up to speed on the field of data science. 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. How to describe the role data science plays in various contexts
2. How statistics, machine learning, and software engineering play a role in data science
3. How to describe the structure of a data science project
4. Know the key terms and tools used by data scientists
5. How to identify a successful and an unsuccessful data science project
3. The role of a data science manager
Course cover image by r2hox. Creative Commons BY-SA: https://flic.kr/p/gdMuhT
Curso2
Building a Data Science Team
4.5
2,330 calificaciones
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
Curso3
Managing Data Analysis
4.5
2,053 calificaciones
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
Curso4
Data Science in Real Life
4.4
1,469 calificaciones
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
Instructores
Jeff Leek, PhD
Associate Professor, BiostatisticsBloomberg School of Public Health
Brian Caffo, PhD
Professor, BiostatisticsBloomberg School of Public Health
Roger D. Peng, PhD
Associate Professor, BiostatisticsBloomberg School of Public Health
Socios del sector
Acerca de Universidad 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.
Preguntas Frecuentes
¿Cuál es la política de reembolsos?
¿Puedo inscribirme en un solo curso?
¡Sí! Para empezar, haz clic en la tarjeta del curso que te interesa e inscríbete. Puedes inscribirte y completar el curso para obtener un certificado que puedes compartir o puedes acceder al curso como oyente para ver los materiales del curso de manera gratuita. Cuando cancelas la suscripción de un curso que forma parte de un programa especializado, se cancela automáticamente la suscripción de todo el programa especializado. Visita el panel del estudiante para realizar un seguimiento de tu progreso.
¿Hay ayuda económica disponible?
¿Puedo tomar este curso de manera gratuita?
¿Este curso es 100 % en línea? ¿Necesito asistir a alguna clase en persona?
Este curso es completamente en línea, de modo que no necesitas ir a un aula en persona. Puedes acceder a tus lecciones, lecturas y tareas en cualquier momento y cualquier lugar a través de Internet o tu dispositivo móvil.
¿Recibiré crédito universitario por completar el programa especializado?
Este programa especializado no otorga crédito universitario, pero algunas universidades pueden aceptar los Certificados del programa especializado para el crédito. Consulta con tu institución para obtener más información.
How long does it take to complete the Executive Data Science Specialization?
Time to completion can vary based on your schedule, but most learners are able to complete the Specialization in 2 months.
¿Con qué frecuencia se ofrece cada curso del programa especializado?
Each course in the Specialization is offered on a regular schedule, with sessions starting about once per month. If you don't complete a course on the first try, you can easily transfer to the next session, and your completed work and grades will carry over.
What background knowledge is necessary?
A basic understanding of how data can be used in an industry, academic, or government environment.
Do I need to take the courses in a specific order?
We recommend that you take the courses in the following order: Crash Course in Data Science, Building a Data Science Team, Managing Data Analysis, Data Science in Real Life
Will I earn university credit for completing the Executive Data Science Specialization?
Coursera courses and certificates don't carry university credit, though some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.
What will I be qualified to do upon completing the Executive Data Science Specialization?
Upon completion, you will be qualified to lead a team of data scientists. You will know how to ask the right questions, recruit the right people, and manage the full team as you work through the entire data science pipeline. The skills you learn in this specialization will prepare you to harness the potential of the data scientists in your organization and deliver world-class analyses to your clients and stakeholders.
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