Perform Cloud Data Science with Azure Machine Learning course is offered by Wardy IT Solutions. As a Microsoft Partner we’ve been awarded with the Silver Learning competency. Every training session we run is taught by a Microsoft Certified Trainer.
DurationPerform Cloud Data Science with Azure Machine Learning course is offered by Wardy IT Solutions. As a Microsoft Partner we’ve been awarded with the Silver Learning competency. Every training session we run is taught by a Microsoft Certified Trainer.
We pride ourselves on the quality of our trainers. Not only are they Microsoft specialists with real world experience but they know how to communicate their expertise using engaging teaching methods.
The Curriculum
We deliver Microsoft Official Curriculum (MOC) courses as well as our Training from the Trenches courses that we have designed especially for developers, DBAs and Business Intelligence professionals working with Microsoft SQL Server.
WARDY IT Solutions was founded in 2004 by Microsoft Valued Professional (MVP), Peter Ward. Today, WARDY IT Solutions is recognised as Australia’s leading provider of Microsoft Data Platform consultants, trainers and Data Analytics specialists.
This course covers an introduction to machine learning, helping candidates to acquire the essential knowledge and skills needed to understand and apply different machine learning techniques.
This course provides the latest concepts, tools and techniques to build and influence the development of a successful data science and machine learning capability. Delivered through an interactive approach utilising the latest tools, participants of this course are exposed to basic techniques
This Machine Learning with Sagemaker (AWS) course intended for data scientists and software engineers
Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars
This course explores a collaborative project between the UTS Data Science Institute and Sydney Trains. The objective of the project was to develop a timetable robustness evaluation model using analytical/statistical methods, or machine learning techniques.
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