Acerca de este Curso
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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

B​asic knowledge of programming (any language)

Aprox. 16 horas para completar

Sugerido: 7 hours/week...

Inglés (English)

Subtítulos: Inglés (English)

Qué aprenderás

  • Check

    Develop data strategy and process for how data will be generated, collected, and consumed

  • Check

    Load and process formatted datasets such as CSV and JSON.

  • Check

    Deal with data in various formats (e.g. timestamps, strings) and filter and “clean” datasets by removing outliers etc.

  • Check

    Basic experience with data processing libraries such as numpy and data ingestion with urllib, requests

Habilidades que obtendrás

Python LibrariesData Pre-ProcessingData Visualization (DataViz)Web Scraping

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

B​asic knowledge of programming (any language)

Aprox. 16 horas para completar

Sugerido: 7 hours/week...

Inglés (English)

Subtítulos: Inglés (English)

Programa - Qué aprenderás en este curso

Semana
1
2 horas para completar

Week 1: Introduction to Data Products

This week, we will go over the syllabus and set you up with the course materials and software. We will introduce you to data products and refresh your memory on Python and Jupyter notebooks.

...
6 videos (Total 42 minutos), 6 readings, 2 quizzes
6 videos
Data Product Examples in Enterprise5m
Developing a Data Product Strategy7m
Python and Jupyter Basics6m
Python Recap5m
Livecoding: Getting Started With Jupyter10m
6 lecturas
Syllabus10m
Course Materials10m
Set Up Your System10m
Our Case Study: Recommender Systems10m
(Optional) Python: How to Run10m
(Optional) Python: Additional Resources and Recommended Readings10m
2 ejercicios de práctica
Review: Data Products4m
Review: Python and Jupyter5m
Semana
2
2 horas para completar

Week 2: Reading Data in Python

This week, we will learn how to load in datasets from CSV and JSON files. We will also practice manipulating data from these datasets with basic Python commands.

...
6 videos (Total 54 minutos), 3 quizzes
6 videos
Reading CSV & JSON Files9m
Processing Structured Data in Python8m
Live-Coding: JSON5m
Extracting Simple Statistics From Datasets11m
Simple Statistics: Live-Coding8m
3 ejercicios de práctica
Review: CSV and JSON Files8m
Review: Simple Statistics10m
Python: Reading Data and Simple Statistics45m
Semana
3
1 hora para completar

Week 3: Data Processing in Python

This week, our goal is to understand how to clean up a dataset before analyzing it. We will go over how to work with different types of data, such as strings and dates.

...
4 videos (Total 38 minutos), 3 quizzes
4 videos
Processing Text and Strings in Python7m
Processing Times and Dates in Python11m
Livecoding: Time and Date Data8m
3 ejercicios de práctica
Review: Data Filtering and Cleaning5m
Review: Processing Different Data Types5m
Data Processing in Python30m
Semana
4
2 horas para completar

Week 4: Python Libraries and Toolkits

In this last week, we will get a sense of common libraries in Python and how they can be useful. We will cover data visualization with numpy and MatPlotLib, and also introduce you to the basics of webscraping with urllib and BeautifulSoup.

...
5 videos (Total 45 minutos), 5 quizzes
5 videos
Introduction to Data Visualization11m
Introduction to Matplotlib5m
Live-coding: MatPlotLib9m
urllib and BeautifulSoup12m
4 ejercicios de práctica
Review: NumPy4m
Review: MatPlotLib6m
Review: urllib and BeautifulSoup6m
Python Libraries and Toolkits15m

Instructores

Avatar

Julian McAuley

Assistant Professor
Computer Science
Avatar

Ilkay Altintas

Chief Data Science Officer
San Diego Supercomputer Center

Acerca de Universidad de California en San Diego

UC San Diego is an academic powerhouse and economic engine, recognized as one of the top 10 public universities by U.S. News and World Report. Innovation is central to who we are and what we do. Here, students learn that knowledge isn't just acquired in the classroom—life is their laboratory....

Acerca del 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

  • Una vez que te inscribes para obtener un Certificado, tendrás acceso a todos los videos, cuestionarios y tareas de programación (si corresponde). Las tareas calificadas por compañeros solo pueden enviarse y revisarse una vez que haya comenzado tu sesión. Si eliges explorar el curso sin comprarlo, es posible que no puedas acceder a determinadas tareas.

  • Cuando te inscribes en un curso, obtienes acceso a todos los cursos que forman parte del Programa especializado y te darán un Certificado cuando completes el trabajo. Se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes auditar el curso sin costo.

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