Coursera Project Network
Series temporales con Deep Learning (RNN, LSTM) y Prophet
Coursera Project Network

Series temporales con Deep Learning (RNN, LSTM) y Prophet

Taught in Spanish

Leire Ahedo

Instructor: Leire Ahedo

Included with Coursera Plus

Guided Project

Learn, practice, and apply job-ready skills with expert guidance

Intermediate level

Recommended experience

2 horas
Learn at your own pace
No downloads or installation required
Only available on desktop
Hands-on learning
4.5

(15 reviews)

What you'll learn

  • Entrenar y optimizar una red neuronal recurrente (RNN y LSTM)

  • Predecir series temporales con Facebook' Prophet

  • Predecir datos futuros con modelos de series temporales

Details to know

Shareable certificate

Add to your LinkedIn profile

Guided Project

Learn, practice, and apply job-ready skills with expert guidance

Intermediate level

Recommended experience

2 horas
Learn at your own pace
No downloads or installation required
Only available on desktop
Hands-on learning
4.5

(15 reviews)

See how employees at top companies are mastering in-demand skills

Placeholder

Learn, practice, and apply job-ready skills in less than 2 hours

  • Receive training from industry experts
  • Gain hands-on experience solving real-world job tasks
  • Build confidence using the latest tools and technologies
Placeholder

About this Guided Project

Learn step-by-step

In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

  1. Introducción a las series temporales

  2. Fundamentos de Redes Neuronales Recurrentes (RNN y LSTM)

  3. Funciones básicas con Keras

  4. Pre-procesamiento de datos y entrenamiento del modelo LSTM

  5. Ejercicio práctico. Desarrollo de un modelo LSTM

  6. Evaluación del modelo y predicciones

  7. Ejercicio práctico. Evaluación del modelo y predicción

  8. Desarrollo de un modelo avanzado de LSTM

  9. Ejercicio práctico. Modelo avanzado de LSTM

  10. Predicción con nuevos datos y despliegue del modelo

  11. Ejercicio práctico. Evaluación y puesta en producción de la red LSTM

  12. Series temporales con Prophet

Recommended experience

Python

7 project images

Instructor

Leire Ahedo
Coursera Project Network
68 Courses35,757 learners

Offered by

How you'll learn

  • Skill-based, hands-on learning

    Practice new skills by completing job-related tasks.

  • Expert guidance

    Follow along with pre-recorded videos from experts using a unique side-by-side interface.

  • No downloads or installation required

    Access the tools and resources you need in a pre-configured cloud workspace.

  • Available only on desktop

    This Guided Project is designed for laptops or desktop computers with a reliable Internet connection, not mobile devices.

Why people choose Coursera for their career

Felipe M.
Learner since 2018
"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."
Jennifer J.
Learner since 2020
"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."
Larry W.
Learner since 2021
"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."
Chaitanya A.
"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."

Learner reviews

Showing 3 of 15

4.5

15 reviews

  • 5 stars

    73.33%

  • 4 stars

    20%

  • 3 stars

    0%

  • 2 stars

    0%

  • 1 star

    6.66%

AR
5

Reviewed on Mar 24, 2022

New to Machine Learning? Start here.

Placeholder

Open new doors with Coursera Plus

Unlimited access to 7,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription

Advance your career with an online degree

Earn a degree from world-class universities - 100% online

Join over 3,400 global companies that choose Coursera for Business

Upskill your employees to excel in the digital economy

Frequently asked questions