This formation is approximately 50% hands-on, combining expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises.

What You Will Learn :

  • Understand the main concepts and principles of predictive analytics
  • Use the Python data analytics ecosystem to implement end-to-end predictive analytics projects
  • Explore advanced predictive modeling algorithms with an emphasis on theory with intuitive explanations
  • Learn to deploy a predictive model’s results as an interactive application
  • Learn about the stages involved in producing complete predictive analytics solutions
  • Understand how to define a problem, propose a solution, and prepare a dataset
  • Use visualizations to explore relationships and gain insights into the dataset
  • Learn to build regression and classification models using scikit-learn
  • Use Keras to build powerful neural network models that produce accurate predictions
  • Learn to serve a model’s predictions as a web application

Who should attend ?

  • Anyone who is interested in quickly learning the Python language in the field of data science.

Prerequisites :

  • This formation is geared for Python experienced attendees who wish to learn and use basic machine learning algorithms and concepts. In order to be successful in the hands-on labs, you should have incoming experience working with basic Python for data science (including Pandas and Numpy, etc)