Scalable AI with Apache Spark and Mllib

CODE: NAI13

DURATION: 3 Days | 5 Days | 10 Days

CERTIFICATIONS: CPD

  • Modern facilities
  • Course materials and certificate
  • Accredited international trainers

3 Days

₦500000

5 Days

₦1500000

10 Days

₦3500000

Course Overview

This course provides a comprehensive introduction to building scalable machine learning solutions using Apache Spark and its MLlib library. Participants will learn how to process large datasets, develop distributed machine learning models, and optimize workflows for performance across clusters. The course is a combination of theory with practical training to help participants apply Spark’s APIs in Python or Scala, enabling scalable and efficient AI workflows for big data environments.

Course Delivery

This course is available in the following formats:

Virtual

Classroom

Request this course in a different delivery format.

Course Outcomes

Delegates will gain the knowledge and skills to:

Know the fundamentals of distributed computing with Apache Spark.

Build and train scalable machine learning models using Mllib.

Preprocess and transform large datasets for model training.

Apply classification, regression, clustering, and recommendation techniques.

Optimize ML workflows and manage model persistence.

Use Spark ML pipelines for automation and reproducibility.

Integrate Spark with cloud platforms and data lakes.

Troubleshoot performance issues and tune distributed systems.

Key Course Highlights

At the end of this course, you’ll understand:

  • Spark architecture and distributed data processing.
  • Hands-on implementation with Spark MLlib algorithms.
  • Data wrangling and feature engineering at scale.
  • Building ML pipelines for automation and deployment.
  • Distributed model evaluation and parameter tuning.
  • Integration with Hadoop, HDFS, and cloud services (e.g., AWS, Azure).
  • Real-time data processing with Spark Streaming.
  • Case studies in fraud detection, predictive analytics, and recommendations.
  • Best practices for scaling AI workflows in production.
  • Labs using Databricks or standalone Spark environments.
Who Should Attend

This course is designed for data engineers, machine learning engineers, data scientists, and technical professionals working with large-scale data. It is also important for software developers and architects looking to build distributed AI systems using Apache Spark. Familiarity with Python or Scala and basic machine learning concepts is recommended.

Upcoming Course Dates

Delivery Format: Classroom & Virtual

Date: 10/11/2025

Location: Abuja

Scalable AI with Apache Spark and Mllib

✓ Modern facilities

✓ Course materials and certificate

✓ Accredited international trainers

✓ Training materials and workbook

✓ Access to online resources

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