Fundamentos de Ciencia de Datos y Aprendizaje Automático

Resumen

Data Science & Machine Learning Fundamentals Course Overview Data science is about using statistics to draw insights from data to drive action and improve business performance. This course will guide you through the world of data science and machine learning, using applied examples to demonstrate real-world applications.

Whether you’re an aspiring data scientist or a c-level exec, this course will bring you up to speed on everything data science. You’ll be introduced to machine learning, classification, exploratory data analysis, feature selection, and feature engineering—what they mean and how they are relevant to your business.

We’ll start by defining the skills, tools, and roles behind data science that work together to create insights. We’ll then walk through regression and classification—the most common predictive and statistical techniques.

Finally, you will understand why having a basic understanding of data science outputs is essential to all business stakeholders and how we can use those outputs to make business decisions. Data Science & Machine Learning Fundamentals Learning Objectives Upon completing this course, you will be able to:

Distinguish data science from business intelligenceOutline the data science and machine learning processDescribe basic data science terms, roles, skills, and applicationsDistinguish popular models used for data science and machine learningIdentify common data preparation steps to better understand your data, better structure your data, and remove errorsEvaluate model resultsWho should take this course?

Whether you are a business leader or an aspiring analyst exploring data science, this Data Science & Machine Learning Fundamentals course will serve as your comprehensive introduction to this fascinating subject. You’ll learn all the key terminology to allow you to talk data science with your teams, begin implementing analysis, and understand how data science can help your business.

Programa

• Introducción
• Fundamentos de la Ciencia de Datos
• Regresión
• Clasificación
• Liderazgo en Ciencia de Datos
• Preparación de Datos
• Otros Tipos de Análisis
• Conclusión del Curso
• Evaluación Calificada

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Impartido por

Sebastian Taylor and Lester Leong

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Materias

Data Science