SAS® ACADEMY FOR DATA SCIENCE

AI & Machine Learning Professional

Learn how to analytically approach business problems and understand each step of the analytical life cycle with this in-depth credential.

Here's what you'll get:

5 training courses

3 certification exams
vouchers

Earn up to 8
digital badges

Included Courses

Machine Learning Using SAS^® Viya^®COURSE 1

This course, which is at the core of the SAS Viya Data Mining and Machine Learning curriculum, teaches you the theoretical foundation for techniques associated with supervised machine learning models. Learn how to analytically approach business problems – and use a business case study to understand each step of the analytical life cycle. This course uses Model Studio, the pipeline flow interface in SAS Viya that helps you prepare, develop, compare and deploy advanced analytics models.

Learn how to:

Apply the analytical life cycle to a business need.
Prepare and explore data for analytical model development.
Create and select features for predictive modeling.

Develop supervised learning models based on different techniques, from decision tree to support vector machines.
Evaluate and select the best model based on business needs.
Deploy and manage analytical models under production.

SAS^® Visual Text Analytics in SAS^® Viya^®COURSE 1

This course, which enables you to use SAS Viya in a distributed computing environment, explores the five components of visual text analytics: parsing, concept derivation, topic derivation, text categorization and sentiment analysis. You’ll parse and analyze documents to find dominant themes and construct linguistic queries to satisfy specific information needs. You’ll also develop an integrated solution using information extracted from subject matter expert rules and machine learning results for model and rule-based topics and categories.

Learn how to:

Use the point-and-click interface of Model Studio and SAS Visual Text Analytics.

Interpret term maps and automatically identify key textual topics in your large document collections.

Create robust models for categorizing the content according to specific needs.

Create, modify and enable (or disable) custom concepts and test linguistic rule definitions with validation checks within the same interactive GUI.

Extract individual instances of concepts from within documents.

Create custom Boolean rules to categorize documents with respect to a categorical target variable and automatically modify those rules.

Deep Learning Using SAS^® Software
COURSE 2

Discover the essential components of deep learning, as well as how to build deep feedforward, convolutional and recurrent networks. Use neural networks to solve problems that include traditional classification, image classification and time-dependent outcomes. Explore practical methods used to enhance training data to produce better models, as well as a method for efficiently searching hyperparameters.

Learn how to:

Define and understand deep learning and build models using deep learning techniques.
Apply models to score (inference) new data.

Modify data for better analysis results.

Search the hyperparameter space of a deep learning model.

Forecasting Using Model Studio in SAS^® Viya^®
COURSE 1

Get a hands-on tour of the forecasting functionality in Model Studio, a component of SAS Viya. Learn how to load data into memory and visualize the time series data to be modeled while introducing and implementing attribute variables. Use pipelines to generate forecasts and select champion pipelines – and discover how to incorporate large-scale forecasting practices. These include the creation of data hierarchies, forecast reconciliation, overrides and forecast model selection best practices.

Learn how to:

Automatically create and fit custom forecast models using structured analytic workflows or pipelines.

Visualize modeling data using attribute variables.

Refine forecast models to improve forecast accuracy.

Apply overrides-generated forecasts.

Generate forecast data sets for deployment.

Build and share custom pipelines for large-scale forecasting analyses.

Optimization Concepts for Data Science and Artificial Intelligence
COURSE 2

This course focuses on linear, nonlinear and mixed-integer linear optimization concepts in SAS Viya. Discover how to formulate optimization problems and make formulations efficient by using index sets and arrays. The demonstrations in the course include examples of diet formulation and portfolio optimization. The OPTMODEL procedure is used to solve optimization problems that reinforce the concepts you've learned.

Learn how to:

Identify and formulate appropriate approaches to solving various linear, mixed-integer linear and nonlinear optimization problems.

Create optimization models commonly used in the industry.

Solve optimization problems using the OPTMODEL procedure in SAS.

Program Features

Online 24/7

E-learning courses accessible whenever – and wherever – you're ready to learn.

Hands-On Learning

Get full access to SAS software to practice what you've learned on real technology.

Globally Recognized Credentials

Earn a certification with tailored training that helps prepare you for each exam.

Pace Yourself

As long as you complete the nine courses within a 12-month time frame, you can go at your own pace.

Real-World Case Studies

Enhance your learning with practical application based on actual case studies.

SAS Expertise

Ask questions, find guidance and stay on track with help from SAS users and experts.

Prerequisite Skills
Discounts & Guidelines

Prerequisite Skills

It is recommended that you have prior programming experience using SAS, Python or R. You can gain programming knowledge in the SAS Programming 1: Essentials course. Candidates should also have some experience with the visual interfaces in SAS Viya. You can learn about those interfaces in SAS Visual Statistics in SAS Viya: Interactive Model Building or SAS Visual Analytics 1 for SAS Viya: Basics. It is helpful to have a conceptual understanding of regression models, which you can gain by completing Statistics 1: Introduction to ANOVA, Regression, and Logistic Regression. It is also helpful to have a conceptual understanding of neural network models, which you can gain by completing Neural Networks: Essentials or Neural Network Modeling.

Discounts

SAS Training Points: SAS Training Points can be purchased and used to pay for Academy offerings.
Academic discount: Educators, students (part- and full-time) and staff directly employed by academic institution or school district are eligible for a 50% discount off the price of the Academy. Proof of affiliation is required (e.g., valid identification card, a letter from HR on institution letterhead or a copy of your current semester transcript). Promo code: A50.
Partner discount: SAS partners are eligible for a 50% discount off the price of the Academy. Promo code: APD.

Guidelines

Buy Now

AI & Machine Learning
Professional

5 online courses.
12 months of unlimited access.
70 hours of cloud software access.
3 certification exam vouchers.

€1,295 / year

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AI & Machine Learning Professional