3 days.

• 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 to produce accurate, useful data sets
• Determine the most appropriate type of analysis to perform 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-oriented results from the analysis

This course is suitable for software engineers, data analysts and statisticians with basic knowledge of Apache Hadoop: HDFS, MapReduce, Hadoop Streaming, Apache Hive. Students should have proficiency in a scripting language: Python is strongly preferred, but familiarity with Perl or Ruby is sufficient.

Certification Exam

Following successful completion of the training class, attendees will be given a voucher for one attempt of the written certification exam. This voucher is non-transfearable and is given only to individuals who successfully complete the entire training class. Participants are also encouraged to prepare for and take the Data Scientist hands-on lab exam. Both exams will be available soon.

• Introduction
• Data Science Overview
• Use Cases
• Project Lifecycle
• Data Acquisition
• Evaluating Input Data
• Data Transformation
• Data Analysis and Statistical Methods
• Fundamentals of Machine Learning
• Recommender Overview
• Introduction to Apache Mahout
• Implementing Recommenders with Apache Mahout
• Experimentation and Evaluation
• Production Deployment and Beyond
• Conclusion
• Appendix A : Hadoop Overview
• Appendix B: Mathematical Formulas
• Appendix C : Language and Tool Reference