Recording of the session “Building Predictive Analytics Models using Data Science Lifecycle” from the CIPS Saskatchewan Professional Development Conference on Nov 19th 2020.

Session Presenter: Alireza Manashty, Assistant Professor, Director, Data Science Laboratory

Session: “Building Predictive Analytics Models using Data Science Lifecycle”

People are curious about becoming a data scientist. You do not need to be a data scientist to start solving business problems using data science lifecycle.

In this talk, you will learn about what Big Data and Data Science could actually mean, and how you can solve an actual business problem and leverage the data science lifecycle to automate some decisions using machine learning models in Python.

What will be covered in this talk:

  • How to reframe a business problem into a data science problem
  • Step-by-step scenario following the data science lifecycle to solve a business problem
  • Python sample code snippets for each step
  • Learning about a simple machine learning model in details

About the speaker:

Dr. Alireza Manashty is the Director of Data Science Laboratory and an Assistant Professor in Computer Science (Data Science & Machine Learning) at the University of Regina. He is conducting research in temporal forecasting, federated machine learning, and explainable artificial intelligence. He has 9+ years of practical problem solving using machine learning by helping government, hospitals, and tech companies. Fortune 500 companies such as Microsoft, NVIDIA, and Google (Kaggle) have sponsored his research in recent years. Dr. Manashty holds a Ph.D. in Computer Science, a M.Sc in Artificial Intelligence, and a B.Sc in Software Engineering.

Webcast: “Building Predictive Analytics Models using Data Science Lifecycle” (Members-Only)