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5.0 /5
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Bienvenidos a nuestro curso de Data Science aplicado a Negocios
Introducción al curso
Cómo sacarle el máximo partido al curso
Trucos clave y mejores prácticas
El temario del curso y estrategias clave de aprendizaje
Cómo clonar los datos para seguir el curso
Toma notas de tu curso en tiempo real en Frogames Formación
Introducción al caso práctico y objetivos clave de aprendizaje
Tarea 1: Entender el problema enunciado y la empresa analizada
Tarea 2: Importar las librerías y los datasets
Tarea 3: Explorar el dataset - Parte 1
Tarea 3: Explorar el dataset - Parte 2
Tarea 3: Explorar el dataset - Parte 3
Tarea 3: Explorar el dataset - Parte 4
Tarea 4: La limpieza de los datos
Tarea 5: Entender la teoría de Random Forest, Regresión Logística y Redes Neuronales
Tarea 6: Entender los KPIs
Tarea 7: Construir y entrenar un clasificador basado en la regresión logística
Tarea 8: Construir y entrenar un clasificador usando Random Forest
Tarea 9: Construir y entrenar un clasificador usando Redes Neuronales Artificiales
Introducción al caso práctico y objetivos claves de aprendizaje
Tarea 1: Entender el problema enunciado y la empresa analizada
Tarea 2: Importar las librerías y los datasets
Tarea 3: Llevar a cabo la visualización de los datos
Tarea 4: Entender la teoría detrás del algoritmo de K-Means
Tarea 5: Encontrar el número óptimo de clusters utilizando la técnica del codo
Tarea 6: Aplicar el clustering con K-Means para segmentar el mercado
Tarea 7: Entender la teoría detrás del análisis de componentes principales
Tarea 8: Entender la teoría detrás de los auto encoders
Tarea 9: Construir y entrenar un auto encoder - Parte 1
Tarea 10: Construir y entrenar un auto encoder - Parte 2
Introducción al caso práctico y objetivos claves de aprendizaje
Tarea 1: Entender el problema enunciado y la empresa analizada
Tarea 2: Importar las librerías y los datasets - Parte 1
Tarea 2: Importar las librerías y los datasets - Parte 2
Tarea 3: Análisis exploratorio de los datos - Parte 1
Tarea 3: Análisis exploratorio de los datos - Parte 2
Tarea 3: Análisis exploratorio de los datos - Parte 3
Tarea 3: Análisis exploratorio de los datos - Parte 4
Tarea 4: Entender la teoría de Facebook Prophet
Tarea 5: Entrenar el modelo - Parte 1
Tarea 5: Entrenar el modelo - Parte 2
Introducción al caso práctico y objetivos claves de aprendizaje
Tarea 1: Entender el problema enunciado y la empresa analizada
Tarea 2: Cargar y explorar el dataset
Tarea 3: Visualización de los datos
Tarea 4: Entender la teoría detrás de las redes neuronales
Tarea 5: Entender la teoría detrás del aprendizaje por transferencia
Tarea 6: Cargar un modelo con pesos pre entrenados
Tarea 7: Construir y entrenar una ResNet
Tarea 8: Evaluar la eficacia del modelo entrenado
Introducción al caso práctico y objetivos claves de aprendizaje
Tarea 1: Entender el problema enunciado y la empresa analizada
Tarea 2: Importar las librerías y los datasets
Tarea 3: Análisis exploratorio de los datos - Parte 1
Tarea 3: Análisis exploratorio de los datos - Parte 2
Tarea 4: Llevar a cabo la limpieza de los datos
Tarea 5: Eliminar los signos de puntuación
Tarea 6: Eliminar las stopwords
Tarea 7: Llevar a cabo la tokenización y vectorización de las palabras
Tarea 8: Ejecutar el flujo de limpieza de texto
Tarea 9: Idea intuitiva de Naive Bayes
Tarea 10: Entrenar un clasificador con Naive Bayes
Tarea 11: Evaluar el clasificador Naive Bayes entrenado
Tarea 12: Entrenar y evaluar un clasificador utilizando regresión logística
Introducción al caso práctico y objetivos claves de aprendizaje
Tarea 1: Entender el problema enunciado y la empresa analizada
Tarea 2: Importar las librerías y los datasets
Tarea 3: Visualización y exploración inicial de los datos
Tarea 4: Entender la teoría del ResNet, RNC y aprendizaje por transferencia
Tarea 5: Construir y entrenar clasificadores ResNet
Tarea 6: Evaluar la calidad del modelo ResNet entrenado
Tarea 7: Entender la idea detrás del modelo de segmentación ResUNet
Tarea 8: Construir y entrenar un modelo de segmentación ResUNet
Tarea 9: Evaluar la calidad del modelo ResUNet entrenado
Bonus 1 - El libro resumen del curso
Bonus 2 - Un caso práctico adicional
Bonus 3 - 3 proyectos top para iniciar tu carrera como científico de datos
Enhorabuena por completar el curso de Machine Learning de la A a la Z

instructor

5.0 /5
(25)

  • Avatar
    Giovanni
    (5)
    Corporate and practical approach

    Learning to make decisions based on real data has given me a huge competitive advantage and a much more analytical view of how to optimize business processes

  • Avatar
    Joiser
    (5)
    I love courses like this, so practical

    I feel that practice makes the master, and definitely here at Frogames they understand that, that's why I love their courses, so practical with the instructors guiding you

  • Avatar
    Nieves
    (5)
    Data Science Applied to Business 6 Real-World Case Studies: transform data into strategic decisions

    This course teaches you how to solve real business problems using data science techniques, artificial intelligence, and machine learning. Through six practical cases, you'll learn to build predictive models to reduce employee turnover, optimize medical diagnoses, predict prices, detect defects, analyze sentiment on social media, and segment customers for marketing.

  • Avatar
    danison
    (5)
    Data Science that transforms businesses

    I learned how to solve business problems with Data Science, from sales forecasting to operations optimization—incredibly useful stuff. I'm sure I'll apply every lesson in my daily work

  • Avatar
    Jorge
    (5)
    I finally see the value of data

    We're often taught the theory but not how to apply it, and seeing six real business problems broken down here made me understand how my analyses impact a company's profitability. It's exactly what I was looking for to improve my professional profile.

  • Avatar
    Javi
    (5)
    Very useful for everyday

    I really liked that they use examples that actually happen in companies, so you don't feel like you're wasting time on boring theory. It helps you spot opportunities where you used to just see a bunch of numbers that meant nothing. It's a great tool for understanding how everything works better.

  • Avatar
    Santiago
    (5)
    High-quality content

  • Avatar
    Rosa
    (5)
    Real case studies give you a different perspective than just having theory explained to you

  • Avatar
    Angel
    (5)
    Data Science aplicado a Negocios | 6 Casos de Estudio Reales

    This course is designed for those who want to apply data science in real business contexts. Through six practical cases, you'll learn to develop Machine Learning, Deep Learning, and natural language processing (NLP) models to solve concrete problems in areas like human resources, health, marketing, and logistics.

  • Avatar
    Rocío
    (5)
    shows you how to apply data science techniques directly to real business problems.

  • Avatar
    María
    (5)
    Real case studies are amazing

    It helped me see how to apply data science in my daily work and now I make more informed decisions. It's a course that opens your eyes and gives you real tools for the working world

  • Avatar
    Sara
    (5)
    Learn with real examples

  • Avatar
    Jackeline
    (5)
    .

    Each case study was like opening a window to a real problem

  • Avatar
    Gustavo
    (5)
    Data Science Applied to Business: Strategy, Analysis and Real Results

    The Data Science Applied to Business course with 6 Real Case Studies is a true immersion into the transformative power of data when aligned with concrete business objectives. What makes it stand out isn't just technical quality, but its practical and strategic approach: each case study is based on real situations that let you understand how data analysis directly impacts decision-making.

  • Avatar
    Samuel
    (5)
    Now I can analyze company data and make better decisions

    I never thought data science could be so practical and useful for my business. It changed the way I look at data.

  • Avatar
    Gabriela
    (5)
    Highly recommended, very professional

    Through 6 case studies, I learned how to solve real problems and communicate insights clearly. It was like gaining work experience in less time.

  • Avatar
    ivan sergio
    (5)
    Wow...

    "Excellent course, very well explained and, above all, very practical."

  • Avatar
    Carlos
    (5)
    Expert instructors in the field

    I took the Applied Data Science for Business course, and I have to say it exceeded my expectations in many ways. From the first module, I realized that this course doesn't just focus on theory, but also offers practical application through six real case studies that are truly relevant to today's business world.

  • Avatar
    Caty
    (5)
    very good teaching methodology

    To keep growing with the applied fundamentals

  • Avatar
    Marc
    (5)
    So happy!

    A really useful course that I loved

  • Avatar
    Alvaro
    (5)
    Bacano

    Cool (nice) and useful

  • Avatar
    Jesus
    (5)
    Excellent!

    Perfect if you've completed the Machine Learning from A to Z course, since it revisits algorithms you've already seen but this time with real-world cases. Learning becomes easier with examples. Congratulations on the course!!!

  • Avatar
    Yeison
    (5)
    Excellent practical course

    This course helps you apply all the Data Science concepts covered in previous courses, with real-world scenarios. The result is excellent

  • Avatar
    Joel
    (5)
    Recommended Course

    A really complete course where you put all the concepts you've learned into practice, and the best part is that it applies to real cases, which helps your professional life. The best course, 100% recommended

  • Avatar
    BORJA
    (5)
    Excellent

    A really interesting course with amazing examples.

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Path of Data Analysis

The ultimate pack with all our Data Analysis courses with R and Python to turn you into a well-paid Data Scientist. Includes upcoming courses and updates and improvements to current ones

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Databases: Learn SQL from scratch

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