Introducción a la Ciencia de Datos y el Big Data from edX

El futuro pertenece a la ciencia de datos y a quienes la entiendan. Al igual que el petróleo y el gas impulsaron las economías de los siglos XX y XXI, los datos impulsan cada vez mas la innovación y la economía global a medida que avanzamos hacia una nueva era denominada la revolución digital.

Las empresas que están cambiando a una mentalidad de datos van a obtener primero una enorme ventaja competitiva.

Esto se ha convertido en una verdad universal: las empresas modernas se están inundando de big data. El año pasado, McKinsey estimó que las iniciativas de Big Data en el sistema de salud de los Estados Unidos, "podrían representar de $300 mil millones a $450 mil millones en gastos de salud reducidos o del 12 al 17 por ciento de la línea de base de $2.6 billones en costos de salud de los Estados Unidos". Por otro lado, sin embargo se estima que los datos erróneos le cuestan a los Estados Unidos apróximadamente $3.1 trillones de dólares al año.

Aunque la ciencia de datos representará ventajas puntuales para las empresas como mitigar el riesgo y/o el fraude; entregar al cliente productos relevantes y tener experiencias personalizadas al mismo, es sin embargo, importante notar que la ciencia de datos podrá agregar un valor a cuaquier negocio, siempre y cuando pueda usar bien sus datos. El análisis de la información y la inteligencia de negocios ayudan a las organizaciones a tomar decisiones inteligentes basadas en el análisis de datos.

What's inside

Learning objectives

- introducir al alumno en los conceptos claves sobre la ciencia de datos y big data.
- comprender la forma en la que se gesta un proyecto de ciencia de datos.

- identificar los proyectos de esta disciplina que se pueden realizar en las diferentes áreas funcionales de una organización a través de casos de éxito en las diferentes industrias.

- introducir al alumno en los conceptos claves sobre la ciencia de datos y big data.
- comprender la forma en la que se gesta un proyecto de ciencia de datos.
- identificar los proyectos de esta disciplina que se pueden realizar en las diferentes áreas funcionales de una organización a través de casos de éxito en las diferentes industrias.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Pone los conceptos fundamentales de la ciencia de datos y los macrodatos al alcance del estudiante

Enseña la forma en que se crean los proyectos de ciencia de datos

Identifica proyectos de ciencia de datos que pueden realizarse en diversas áreas funcionales, mediante casos de éxito en las diferentes industrias

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Introducción a la Ciencia de Datos y el Big Data with these activities:

Familiarise with Basic Statistics

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Reinforce your foundational understanding of basic statistical concepts to enhance your ability to analyze and interpret data effectively.

Browse courses on Basic Statistics

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Review key statistical concepts such as mean, median, mode, variance, and standard deviation.
Practice calculating and interpreting statistical measures using sample datasets.
Re-familiarize yourself with probability distributions, including normal, binomial, and Poisson distributions.

Revise essential algebra skills

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Algebra is an essential skill for data science. By reviewing it, you'll strengthen your understanding of mathematical concepts and prepare for the course.

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Review key concepts such as variables, equations, and polynomials.
Practice solving linear equations and inequalities.
Factor polynomials and simplify algebraic expressions.

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Career center

Learners who complete Introducción a la Ciencia de Datos y el Big Data will develop knowledge and skills that may be useful to these careers:

Data Engineer

A Data Engineer builds and maintains data pipelines and infrastructure. The course, Introduction to Data Science and Big Data, can help build a foundation for a career as a Data Engineer. The course covers topics such as data mining, data visualization, and machine learning, which are all essential skills for a Data Engineer.

See salaries and explore the career path for Data Engineer

Business Intelligence Analyst

A Business Intelligence Analyst uses data to identify trends and patterns and make recommendations to improve business performance. The course, Introduction to Data Science and Big Data, can help build a foundation for a career as a Business Intelligence Analyst. The course covers topics such as data mining, data visualization, and machine learning, which are all essential skills for a Business Intelligence Analyst.

See salaries and explore the career path for Business Intelligence Analyst

Operations Research Analyst

An Operations Research Analyst uses data to solve optimization problems and improve decision-making. The course, Introduction to Data Science and Big Data, can help build a foundation for a career as an Operations Research Analyst. The course covers topics such as data mining, data visualization, and machine learning, which are all essential skills for an Operations Research Analyst.

See salaries and explore the career path for Operations Research Analyst

Statistician

A Statistician uses data to design and conduct statistical studies and analyze data. The course, Introduction to Data Science and Big Data, can help build a foundation for a career as a Statistician. The course covers topics such as data mining, data visualization, and machine learning, which are all essential skills for a Statistician.

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Machine Learning Engineer

A Machine Learning Engineer builds and deploys machine learning models. The course, Introduction to Data Science and Big Data, can help build a foundation for a career as a Machine Learning Engineer. The course covers topics such as data mining, data visualization, and machine learning, which are all essential skills for a Machine Learning Engineer.

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Market Researcher

A Market Researcher uses data to understand consumer behavior and trends. The course, Introduction to Data Science and Big Data, can help build a foundation for a career as a Market Researcher. The course covers topics such as data mining, data visualization, and machine learning, which are all essential skills for a Market Researcher.

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Data Analyst

A Data Analyst uses data to solve business problems and improve decision-making. The course, Introduction to Data Science and Big Data, can help build a foundation for a career as a Data Analyst. The course covers topics such as data mining, data visualization, and machine learning, which are all essential skills for a Data Analyst.

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Data Scientist

A Data Scientist uses data to build predictive models and develop new insights. The course, Introduction to Data Science and Big Data, can help build a foundation for a career as a Data Scientist. The course covers topics such as data mining, data visualization, and machine learning, which are all essential skills for a Data Scientist.

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Product Manager

A Product Manager uses data to make decisions about product development and marketing. The course, Introduction to Data Science and Big Data, can help build a foundation for a career as a Product Manager. The course covers topics such as data mining, data visualization, and machine learning, which are all essential skills for a Product Manager.

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Quantitative Analyst

A Quantitative Analyst uses data to develop trading strategies and make investment decisions. The course, Introduction to Data Science and Big Data, can help build a foundation for a career as a Quantitative Analyst. The course covers topics such as data mining, data visualization, and machine learning, which are all essential skills for a Quantitative Analyst.

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Consultant

A Consultant uses data to solve problems and improve decision-making for clients. The course, Introduction to Data Science and Big Data, can help build a foundation for a career as a Consultant. The course covers topics such as data mining, data visualization, and machine learning, which are all essential skills for a Consultant.

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Database Administrator

A Database Administrator manages and maintains databases. The course, Introduction to Data Science and Big Data, may be useful for building a foundation for a career as a Database Administrator. The course covers topics such as data mining, data visualization, and machine learning, which are all relevant to the work of a Database Administrator.

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Data Architect

A Data Architect designs and builds data systems and infrastructure. The course, Introduction to Data Science and Big Data, may be useful for building a foundation for a career as a Data Architect. The course covers topics such as data mining, data visualization, and machine learning, which are all relevant to the work of a Data Architect.

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Software Engineer

A Software Engineer designs, develops, and tests software systems. The course, Introduction to Data Science and Big Data, may be useful for building a foundation for a career as a Software Engineer. The course covers topics such as data mining, data visualization, and machine learning, which are all relevant to the work of a Software Engineer.

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System Administrator

A System Administrator manages and maintains computer systems and networks. The course, Introduction to Data Science and Big Data, may be useful for building a foundation for a career as a System Administrator. The course covers topics such as data mining, data visualization, and machine learning, which are all relevant to the work of a System Administrator.

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