Data Analysis with R Programming

• ¿Cuándo podré acceder a las lecciones y tareas?

  El acceso a las clases y las asignaciones depende del tipo de inscripción que tengas. Si tomas un curso en modo de oyente, verás la mayoría de los materiales del curso en forma gratuita. Para acceder a asignaciones calificadas y obtener un certificado, deberás comprar la experiencia de Certificado, ya sea durante o después de participar como oyente. Si no ves la opción de oyente:

  • es posible que el curso no ofrezca la opción de participar como oyente. En cambio, puedes intentar con una Prueba gratis o postularte para recibir ayuda económica.

  • Es posible que el curso ofrezca la opción 'Curso completo, sin certificado'. Esta opción te permite ver todos los materiales del curso, enviar las evaluaciones requeridas y obtener una calificación final. También significa que no podrás comprar una experiencia de Certificado.

• ¿Qué recibiré si me suscribo a este Certificado?

  Cuando te inscribes en un curso, obtienes acceso a todos los cursos del Certificado y te darán un certificado cuando completes el trabajo. Se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes auditar el curso sin costo.

• What is data analytics?

  Data is a group of facts that can take many different forms, such as numbers, pictures, words, videos, observations, and more. We use and create data everyday, like when we stream a show or song or post on social media.

  Data analytics is the collection, transformation, and organization of these facts to draw conclusions, make predictions, and drive informed decision-making.

• Why start a career in data analytics?

  The amount of data created each day is tremendous. Any time you use your phone, look up something online, stream music, shop with a credit card, post on social media, or use GPS to map a route, you’re creating data. Companies must continually adjust their products, services, tools, and business strategies to meet consumer demand and react to emerging trends. Because of this, data analyst roles are in demand and competitively paid.

  Data analysts make sense of data and numbers to help organizations make better business decisions. They prepare, process, analyze, and visualize data, discovering patterns and trends and answering key questions along the way. Their work empowers their wider team to make better business decisions.

• Why enroll in the Google Data Analytics Certificate?

  You will learn the skill set required for becoming a junior or associate data analyst in the Google Data Analytics Certificate. Data analysts know how to ask the right question; prepare, process, and analyze data for key insights; effectively share their findings with stakeholders; and provide data-driven recommendations for thoughtful action.

  You’ll learn these job-ready skills in our certificate program through interactive content (discussion prompts, quizzes, and activities) in under six months, with under 10 hours of flexible study a week. Along the way, you'll work through a curriculum designed with input from top employers and industry leaders, like Tableau, Accenture, and Deloitte. You’ll even have the opportunity to complete a case study that you can share with potential employers to showcase your new skill set.

  After you’ve graduated from the program, you’ll have access to career resources and be connected directly with employers hiring for open entry-level roles in data analytics.

• What background is required?

  No prior experience with spreadsheets or data analytics is required. All you need is high-school level math and a curiosity about how things work.

• Do you need to be strong at math to succeed in this certificate?

  You don't need to be a math all-star to succeed in this certificate. You need to be curious and open to learning with numbers (the language of data analysts). Being a strong data analyst is more than just math, it's about asking the right questions, finding the best sources to answer your questions effectively, and illustrating your findings clearly in visualizations.

• What tools and platforms are taught in the curriculum?

  You'll learn to use analysis tools and platforms such as spreadsheets (Google Sheets or Microsoft Excel), SQL, presentation tools (Powerpoint or Google Slides), Tableau, RStudio, and Kaggle.

• Will you be teaching R or Python?

  This program teaches the open-source programming language, R. R is a great starting point for foundational data analysis, and offers helpful packages for beginners to apply to their projects. We do not cover Python in the curriculum but encourage you to explore Python after completion if you'd like to continue your learning journey.

• Which “spreadsheet” platform is being taught?

  Learners can self-select which platform they want to use throughout the program: Google Sheets or Microsoft Excel. It’s up to the learner’s preference, and all activities throughout the syllabus can be performed on either platform.

• Do you need to take each course in course order?

  We highly recommend completing the courses in the order presented because the content in each course builds on information from earlier lessons.

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