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Machine Learning Using SAS Viya

  • Tuition USD $1,450
  • Reviews star_rate star_rate star_rate star_rate star_half 3224 Ratings
  • Course Code CPML35
  • Duration 2 days
  • Available Formats Classroom, Virtual

This course discusses the theoretical foundation for techniques associated with supervised machine learning models. A series of demonstrations and practices is used to reinforce all the concepts and the analytical approach to solving business problems. In addition, 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 and deployment. This course is the core of the SAS Viya Data Mining and Machine Learning curriculum. It uses Model Studio, the pipeline flow interface in SAS Viya that enables you to prepare, develop, compare, and deploy advanced analytics models. You learn to train supervised machine learning models to make better decisions on big data.

  • This course can help prepare you for the following certification exam(s): Machine Learning Specialist.

Skills Gained

  • Apply the analytical life cycle to a business need.
  • Incorporate a business-problem-solving approach in daily activities.
  • Prepare and explore data for analytical model development.
  • Create and select features for predictive modeling.
  • Develop a series of supervised learning models based on different techniques such as decision trees, ensembles of trees (forest and gradient boosting), neural networks, and support vector machines.
  • Evaluate and select the best model based on business needs.
  • Deploy and manage analytical models under production.

Who Can Benefit

Business analysts, data analysts, marketing analysts, marketing managers, data scientists, data engineers, financial analysts, data miners, statisticians, mathematicians, and others who work in correlated areas

  • Business analysts, data analysts, marketing analysts, marketing managers, data scientists, data engineers, financial analysts, data miners, statisticians, mathematicians, and others who work in correlated areas

Prerequisites

Before attending this course, participants should have at least an introductory-level familiarity with basic statistics. Previous SAS software experience is helpful but not required.

  • Before attending this course, participants should have at least an introductory-level familiarity with basic statistics. Previous SAS software experience is helpful but not required.

Course Details

Introduction

Introduction

  • Machine learning in business decision making.
  • Essentials of supervised prediction.
  • Introduction to SAS Viya.

Data Preparation

Data Preparation

  • Data exploration.
  • Feature extraction.
  • Input transformations.
  • Feature selection.
  • Variable clustering (self-study).
  • Best practices.
  • Selecting your algorithm.

Decision Trees and Ensembles of Trees

Decision Trees and Ensembles of Trees

  • Introduction.
  • Tree-structure models.
  • Recursive partitioning.
  • Pruning.
  • Ensembles of trees.

Neural Networks

Neural Networks

  • Introduction.
  • Network architecture.
  • Network learning and optimization.

Support Vector Machines and Additional Topics

Support Vector Machines and Additional Topics

  • Large-margin linear classifier.
  • Methods of solution.
  • Nonlinear classifier: Kernel Trick.
  • Additional tools.

Model Assessment and Deployment

Model Assessment and Deployment

  • Model assessment and comparison.
  • Model deployment.

When does class start/end?

Classes begin promptly at 9:00 am, and typically end at 5:00 pm.

Does the course schedule include a Lunchbreak?

Lunch is normally an hour long and begins at noon. Coffee, tea, hot chocolate and juice are available all day in the kitchen. Fruit, muffins and bagels are served each morning. There are numerous restaurants near each of our centers, and some popular ones are indicated on the Area Map in the Student Welcome Handbooks - these can be picked up in the lobby or requested from one of our ExitCertified staff.

How can someone reach me during class?

If someone should need to contact you while you are in class, please have them call the center telephone number and leave a message with the receptionist.

What languages are used to deliver training?

Most courses are conducted in English, unless otherwise specified. Some courses will have the word "FRENCH" marked in red beside the scheduled date(s) indicating the language of instruction.

What does GTR stand for?

GTR stands for Guaranteed to Run; if you see a course with this status, it means this event is confirmed to run. View our GTR page to see our full list of Guaranteed to Run courses.

Does ExitCertified deliver group training?

Yes, we provide training for groups, individuals and private on sites. View our group training page for more information.

Does ExitCertified deliver group training?

Yes, we provide training for groups, individuals, and private on sites. View our group training page for more information.

Great class, engaging instructor - helpful materials. A week on Zoom went by in a flash, thank you :)

It was a great class taught by Ruben. It was great the way he used his experience and use cases to communicate to the class.

I am impressed with the level of attention and swift support from ExitCertified. Great work

ExitCertified offers excellent IT training classes. Virtual learning is as good as in-person in my opinion.

The lab environment is well established. Access to study materials is a bit too restrictive (vitalsource bookshelf)

5 options available

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  • Jun 28, 2021 Jul 1, 2021 (4 days)
    Location
    Virtual
    Language
    English
    Time
    1:00 PM 4:30 PM EST
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  • Aug 3, 2021 Aug 6, 2021 (4 days)
    Location
    Virtual
    Language
    English
    Time
    1:00 PM 4:30 PM EST
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  • Oct 12, 2021 Oct 15, 2021 (4 days)
    Location
    Virtual
    Language
    English
    Time
    1:00 PM 4:30 PM EST
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  • Oct 25, 2021 Oct 28, 2021 (4 days)
    Location
    Virtual
    Language
    English
    Time
    1:00 PM 4:30 PM EST
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  • Nov 30, 2021 Dec 3, 2021 (4 days)
    Location
    Virtual
    Language
    English
    Time
    1:00 PM 4:30 PM EST
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