University of California San Diego
Python Data Products for Predictive Analytics Specialization

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University of California San Diego

Python Data Products for Predictive Analytics Specialization

Build Predictive Systems with Accuracy. Collect, model, and deploy data-driven systems using Python and machine learning.

Julian McAuley
Ilkay Altintas

Instructors: Julian McAuley

Included with Coursera Plus

Get in-depth knowledge of a subject
4.2

(172 reviews)

Intermediate level
Some related experience required
4 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
Get in-depth knowledge of a subject
4.2

(172 reviews)

Intermediate level
Some related experience required
4 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Discover how to transform data and make it suitable for data-driven predictive tasks

  • Understand how to compute basic statistics using real-world datasets of consumer activities, like product reviews and more

  • Use Python to create interactive data visualizations to make meaningful predictions and build simple demo systems

  • Perform simple regressions and classifications on datasets using machine learning libraries

Details to know

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Taught in English
42 practice exercises

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  • Develop a deep understanding of key concepts
  • Earn a career certificate from University of California San Diego

Specialization - 4 course series

What you'll learn

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

  • Load and process formatted datasets such as CSV and JSON.

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

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

Skills you'll gain

Data Processing, NumPy, Python Programming, Matplotlib, Data Visualization Software, Interactive Data Visualization, Web Scraping, Data Manipulation, Data Cleansing, Data Visualization, Data Science, Data Import/Export, Pandas (Python Package), JSON, and Jupyter

What you'll learn

Skills you'll gain

Feature Engineering, Regression Analysis, Supervised Learning, Predictive Analytics, Tensorflow, Classification And Regression Tree (CART), Data Manipulation, Data Cleansing, Design Thinking, Data Science, Deep Learning, Predictive Modeling, Applied Machine Learning, Machine Learning Algorithms, Scikit Learn (Machine Learning Library), and Statistical Methods

What you'll learn

  • Understand the definitions of simple error measures (e.g. MSE, accuracy, precision/recall).

  • Evaluate the performance of regressors / classifiers using the above measures.

  • Understand the difference between training/testing performance, and generalizability.

  • Understand techniques to avoid overfitting and achieve good generalization performance.

Skills you'll gain

Predictive Modeling, Supervised Learning, Regression Analysis, Data Validation, Machine Learning Methods, Python Programming, Applied Machine Learning, Test Data, Natural Language Processing, Verification And Validation, and Statistical Methods

What you'll learn

  • Project structure of interactive Python data applications

  • Python web server frameworks: (e.g.) Flask, Django, Dash

  • Best practices around deploying ML models and monitoring performance

  • Deployment scripts, serializing models, APIs

Skills you'll gain

Django (Web Framework), Applied Machine Learning, Flask (Web Framework), Application Deployment, Predictive Modeling, Web Applications, Regression Analysis, Machine Learning, Data Manipulation, Data Processing, and Python Programming

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Instructors

Julian McAuley
University of California San Diego
5 Courses32,395 learners

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