Time Series Analysis with Spark
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.
68/100
CourseAsk score
- What the provider tells you
- 32/45
- Who stands behind it
- 20/35
- How complete the listing is
- 16/20
Scores how much the provider publishes and who stands behind it — not how well it is taught.
What you'll learn
- understand the fundamentals of time series analysis
- prepare and clean time series datasets
- perform exploratory analysis of time series data
- build and refine time series models using Apache Spark
Price shown by Coursera — confirm on their site.
Enroll on CourseraYou'll be redirected to Coursera to complete enrollment.
- Listed & compared by CourseAsk
- English · 0
Coursera
Udemy
Compared on these lists
Where this course ranks against the alternatives.