Informações sobre o curso

100% online

Comece imediatamente e aprenda em seu próprio cronograma.

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.

Nível intermediário

B​asic knowledge of programming (any language)

Aprox. 21 horas para completar

Sugerido: 9 hours/week...

Inglês

Legendas: Inglês

O que você vai aprender

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    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 você terá

Python LibrariesData Pre-ProcessingData Visualization (DataViz)

100% online

Comece imediatamente e aprenda em seu próprio cronograma.

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.

Nível intermediário

B​asic knowledge of programming (any language)

Aprox. 21 horas para completar

Sugerido: 9 hours/week...

Inglês

Legendas: Inglês

Programa - O que você aprenderá com este curso

Semana
1
2 horas para concluir

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 vídeos (total de (Total 42 mín.) min), 6 leituras, 2 testes
6 videos
Data Product Examples in Enterprise5min
Developing a Data Product Strategy7min
Python and Jupyter Basics6min
Python Recap5min
Livecoding: Getting Started With Jupyter10min
6 leituras
Syllabus10min
Course Materials10min
Set Up Your System10min
Our Case Study: Recommender Systems10min
(Optional) Python: How to Run10min
(Optional) Python: Additional Resources10min
2 exercícios práticos
Review: Data Products4min
Review: Python and Jupyter4min
Semana
2
1 hora para concluir

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 vídeos (total de (Total 54 mín.) min), 3 testes
6 videos
Reading CSV & JSON Files9min
Processing Structured Data in Python8min
Live-Coding: JSON5min
Extracting Simple Statistics From Datasets11min
Simple Statistics: Live-Coding8min
3 exercícios práticos
Review: CSV and JSON Files6min
Review: Simple Statistics4min
Python: Reading Data10min
Semana
3
1 hora para concluir

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 vídeos (total de (Total 38 mín.) min), 3 testes
4 videos
Processing Text and Strings in Python7min
Processing Times and Dates in Python11min
Livecoding: Time and Date Data8min
3 exercícios práticos
Review: Data Filtering and Cleaning2min
Review: Processing Different Data Types5min
Data Processing in Python10min
Semana
4
1 hora para concluir

Week 4: Python Libraries and Toolkits

Get a sense of common libraries in Python and how they can be useful. Practice with MatPlotLib and other libraries. ...
5 vídeos (total de (Total 45 mín.) min), 4 testes
5 videos
Introduction to Data Visualization11min
Introduction to Matplotlib5min
Live-coding: MatPlotLib9min
urllib and BeautifulSoup12min
4 exercícios práticos
Review: NumPy2min
Review: MatPlotLib6min
Review: urllib and BeautifulSoup4min
Python Libraries & Toolkits10min

Instrutores

Avatar

Julian McAuley

Assistant Professor
Computer Science
Avatar

Ilkay Altintas

Chief Data Science Officer
San Diego Supercomputer Center

Sobre Universidade da Califórnia, 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....

Sobre o Programa de cursos integrados 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 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

Perguntas Frequentes – FAQ

  • Ao se inscrever para um Certificado, você terá acesso a todos os vídeos, testes e tarefas de programação (se aplicável). Tarefas avaliadas pelos colegas apenas podem ser enviadas e avaliadas após o início da sessão. Caso escolha explorar o curso sem adquiri-lo, talvez você não consiga acessar certas tarefas.

  • Quando você se inscreve no curso, tem acesso a todos os cursos na Especialização e pode obter um certificado quando concluir o trabalho. Seu Certificado eletrônico será adicionado à sua página de Participações e você poderá imprimi-lo ou adicioná-lo ao seu perfil no LinkedIn. Se quiser apenas ler e assistir o conteúdo do curso, você poderá frequentá-lo como ouvinte sem custo.

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