This hands-on course introduces experienced SAS programmers to working with Apache Hadoop. The course is problem-driven and focuses on helping you understand what data scientists do, the problems they solve, and their methods. By taking a practical approach to the subject, including multiple hands-on exercises, you will leave the course with skills that you can immediately apply to real-world problems.
Data Science Building Recommender Systems with SAS R and Hadoop
Before attending this course, you must be able to program in Base SAS and know how to use macros.
Who should attend?
SAS programmers and statisticians who have some basic familiarity with Apache Hadoop
- describe the role and responsibilities of a data scientist
- explain several ways in which data scientists create value for organizations across many industries
- locate and acquire data from diverse sources
- use transformation and normalization techniques on both structured and unstructured data
- determine the most appropriate type of analysis and modeling tool to use for a given problem
- be able to implement an automated recommendation system
- develop, evaluate and refine scoring systems for recommenders
- understand the considerations involved in working at scale
- Identify meaningful, actionable, and business-orientated results from the analysis
- Data Science Overview
- Hadoop Overview
- Use Cases
- Project Lifecycle
- Data Acquisition
- Evaluating Input Data
- Data Transformation
- Data Analysis and Statistical Methods
- Machine Learning Fundamentals
- Recommender Overview
- Implementing Recommenders with Map Reduce and SAS
- Experimentation and Evaluation
- Deployment and Next Steps
- Appendix: Hadoop Overview
- Appendix: Mathematical Formulas
- Appendix: Language and Tool Reference
This is a QA approved partner course
Face-to-face learning in the comfort of our quality nationwide centres, with free refreshments and Wi-Fi.
Find dates and prices
Online booking is currently not available for this course, to find out more please call us on 0113 220 7150 or email us at firstname.lastname@example.org to discuss how we can help.
Fully accredited to ensure we provide the highest possible standards in learning