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Sandip Saha Joy, Ramesh Sannareddy, and Rav Ahuja
En este curso se aplicarán diversas habilidades y técnicas de Data Analytics que ha aprendido como parte de los cursos anteriores del Certificado Profesional de IBM Data Analyst. Asumirá el papel de Analista de datos asociado que se ha incorporado...
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En este curso se aplicarán diversas habilidades y técnicas de Data Analytics que ha aprendido como parte de los cursos anteriores del Certificado Profesional de IBM Data Analyst. Asumirá el papel de Analista de datos asociado que se ha incorporado recientemente a la organización y se enfrentará a un reto empresarial que requiere que el análisis de datos se realice en conjuntos de datos del mundo real. Se encargará de las tareas de recoger datos de múltiples fuentes, realizar análisis de datos exploratorios, la preparación y discusión de datos, el análisis estadístico y la extracción de datos, la creación de gráficos y diagramas para visualizar los datos, y la construcción de un tablero interactivo. El proyecto culminará con la presentación de su informe de análisis de datos, con un resumen ejecutivo para los diversos interesados en la organización. Se evaluará tanto su trabajo en las diversas etapas del proceso de análisis de datos como el producto final. Este proyecto es una gran oportunidad para mostrar sus habilidades de análisis de datos, y demostrar su competencia a los posibles empleadores.
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Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Explores Data Analytics skills and techniques in the context of real-world datasets
Guided by experienced instructors Rav Ahuja, Sandip Saha Joy, and Ramesh Sannareddy
Provides practical experience in applying Data Analytics to solve business challenges
Covers various stages of the Data Analytics process, from data collection to visualization
Involves the creation of an interactive dashboard to showcase analysis results
Culminates in a comprehensive analysis report, demonstrating proficiency in data analysis

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Reviews summary

Spanish capstone data analytics project

This course is a capstone project for the IBM Data Analytics Professional Certificate. It is recommended that students take the English version of this course. Students mentioned that this course was good or very good, with clear topics and good audiovisual aids. However, some students complained about outdated content, lack of instructor support, and technical issues with the course platform.
Good audiovisual aids
"Excelente curso, los temas muy claros, las ayudas audiovisuales son excelentes, gracias"
Clear topics
"Excelente curso, los temas muy claros, las ayudas audiovisuales son excelentes, gracias"
Outdated course content
"...faltaria actualizar algunos contenidos en relacion a las herramientas que se usan, y quiza mas ejemplos..."
No instructor support
"U​n asco todo el curso definitivamente, no tienes soporte de ningun instructor, ni siquiera te puedes contactar con ellos."
Technical issues with course platform
"En cada modulo tienes un problema diferente, no cargan las actividades, los archivos no estan, la plataforma de IBM cloud tambien es un problema..."

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 Proyecto Final de Analítica de Datos with these activities:
Review previous coursework or study materials on related topics
Refreshing your knowledge on foundational topics will help you better grasp the concepts covered in this course.
Browse courses on Data Analytics
Show steps
  • Identify relevant coursework or study materials.
  • Review key concepts and principles.
Read 'Data Analytics with Python' by Anil Maheshwari
This book provides a comprehensive overview of data analytics techniques and their implementation using Python, reinforcing your understanding of the concepts covered in the course.
Show steps
  • Read Chapters 1-3 to understand the fundamentals of data analytics.
  • Review the code examples and practice exercises to solidify your understanding of Python programming for data analysis.
Attend a study group or online discussion forum
Engaging in peer discussions helps you clarify concepts, identify gaps in your understanding, and broaden your perspectives.
Browse courses on Data Analytics
Show steps
  • Find a suitable study group or online forum.
  • Participate actively in discussions and ask questions.
  • Share your knowledge and insights with others.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Watch online tutorials on specific data analysis techniques
Tutorials provide step-by-step guidance on how to implement specific data analysis techniques, enhancing your practical skills.
Browse courses on Data Analytics
Show steps
  • Identify topics or techniques you need to strengthen.
  • Search for suitable tutorials online or on platforms like Coursera.
  • Watch the tutorials and try out the examples.
Complete Kaggle's Titanic: Machine Learning from Disaster competition
This competition provides a practical platform to apply your data analysis and machine learning skills, enhancing your understanding of the course material.
Browse courses on Machine Learning
Show steps
  • Explore the dataset and preprocess the data.
  • Train and evaluate different machine learning models.
  • Submit your predictions and analyze your results.
Write a blog post summarizing a key concept or technique covered in the course
Explaining concepts to others helps solidify your understanding and enhances your ability to communicate technical ideas.
Browse courses on Data Analytics
Show steps
  • Choose a concept or technique to focus on.
  • Research and gather information.
  • Write a clear and concise blog post.
  • Share your blog post with others.
Develop a data analytics dashboard for a real-world organization
This project allows you to apply your data analytics skills to a realistic scenario, showcasing your ability to present insights effectively.
Browse courses on Data Visualization
Show steps
  • Define the problem statement and identify relevant data sources.
  • Clean and prepare the data for analysis.
  • Perform exploratory data analysis and identify key insights.
  • Design and develop the data visualization dashboard.
  • Present your findings and recommendations.

Career center

Learners who complete Proyecto Final de Analítica de Datos will develop knowledge and skills that may be useful to these careers:
Data Analyst
The Proyecto Final de Analítica de Datos course from IBM Skills Network is the perfect resource for aspiring or current Data Analysts. Throughout the course, you will apply various skills and techniques in data analytics, including data collection, exploratory data analysis, data preparation and discussion, statistical analysis and data mining, data visualization, and interactive dashboard construction. This hands-on experience will provide you with the skills and knowledge necessary to succeed in the field of data analytics.
Data Scientist
As a Data Scientist, you will use your expertise in data analysis, machine learning, and statistical modeling to extract insights from large datasets. The Proyecto Final de Analítica de Datos course will provide you with the foundational skills you need to succeed in this role, including data collection, exploratory data analysis, data preparation and discussion, statistical analysis and data mining, data visualization, and interactive dashboard construction.
Business Analyst
Business Analysts use data analysis to identify and solve business problems. The Proyecto Final de Analítica de Datos course will provide you with the skills you need to succeed in this role, including data collection, exploratory data analysis, data preparation and discussion, statistical analysis and data mining, data visualization, and interactive dashboard construction.
Market Researcher
Market Researchers use data analysis to understand consumer behavior and market trends. The Proyecto Final de Analítica de Datos course will provide you with the skills you need to succeed in this role, including data collection, exploratory data analysis, data preparation and discussion, statistical analysis and data mining, data visualization, and interactive dashboard construction.
Operations Research Analyst
Operations Research Analysts use data analysis to improve the efficiency and effectiveness of business operations. The Proyecto Final de Analítica de Datos course will provide you with the skills you need to succeed in this role, including data collection, exploratory data analysis, data preparation and discussion, statistical analysis and data mining, and interactive dashboard construction.
Quantitative Analyst
Quantitative Analysts use data analysis to develop and implement financial models. The Proyecto Final de Analítica de Datos course will provide you with the skills you need to succeed in this role, including data collection, exploratory data analysis, data preparation and discussion, statistical analysis and data mining, and interactive dashboard construction.
Statistician
Statisticians use data analysis to collect, analyze, interpret, and present data. The Proyecto Final de Analítica de Datos course will provide you with the skills you need to succeed in this role, including data collection, exploratory data analysis, data preparation and discussion, statistical analysis and data mining, data visualization, and interactive dashboard construction.
Data Engineer
Data Engineers design, build, and maintain data pipelines and infrastructure. The Proyecto Final de Analítica de Datos course will provide you with the skills you need to succeed in this role, including data collection, data preparation and discussion, and interactive dashboard construction.
Machine Learning Engineer
Machine Learning Engineers design, build, and deploy machine learning models. The Proyecto Final de Analítica de Datos course will provide you with the skills you need to succeed in this role, including data collection, exploratory data analysis, data preparation and discussion, data visualization, and interactive dashboard construction.
Software Engineer
Software Engineers design, build, and maintain software systems. The Proyecto Final de Analítica de Datos course may be useful for aspiring Software Engineers who want to develop data analysis applications.
Database Administrator
Database Administrators design, build, and maintain databases. The Proyecto Final de Analítica de Datos course may be useful for aspiring Database Administrators who want to develop data analysis applications.
Data Architect
Data Architects design and build data architectures. The Proyecto Final de Analítica de Datos course may be useful for aspiring Data Architects who want to develop data analysis applications.
Information Security Analyst
Information Security Analysts protect computer systems and networks from unauthorized access. The Proyecto Final de Analítica de Datos course may be useful for aspiring Information Security Analysts who want to develop data analysis applications for security purposes.
Computer Systems Analyst
Computer Systems Analysts design, build, and maintain computer systems. The Proyecto Final de Analítica de Datos course may be useful for aspiring Computer Systems Analysts who want to develop data analysis applications.
Web Developer
Web Developers design, build, and maintain websites. The Proyecto Final de Analítica de Datos course may be useful for aspiring Web Developers who want to develop data analysis applications for the web.

Reading list

We've selected ten 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 Proyecto Final de Analítica de Datos.
Provides a comprehensive overview of deep learning, including convolutional neural networks, recurrent neural networks, and generative adversarial networks. It good resource for those who want to learn about the latest advances in deep learning.
Provides a comprehensive overview of statistical methods for data analysis, including descriptive statistics, inferential statistics, and regression analysis. It good resource for those who want to learn about the latest advances in statistical methods.
Provides a practical introduction to data visualization, including how to choose the right charts and graphs for your data, how to create effective visualizations, and how to communicate your findings to others. It good resource for those who want to learn how to create effective data visualizations.
Provides a comprehensive overview of Python for data analysis, including data manipulation, data visualization, and machine learning. It good resource for those who want to learn how to use Python for data analytics.
Provides a comprehensive overview of R for data science, including data manipulation, data visualization, and machine learning. It good resource for those who want to learn how to use R for data analytics.
Provides a comprehensive overview of SQL for data analysis, including data querying, data manipulation, and data analysis. It good resource for those who want to learn how to use SQL for data analytics.
Provides a comprehensive overview of NoSQL for data analysis, including data modeling, data storage, and data querying. It good resource for those who want to learn how to use NoSQL for data analytics.
Provides a comprehensive overview of big data analytics, including data collection, data storage, data processing, and data analysis. It good resource for those who want to learn how to use big data for data analytics.
Provides a practical guide to data science for business professionals. It covers topics such as data mining, machine learning, and statistical analysis. It good resource for those who want to learn how to use data to make better business decisions.

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