About the Seminar
The rapid advancement of Generative AI has transformed the way developers build Data Science and AI solutions. While AI tools can significantly accelerate development, successful AI projects still require strong Data Science thinking, proper problem definition, and business-oriented evaluation.
This Seminar introduces modern Data Science from the perspective of today's AI-powered development workflow.
Participants will learn how to leverage AI tools effectively, understand where Data Science expertise remains essential, and apply practical methodologies for building valuable AI solutions.
Who Is This Seminar For?
Developers
Prerequisites
- Basic Python is required
- knowledge of using coding assistants
Key Topics
Part 1 – Modern AI & Data Science Foundations
Understanding today's AI landscape
- AI & Data Science – basic definitions
- Evolution of AI development
- Evolution of Generative AI
- Where Data Science fits in today's AI landscape
- How AI is changing the role of developers and Data Scientists
Part 2 – Exercise using coding assistant only
Part 3 – Developing with AI vs Developing AI (75–90 min)
Using AI as a Data Science assistant
- Developing with AI vs developing AI solutions
- Using AI throughout the Data Science workflow
- What still requires Data Science expertise
- Common mistakes when relying solely on AI-generated solutions
- Model selection: choosing the right approach instead of the most complex one
Part 4 – Building Valuable AI Solutions (75–90 min)
From business problem to successful solution
- The Data Science development lifecycle
- Defining the business problem
- Understanding and measuring business value
- Why accuracy is not enough
- Choosing the right evaluation metrics
- Common Data Science mistakes
- Risks and limitations of AI-generated solutions
- When traditional Data Science outperforms Generative AI
Part 5 – Developing a Data Science Solution with AI