Time Series Analysis with Spark
By External Provider
About this course
This course focuses on building scalable time series analysis solutions using Apache Spark, a critical skill for modern data-driven organizations. Learners gain a strong understanding of why time series analysis matters and how it supports forecasting, monitoring, and decision-making at scale. Through a structured, end-to-end approach, the course guides learners from understanding time series data to preparing datasets, performing exploratory analysis, and building robust models. You will develop practical skills to test, evaluate, and refine models while handling real-world data challenges. What sets this course apart is its emphasis on combining core time series concepts with distributed computing using Spark. Learners explore how theory translates into scalable, production-ready systems used in industry. This course is ideal for data professionals, engineers, and analysts looking to scale time series workflows using Spark. Prior experience with basic data analysis and some familiarity with programming concepts is recommended.
What you will learn
- Master the process of preparing and organizing large-scale time series data for analysis.
- Develop and evaluate scalable, production-ready time series models with Apache Spark and Databricks.
- Leverage Generative AI and advanced Spark features to enhance predictive analytics and discover new patterns.