I have been developing predictive applications for more than a decade.
I have built countless models and leading data science teams in the finance, online, ad-tech and gaming industries. Recommendation engines, automatic bidding, smart alerts, marketing models and algorithmic trading are only partial list of applications I built from scratch. For each of them, I was involved in the project from conception to delivery - beginning by pinpointing the business's needs and ending up with a live system.
Because data science is an emerging field, it is often hard to find professionals who can share their insights from the real world. When I was starting out, I often wished I had a mentor. (I am sure he or she could have helped me avoid many of the challenges and failures that I faced early on.)
I learned the hard way, but through this course I hope to help accelerate my students’ achievement so they know how to deliver outstanding results as a data scientist, regardless of how long they’ve been in the field.
Learning machine learning models is one thing, but delivering predictive application that work is a challenge with a totally different level of complexity.
This is the focus of my course - lessons learned about delivering predictive applications that work and meet the needs of a company.