About This Course

• Leverage Python’s most powerful open source libraries for deep learning, data wrangling, and data visualization

• Get to know effective strategies and best practices to improve and optimize machine learning systems and algorithms

• Ask—and answer— tough questions of your data with robust statistical models, built for a range of datasets

Machine learning and predictive analytics are transforming the way that businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, and is becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace.

Python can help you deliver key insights into your data. Its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success.

This course gives you access to the world of predictive analytics and demonstrates why Python is one of the world’s leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science course is invaluable.

The course covers a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and features guidance and tips on everything from sentiment analysis to neural networks.

With this course, you’ll soon be able to answer some of the most important questions facing you and your organization.