DSCI-272: Predicting with Cloudera Machine Learning( Predicting With Cloudera Machine Learning ) Course Overview

Target Audience for DSCI-272: Predicting with Cloudera Machine Learning( Predicting With Cloudera Machine Learning )

DSCI-272: Predicting with Cloudera Machine Learning is an intermediate level course designed to equip data professionals with the skills to develop and deploy machine learning workflows using Cloudera's CML and CDP.

• Data Scientists
• Data Engineers
• Machine Learning Engineers
• Developers involved in data science projects
• Solution Architects
• IT Professionals working with big data and machine learning platforms
• Analytics Professionals seeking to leverage Cloudera's machine learning tools

Learning Objectives - What you will Learn in this DSCI-272: Predicting with Cloudera Machine Learning( Predicting With Cloudera Machine Learning )?

Introduction to the Learning Outcomes of DSCI-272: Predicting with Cloudera Machine Learning This course equips participants with the skills to create, evaluate, and deploy machine learning models using Cloudera Machine Learning on the Cloudera Data Platform.

Learning Objectives and Outcomes:

• Understand and utilize Cloudera SDX and other Cloudera Data Platform components for locating and managing data suitable for machine learning experiments.
• Employ Apache Spark and Spark ML for conducting scalable data analysis and machine learning on big datasets.
• Execute full machine learning workflows, including data preparation, model training, and model evaluation within the CML environment.
• Deploy machine learning models as REST APIs, allowing for integration into broader application ecosystems.
• Effectively manage and monitor machine learning models post-deployment to ensure performance and accuracy.
• Use the Applied ML Prototypes (AMPs) to jump-start machine learning projects with pre-built solutions.
• Connect to various data source types within Cloudera Machine Learning for comprehensive data exploration and visualization.
• Manipulate and transform data using DataFrame operations in PySpark within the Cloudera ecosystem.
• Address complex data types and apply user-defined functions in Spark to enhance data analysis capabilities.
• Master MLlib in Spark for executing machine