This course is the most comprehensive training program in the fields of big data analytics and artificial intelligence. It is designed to prepare specialists to address the most complex analytical challenges using the SAS Viya platform and advanced statistical techniques. The course is based on the latest official curriculum from SAS for 2026, combining traditional data science with modern machine learning technologies to ensure participants acquire the ability to extract strategic insights that support decision-making in major organizations.
Note: This course does not grant a certificate of attendance. It is specifically designed to prepare and train participants to pass the official examination, aiming to equip them with a high level of professional competence to successfully attain the SAS Certified Data Scientist credential, officially accredited by SAS.
Course Objectives
- Develop skills in big data curation and preparation for statistical analysis.
- Enable participants to build predictive models using regression and multivariate analysis techniques.
- Explain advanced machine learning algorithms such as random forests and neural networks.
- Enhance the ability to use visual analytics tools to present results in an interactive and impactful manner.
- Apply optimization and simulation methodologies to achieve the best possible operational solutions.
- Prepare candidates to pass the SAS Data Scientist exam series through cloud lab training and applied practice questions.
Detailed Training Content
Unit 1: Data Curation for SAS Data Scientists
- Data management using SAS Data Management and integration with various data sources such as Hadoop and NoSQL.
- Data transformation techniques, including cleaning and processing using SAS programming language.
- Advanced querying using PROC SQL to handle large data sets.
- Data quality analysis and the identification and treatment of anomalies.
- Practical exercises and application questions on data organization, processing, and quality management.
Unit 2: Advanced Analytics and Statistical Modeling
- Inferential statistics, understanding distributions, and hypothesis testing.
- Building and interpreting linear and logistic regression models.
- Time series analysis and forecasting of future trends.
- Variable selection and dimensionality reduction techniques to improve model accuracy.
- Practical exercises and application questions on statistical modeling and predictive analytics.
Unit 3: Machine Learning and AI
- Supervised learning algorithms such as decision trees and support vector machines (SVM).
- Unsupervised learning techniques including clustering methods.
- Deep neural networks and their applications in complex data analysis.
- Model evaluation and comparison using confusion matrix and ROC curves.
- Practical exercises and application questions on machine learning algorithms and model performance evaluation.
Unit 4: Visual Analytics and Model Deployment
- Advanced data visualization using SAS Visual Analytics.
- Designing interactive dashboards to present results to stakeholders.
- Model management and deployment in real-world production environments.
- Open source integration and connecting SAS with Python and R.
- Practical exercises and application questions on analytical visualization and model deployment.
Unit 5: Final Review and Official Exam Simulation
- Comprehensive review of all exam tracks (Data Curation & Advanced Analytics).
- Business scenario analysis and training on identifying optimal analytical solutions.
- Intensive full mock exams simulating the official SAS testing environment.
- Discussion of efficient programming methodologies to enhance processing and analysis speed.
- Practical exercises and application questions on the full SAS Data Scientist curriculum and mock exams.
Target Audience
- Data analysts seeking to transition into data science roles.
- Statistical and mathematical engineers working in research and development sectors.
- Data engineers interested in predictive modeling and analysis.
- System administrators and project managers in the business intelligence sector.
- Graduates of computer science and statistics aiming to obtain the most prestigious global credential in data.
The SAS Certified Data Scientist credential represents the pinnacle of professional achievement in the era of big data. Holding this certification reflects your exceptional ability to harness complex algorithms to solve major organizational challenges. Investing in this course is a commitment to excellence in one of the 21st century’s most prestigious disciplines, ensuring you a leading position in the global job market that competes to attract minds capable of transforming silent data into strategic insights.
