Data Science for Executives
Are you a business leader trying to navigate through all the recent advancements in AI technology?
Do you know what’s behind the power of your enterprise Data? And how you can start monetizing it today?
We invite to you participate and develop a clear understanding of how to strategically capitalize on and unlock your biggest business opportunities, yet.
"Data is your strategic asset. It’s your competitive advantage."
Nir KalderoNEORIS brings to you a unique workshop focused on identifying the highest value opportunities to leverage your enterprise data through data science and AI techniques.
The Data Science for Executives workshop will illuminate the key strengths and opportunities that lie in front of you on how to navigate your enterprise to become a data- and model-driven organization- that leverages the power of its data to better compete, reduce costs, and enhance growth & productivity.
This tailored worksop is guided by real-world case studies relevant to your industry, illustrating the importance of transforming your organization into a robust data- and model-driven enterprise that is better able to respond to this game-changing technology.
By the end of this workshop you be able to :
- Develop a stronger data literacy & machine intelligence mindset
- Understand the data science workflow, journey & ROI
- Apply tools, ideas, and mindsets on how to transform your enterprise to a data- and a model-driven organization
- Evaluate opportunities to invest in data science to achieve the highest potential business ROI
Hear from Nir Kaldero, the best-selling author of the Data Science for Executives and the Global Executive, Head of Data Science at NEORIS. Nir has dedicated his career working with the largest organizations in the world on how to transform themselves into a robust data- and model driven enterprise.
Member of Forbes Technology Councils, expert/mentor for companies such as Google / Facebook / CEMEX, long time an IBM Champion , and a frequesnt keynote speaker around the world.