Most digital learning professionals know that data science and artificial intelligence (AI) can make their everyday processes more efficient and help them reach business goals faster. However, many still have questions around the real-life applications of data science and AI within digital learning, including:

• What are some examples of how AI and data science can address digital learning challenges?
• What processes can be automated?
• At what stage of the learning strategy can these technologies be implemented?
• What are the first steps for implementing data science solutions?
• What expertise and resources are necessary to successfully implement AI and data science solutions?
• What are some best practices for preparing learning data for processing, etc.?

In this session, you will study some of our practical use cases to learn about the diverse data science and machine learning applications in education. After this session, you will have a strong understanding of how you can leverage data science for your digital learning strategy to become more efficient in reaching your business goals.

In this session you will:

• Discover diversity and variability of the data science and machine learning applications in education 
• See how EPAM uses these technologies to improve learning outcomes and the impact of learning in our organization 
• Learn how you could implement these technologies in your own digital learning strategy

Technologies discussed:

Data science, machine learning, artificial intelligence, predictive analytics

Target audience:

Designers, developers, managers, senior leaders (directors, VP, CLO, executive, etc.)