Acerca de este Curso

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Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Nivel intermedio
Aprox. 7 horas para completar
Inglés (English)
Subtítulos: Inglés (English)
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Nivel intermedio
Aprox. 7 horas para completar
Inglés (English)
Subtítulos: Inglés (English)

ofrecido por

Logotipo de Universidad de California en San Diego

Universidad de California en San Diego

Programa - Qué aprenderás en este curso

Semana
1

Semana 1

2 horas para completar

Week 1: Supervised Learning & Regression

2 horas para completar
5 videos (Total 46 minutos), 4 lecturas, 3 cuestionarios
5 videos
Supervised Learning: Regression9m
Regression in Python10m
Time-Series Regression8m
Autoregression6m
4 lecturas
Syllabus10m
Course Materials10m
Set Up Your System10m
Recap: Mathematical Notation10m
3 ejercicios de práctica
Review: Supervised Learning4m
Review: Regression4m
Supervised Learning & Regression10m
Semana
2

Semana 2

1 hora para completar

Week 2: Features

1 hora para completar
4 videos (Total 29 minutos), 1 lectura, 3 cuestionarios
4 videos
Features from Temporal Data8m
Feature Transformations4m
Missing Values7m
1 lectura
Supplementary Notebook for Features3m
3 ejercicios de práctica
Review: Getting Features
Review: Working with Features
Features10m
Semana
3

Semana 3

1 hora para completar

Week 3: Classification

1 hora para completar
4 videos (Total 31 minutos)
4 videos
Classification: Nearest Neighbors4m
Classification: Logistic Regression10m
Introduction to Support Vector Machines10m
3 ejercicios de práctica
Review: Classification and K-Nearest Neighbors6m
Review: Logistic Regression and Support Vector Machines5m
Classification10m
Semana
4

Semana 4

1 hora para completar

Week 4: Gradient Descent

1 hora para completar
5 videos (Total 36 minutos)
5 videos
Introduction to Training and Testing6m
Gradient Descent in Python8m
Gradient Descent in TensorFlow6m
Livecoding: Tensorflow7m
3 ejercicios de práctica
Review: Classification and Training4m
Review: Gradient Descent4m
More on Classification15m

Acerca de Programa especializado: Python Data Products for Predictive Analytics

Python data products are powering the AI revolution. Top companies like Google, Facebook, and Netflix use predictive analytics to improve the products and services we use every day. Take your Python skills to the next level and learn to make accurate predictions with data-driven systems and deploy machine learning models with this four-course Specialization from UC San Diego. This Specialization is for learners who are proficient with the basics of Python. You’ll start by creating your first data strategy. You’ll also develop statistical models, devise data-driven workflows, and learn to make meaningful predictions for a wide-range of business and research purposes. Finally, you’ll use design thinking methodology and data science techniques to extract insights from a wide range of data sources. This is your chance to master one of the technology industry’s most in-demand skills. Python Data Products for Predictive Analytics is taught by Professor Ilkay Altintas, Ph.D. and Julian McAuley. Dr. Alintas is a prominent figure in the data science community and the designer of the highly-popular Big Data Specialization on Coursera. She has helped educate hundreds of thousands of learners on how to unlock value from massive datasets....
Python Data Products for Predictive Analytics

Preguntas Frecuentes

  • Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:

    • The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.

    • The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

  • If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.

  • Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.

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