Data Science is the practice of applying advanced machine learning techniques to address complex business problems. At DSI, we combine our client’s domain expertise and data with our AI expertise to develop production-ready AI models.
Arash AskaryCloud Solution Architect - Data Science
Arash is an academically trained Data Scientist with a thorough understanding of big data analytics and a deep fascination with its implications for our future. He is a problem solver, big thinker and a team player. His passion resides in using machine learning to identify patterns within data and develop AI based applications that enable smarter business decisions.
Combine your domain knowledge and data with our machine learning expertise to build powerful AI solutions
A free half-day session on machine learning to enhance your internal capabilities followed by a discovery session to collaboratively define business use-cases that can be addressed with the latest in AI.
A term coined by Gartner: a person who develops statistical models but whose primary job function is outside the field of statistics. Allow us to get you started on your Data Science journey by registering for our Data Science 101 sessions!
Deep learning is part of a broader family of machine learning methods based on artificial neural networks. Deep learning has enabled us to build statistical models that can detect objects from images, recognize speech, translate languages and much more. Join our AI in a day session to learn more about the intricacies of deep learning!
MLOps is a practice for collaboration and communication between data scientists and operations professionals to help manage production ML lifecycle – from conception to productionization and maintenance
Data Science Process:
Using a variety of Azure services, data from various sources is transferred into an AI-enabled environment to build optimized models that are deployed and utilized by business users
Take advantage of our free learning
Data Science: Basics for Business
Overview: In this session attendees will have a comprehensive understanding of the statistical reasoning necessary in conducting machine learning applications within a business environment. The session will begin with an introduction into the current state of AI in 2020 followed by a run-down of the basic principles & best practices for machine learning, and ending with a hands-on exercise on model development, training & validation.
Intended Audience: Stakeholders of varying technical backgrounds. Beginners are welcome.
AI in a Day
Overview: Microsoft Azure Training Day: Azure AI is designed to help you think differently about developing cloud applications when AI is part of the solution set. You’ll learn how to build machine learning models and get a deeper understanding of Azure AI services so you can envision Azure-enabled AI projects for your company.
Intended Audience: Machine Learning Engineers and Data Scientists interested in learning what Azure has to offer and Citizen Data Scientists interested in productionizing their models.