Data Science: From Prediction to Production
What you'll learn
- Practical perspective about predictions
- Guidelines for selecting models
- What makes you professional
- Guidelines for delivering fast results
- How to plan the development
- The importance of well written code
- Advanced topics in predictive modeling
Course content
- Preview07:29
- 13:34The Characteristics of a Good Prediction
Requirements
- Basic knowledge about data science
Description
When most data scientists begin their careers in the field, they quickly realize there is a huge gap between what they learned in school and the models they are asked to create day-in and day-out for the companies they work at. This course is meant to help data scientists excel in the workplace and teach them the real-life applications of their work.
Taught by a data scientist with over 10 years’ of experience, the course will give you an in-depth look at the work of a data scientist.
You will get actionable advice about how to deliver fast results and create models efficiently, effectively and in a way that is most beneficial for your company.
This course is an important step toward becoming a leading data scientist.
See you at the course.
Who this course is for:
- Data scientists
- Job seekers
- Data science managers
Instructor
![Snir Madar](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
- 3.9 Instructor Rating
- 24 Reviews
- 6,363 Students
- 1 Course
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.