Analytics Experience 2019

October 21-23 | Milan, Italy

Registration is now closed

High Level Training Courses

Become a proficient SAS® user and gain globally recognized credentials.

Join us during the training sessions on October 21st and participate in the courses taught by certified SAS professionals and renowned education institutions and universities!

You can choose among five different courses and register for them during online registration.

Be curious: Do not miss the opportunity to enrich your Analytics Experience!

AMBER 6

Accelerate the analytics lifecycle in cloud

This course introduces the complete analytics lifecycle: data, discovery, deployment; participants will learn how the analytical flow works in cloud.The first part of the cycle is about data collection and data management; the second part is about discovery, models and the application of algorithms; the third part is about deployment and governance. The course will follow these 3 steps and will have a fourth part about the development of this lifecycle with a cloud architecture and with containers.

AMBER 7

Crash Course in Data Science for the Business User

This crash course Data Science teaches the basic concepts of data science.  It kicks off by zooming out and reviewing various applications and the analytics process model.  It then zooms into each of the steps in more detail.  Data preprocessing is extensively covered given its impact on subsequent analytical model development.  We elaborate on predictive, descriptive and social network analytics and discuss various techniques together with their performance measurement from a business perspective.  Post processing of analytical models and a selection of management topics such as economic aspects, improving ROI, privacy and security are also reviewed. Throughout the course, some examples and small case studies are used for further clarification of the concepts introduced. Upon finishing this course, the participant will have sound knowledge about the key concepts, business applications, potential and challenges of data science! 

AMBER 8

Deep Learning with SAS

This Workshop will lead the attendees towards the most exciting breakthroughs in modern Artificial Intelligence by implementing code. The participant will learn how to implement AI programs very easily and effectively by putting hands-on SAS. We will tackle the two most appealing case of study in AI nowadays: Computer Vision and Time-Series

SUITE 7

SAS Viya & Open Source Integration focus on Python

In this course, you learn to use the Python API to take control of SAS Cloud Analytic Services (CAS) actions from Jupyter Notebook. You learn to upload data into the in-memory distributed environment, analyze data, and create predictive models in CAS using familiar Python functionality via the SWAT (SAS Wrapper for Analytics Transfer) package. You will then learn to download results to the client and use native Python syntax to compare models. Important: this is a BYOD course (Bring Your Own Device): you are allowed to take your laptop or personal computer to have practice examples, tips & tricks directly during the conference. It is not mandatory, anyone wishing to do hands-on must have a laptop with Firefox or Chrome installed. Mac, pc, and Chromebook should all be fine.

SUITE 6

Machine Learning with SAS Viya: Hands-on

This course covers the foundation for different techniques associated with supervised machine learning models. A series of demonstrations and exercises is used to reinforce all the concepts and the analytical approach to solving business problems. A business case study is defined to guide participants through all steps of the analytical life cycle, from problem understanding to model deployment, through data preparation, feature selection, model training and validation, and model assessment. You learn to train supervised machine learning models to make better decisions about big data.IMPORTANT: This is an intensive course with PCs support but without final exam/certification.

Together we make analytics real
Real data. Real insights. Real results.