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Aplicaciones de ciencias de datos en los negocios actuales

La ciencia de los datos se encarga de la extracción, preparación, análisis y presentación visual de datos. Existen diferentes lenguajes de programación que otorgan posibilidades para realizar proyectos de ciencia de datos y nos permitan tomar decisiones. R es un lenguaje muy popular utilizado generalmente para realizar análisis estadísticos alrededor del mundo y amigable con la construcción de código para los usuarios.

Este curso se centra en la construcción de proyectos de ciencias de datos relevantes para los negocios de la nueva era digital. Todas las actividades y ejercicios se desarrollarán en lenguaje R, utilizando RStudio.

Te guiaremos paso a paso para que desarrolles y entiendas las diferentes herramientas que nos ofrece R para aplicarlas a proyectos de ciencia de datos que se implementa específicamente en los negocios de la era digital. Desarrollaremos prácticas que te ayuden a incrementar tus habilidades en la construcción de software y el análisis de datos.

Al finalizar este curso contarás con un portafolio de trabajos en ciencias de datos que te ayudará a demostrar tus conocimientos en el tema. Además, lograrás implementar proyectos de ciencias de datos aplicados a las problemáticas laborales en los negocios.

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What's inside

Learning objectives

Desarrollar un sistema de recomendación de productos mediante la preparación y análisis de datos
Construir un sistema de evaluación de la puntuación crediticia mediante algoritmos en r

Implementar análisis automático para definir costos en tiempo real
Generar código en r para detectar fraudes crediticios

Desarrollar un sistema de recomendación de productos mediante la preparación y análisis de datos
Construir un sistema de evaluación de la puntuación crediticia mediante algoritmos en r
Implementar análisis automático para definir costos en tiempo real
Generar código en r para detectar fraudes crediticios

Syllabus

Módulo 1. Desarrollo de sistema de recomendación de producto

Aprenderás diferentes técnicas de limpieza de datos, así como a diferencias los diferentes tipos de sistemas de recomendación. Analizarás los datos utilizando métodos exploratorios y seleccionarás el tipo de sistema de recomendación que mejor se adapte a los datos.

Módulo 2. Desarrollo de un sistema para la detección de fraudes

Identificarás los diferentes tipos de sistemas de detección de fraudes y sus aplicaciones. Además, seleccionarás y desarrollarás el modelo a aplicar con base en los datos y evaluarás las mejores métricas para aplicar según el sistema que se desarrolle.

Módulo 3. Desarrollo de modelo de puntaje crediticio

Desarrollarás técnicas de creación de modelos logísticos para identificar clientes válidos para un préstamo y validarás modelos mediante las técnicas de análisis de ROC.

Módulo 4. Desarrollo de modelo para predecir costos

Aplicarás el método de regresión lineal para predecir los costos a establecer en periodos futuros y validarás tus modelos mediante la técnica de la raíz media cuadrática (RMS) para verificar la calidad de tu modelo.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Desarrolla habilidades prácticas mediante el uso de RStudio

Brinda una base sólida para la ciencia de datos en los negocios

Está dirigido específicamente a profesionales de negocios

Cuenta con un portafolio de proyectos de ciencias de datos para demostrar habilidades

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Save Aplicaciones de ciencias de datos en los negocios actuales to your list so you can find it easily later:

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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 Aplicaciones de ciencias de datos en los negocios actuales with these activities:

Review basic probability and statistics

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Understand basic probability and statistics which are fundamental for doing Data Science projects.

Browse courses on Probability and Statistics

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Review basic probability concepts such as conditional probability, Bayes' theorem, and independence.
Review basic statistical concepts such as mean, median, standard deviation, and confidence intervals.

Practice coding in R

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Improve coding skills and become more comfortable with R programming basics.

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Find online coding challenges or exercises.
Code the solutions to the challenges using R.
Review your solutions and identify areas for improvement.
Repeat the process regularly to improve your skills.

Organize and review your course materials

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Organizing and reviewing your materials will enhance your understanding and retention.

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Gather all your lecture notes, assignments, and readings
Organize the materials by topic or module
Review the materials regularly and take notes or highlight important concepts

Seven other activities

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Participate in study groups or online forums

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Engaging with peers can help reinforce your understanding, provide support, and expose you to different perspectives.

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Find study groups or online forums related to data science
Actively participate in discussions, ask questions, and share your insights
Collaborate with others on projects or assignments

Build a simple data wrangling pipeline

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Practice wrangling real-world data to gain hands-on experience.

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Find a dataset that interests you and download it.
Use R to load the dataset into a data frame.
Explore the data frame using functions like head(), tail(), and summary().
Clean the data by removing duplicate rows, handling missing values, and converting data types.
Save the cleaned data to a new file.

Practice data cleaning and manipulation in R

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Practicing data cleaning and manipulation will improve your proficiency in handling and preparing data for analysis, which is essential for data science projects.

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Find a dataset and import it into R
Identify and correct errors or missing values in the data
Transform and reshape the data as needed for analysis

Learn about different algorithms for data analysis

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Understanding different algorithms will broaden your knowledge and equip you with the tools to tackle a wider range of data analysis tasks.

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Search for tutorials or courses on data analysis algorithms
Choose a few algorithms to focus on and learn about their strengths and weaknesses
Implement the algorithms in R and experiment with them on different datasets

Create a data visualization dashboard

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Develop skills in creating interactive visualizations that communicate insights from data.

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Choose a dataset that you're interested in visualizing.
Use R to create a variety of visualizations, such as bar charts, line charts, and scatterplots.
Organize the visualizations into a cohesive dashboard using R Shiny or another tool.
Share your dashboard with others and get feedback.

Develop a data visualization dashboard for a business problem

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Creating a data visualization dashboard will allow you to apply your skills in data analysis, visualization, and communication to solve a real-world business problem.

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Identify a business problem that can be addressed with data visualization
Gather and analyze the relevant data
Design and develop the dashboard using R and appropriate visualization tools
Present and communicate your findings to stakeholders

Write a blog post or article on a data science topic

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Creating content will deepen your understanding of the topic and improve your communication skills.

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Choose a specific aspect of data science that you want to write about
Research and gather information from credible sources
Write and edit your blog post or article, ensuring clarity and accuracy
Publish and promote your content

Career center

Learners who complete Aplicaciones de ciencias de datos en los negocios actuales will develop knowledge and skills that may be useful to these careers:

Data Analyst

Data Analysts collect, clean, and analyze data to help organizations make informed decisions. They use their skills in data analysis, statistics, and programming to identify trends, patterns, and insights in data. This course can help you develop the skills you need to become a successful Data Analyst. You will learn how to use R to prepare and analyze data, develop visualizations, and build models.

See salaries and explore the career path for Data Analyst

Statistician

Statisticians collect, analyze, and interpret data to provide insights into various fields. They use their skills in statistics, mathematics, and programming to develop models that can help organizations make informed decisions. This course can help you develop the skills you need to become a successful Statistician. You will learn how to use R to prepare and analyze data, develop models, and communicate your findings to stakeholders.

See salaries and explore the career path for Statistician

Quantitative Analyst

Quantitative Analysts use their skills in mathematics, statistics, and programming to analyze financial data and develop investment strategies. They use their models to predict future trends and outcomes. This course can help you develop the skills you need to become a successful Quantitative Analyst. You will learn how to use R to prepare and analyze data, develop models, and evaluate their performance.

See salaries and explore the career path for Quantitative Analyst

Data Scientist

Data Scientists use their skills in data analysis, statistics, and programming to build models that can predict future trends and outcomes. They use these models to help organizations make better decisions. This course can help you develop the skills you need to become a successful Data Scientist. You will learn how to use R to prepare and analyze data, build models, and evaluate their performance.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

Machine Learning Engineers design, develop, and deploy machine learning models. They use their skills in data analysis, statistics, and programming to build models that can learn from data and make predictions. This course can help you develop the skills you need to become a successful Machine Learning Engineer. You will learn how to use R to prepare and analyze data, build models, and evaluate their performance.

See salaries and explore the career path for Machine Learning Engineer

Financial Analyst

Financial Analysts use their skills in finance, accounting, and data analysis to evaluate investment opportunities and make recommendations to clients. They use their knowledge of financial markets and their ability to analyze data to help clients make informed investment decisions. This course can help you develop the skills you need to become a successful Financial Analyst. You will learn how to use R to prepare and analyze financial data, develop models, and evaluate investments.

See salaries and explore the career path for Financial Analyst

Consultant

Consultants provide advice and guidance to organizations on a variety of topics, including data analysis, strategy, and operations. They use their skills in problem-solving, communication, and presentation to help organizations improve their performance. This course can help you develop the skills you need to become a successful Consultant. You will learn how to use R to prepare and analyze data, develop recommendations, and communicate your findings to stakeholders.

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Data Engineer

Data Engineers build and maintain data pipelines that can collect, clean, and transform data. They use their skills in data engineering, programming, and cloud computing to build pipelines that can meet the needs of organizations. This course can help you develop the skills you need to become a successful Data Engineer. You will learn how to use R to build and maintain data pipelines that can handle the challenges of big data.

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Business Intelligence Analyst

Business Intelligence Analysts use data analysis techniques to provide insights into business operations. They use their skills in data analysis, visualization, and reporting to develop reports and dashboards that can help organizations make better decisions. This course can help you develop the skills you need to become a successful Business Intelligence Analyst. You will learn how to use R to prepare and analyze data, develop visualizations, and build models.

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Business Analyst

Business Analysts help organizations make better decisions by providing data-driven insights. They use data analysis techniques to understand business problems and develop solutions. This course can help you develop the skills you need to become a successful Business Analyst. You will learn how to prepare and analyze data, develop recommendations, and communicate your findings to stakeholders. Also, the use of R in real-life business scenarios.

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Operations Research Analyst

Operations Research Analysts use mathematical and analytical techniques to solve complex problems in a variety of industries. They use their skills in optimization, simulation, and modeling to develop solutions that can help organizations improve their efficiency and effectiveness. This course can help you develop the skills you need to become a successful Operations Research Analyst. You will learn how to use R to prepare and analyze data, develop models, and evaluate solutions.

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Data Architect

Data Architects design and build data management systems that can store, process, and analyze large amounts of data. They use their skills in data modeling, database design, and programming to build systems that meet the needs of organizations. This course can help you develop the skills you need to become a successful Data Architect. You will learn how to use R to design and build data management systems that can handle the challenges of big data.

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Software Engineer

Software Engineers design, develop, and maintain software applications. They use their skills in programming, data structures, and algorithms to build software that meets the needs of users. This course can help you develop the skills you need to become a successful Software Engineer. You will learn how to use R to develop software applications that can analyze data and solve business problems.

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Risk Analyst

Risk Analysts identify, assess, and mitigate risks to organizations. They use their skills in risk management, data analysis, and modeling to develop risk management plans that can help organizations protect their assets and reputation. This course can help you develop the skills you need to become a successful Risk Analyst. You will learn how to use R to prepare and analyze data, develop models, and evaluate risks.

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Project Manager

Project Managers plan, execute, and control projects to ensure their successful completion. They use their skills in project management, communication, and leadership to manage projects that meet the needs of stakeholders. This course may be useful for developing the skills needed to use R for data analysis and reporting on project progress and outcomes.

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Reading list

We've selected 13 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Aplicaciones de ciencias de datos en los negocios actuales.

R for Data Science

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Este libro es un recurso integral para el análisis de datos con R. Cubre una amplia gama de temas, desde el modelado lineal hasta el aprendizaje automático.

Aplicaciones de ciencias de datos en los negocios actuales

What's inside

Learning objectives

Syllabus

Good to know

Save this course

Activities

Career center

Reading list

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