Introduction to Data Science – Building Recommender Systems

This hands-on course is suitable for software engineers, data analysts and statisticians. It is problem-driven and focuses on helping participants understand what a data scientist does, the problems they typically solve and their approach to doing so. By taking a practical approach to the subject, including multiple hands-on exercises, participants will leave the course with skills they can immediately apply to real-world problems.

Download the full agenda for Cloudera’s Introduction to Data Science.

Read the blog post: Training a New Generation of Data Scientists.

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. A basic knowledge of Hadoop is assumed: use of the HDFS file system, awareness of the MapReduce framework, Hadoop Streaming and Hive. Students should have proficiency in a scripting language; Python is strongly preferred, although students familiar with another language such as Perl or Ruby should be able to complete the exercises.

• 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

To register: http://university.cloudera.com/training/data_science/introduction_to_data_science_-_building_recommender_systems.html