Data scientists build information platforms to provide deep insight and answer previously unimaginable questions. Spark and Hadoop are transforming how data scientists work by allowing interactive and iterative data analysis at scale. Learn how Spark and Hadoop enable data scientists to help companies reduce costs, increase profits, improve products, retain customers, and identify new opportunities. Cloudera University’s three-day course helps participants understand what data scientists do, the problems they solve, and the tools and techniques they use. Through in-class simulations, participants apply data science methods to real-world challenges in different industries and, ultimately, prepare for data scientist roles in the field
Through instructor-led discussion and interactive, hands-on exercises, participants will navigate the Hadoop ecosystem, and develop concrete skills such as:
How to identify potential business use cases where data science can provide impactful results
How to obtain, clean and combine disparate data sources to create a coherent picture for analysis
What statistical methods to leverage for data exploration that will provide critical insight into your data
Where and when to leverage Hadoop streaming and Apache Spark for data science pipelines
What machine learning technique to use for a particular data science project
How to implement and manage recommenders using Spark’s MLlib, and how to set up and evaluate data experiments
What are the pitfalls of deploying new analytics projects to production, at scale
Overview of ALS Method for Latent Factor Recommenders
Hyperparameters for ALS Recommenders
Building a Recommender in MLlib
Experimentation and Evaluation
Designing Effective Experiments
Conducting an Effective Experiment
User Interfaces for Recommenders
Production Deployment and Beyond
Deploying to Production
Tips and Techniques for Working at Scale
Summarizing and Visualizing Results
Considerations for Improvement
Next Steps for Recommenders
This course is suitable for developers, data analysts, and statisticians with basic knowledge of Apache Hadoop: HDFS, MapReduce, Hadoop Streaming, and Apache Hive as well as experience working in Linux environments.
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