Artificial Intelligence
Machine Learning with Apache Spark
This course is an intermediate training program designed to help data engineers, machine learning practitioners, and analytics professionals build and deploy scalable ML models using Apache Spark.
🔒
Included with Skilldacity Membership
About This Course
⌄
This course is an intermediate training program designed to help data engineers, machine learning practitioners, and analytics professionals build and deploy scalable ML models using Apache Spark. This course blends foundational ML concepts with hands-on experience in SparkML, enabling you to construct real-world machine learning solutions for large-scale data environments. Begin your learning journey with the fundamentals of machine learning before diving into Apache Spark’s powerful distributed computing capabilities.
You’ll explore supervised and unsupervised learning methods—such as regression, classification, and clustering—through guided lessons, videos, and readings. Hands-on labs allow you to.
What You’ll Learn
⌄
Core machine learning concepts and their role in modern data engineering
Overview of generative AI and its relationship to ML workflows
How Apache Spark supports large-scale machine learning and data processing
How to build, evaluate, and deploy ML pipelines using SparkML
Model persistence, optimization, and real-world pipeline structures
Distinguishing between regression, classification, and clustering models
Constructing data analysis processes using Spark SQL
Performing ETL tasks and creating ML models with SparkML and scikit-learn
Skills You’ll Gain
⌄
Artificial Intelligence
Machine Learning
Database
Data Science
Career Path
Artificial Intelligence
Provider
Skilldacity
Level
Intermediate
Certification
No certification associated
Access
Included with eligible Skilldacity subscription
Ready to advance your career?
Join Skilldacity today and get unlimited access to this course and hundreds more.