Open to the Climate: Data-based Modeling and Decision-Making

In today's data-driven world, organizations generate vast amounts of information. Success lies in the ability to transform raw data into actionable insights. This course is designed to equip professionals with the skills needed to turn raw data into actionable intelligence.

This course is ideal for professionals looking to improve their skills in data-driven decision-making and predictive analytics, giving them the tools to make better strategic business decisions.

Who is the course for?

The course is aimed at business leaders, managers, and researchers who wish to understand the complexities of data-driven decision-making to enhance their leadership skills and business strategies.

Course content

The course covers:

• Overview of data-driven decision-making processes in modern organizations.
• Introduction to machine learning and its significance in data analytics.
• Exploration of information-based learning techniques for predictions and their use cases.
• In-depth exploration of error-based learning techniques used in predictive analytics.
• Practical examples and case studies showcasing error-based learning in real-world scenarios.
• Introduction to Artificial Neural Networks (ANN) and deep learning.
• Explanation of how neural networks are used to model complex patterns and make predictions.
  

Course Structure

The course is structured in two phases: Theory and Practical.

Phase 1: Theoretical Foundations (Module 1-4)

• The theory phase spans four weeks, four theory modules with one lecture per week.

• The lectures follow a flipped classroom model, where participants are expected to engage in self-study using the provided learning materials.

• There will be three Q&A sessions during this phase, providing opportunities for participants to ask questions and engage in brief discussions.

Phase 2: Practical Application (Module 5)

• In the practical phase, participants will apply their learning to a project task designed to reinforce the concepts covered in the theory phase

• There will be two Q&A sessions during this phase to support participants as they work on their projects.

By the end of the course you will be able to

• Explain and apply key concepts in predictive analytics.
• Demonstrate how data-driven decision-making can add value to industries and businesses.
• Plan and execute a project focused on data-driven decision-making.
• Interpret and evaluate the results of predictive models to inform business strategies.
  

For successful completion of the course, the following is required

• Completion of all course assignments as outlined in the curriculum.

Teachers

• Dr. Payal Gupta
• Professor Jaap van de Beek
  

Registration

• Register here External link, opens in new window.
  Luleå University of Technology reserves the right to cancel the course if there are too few participants. The course will begin once there are enough participants.

Contact us

LTU Professional Education uppdragsutbildning@ltu.se