UdemyIT & SoftwarePaid courseAll LevelsCertificate

Distributed Computing for Smart Grids Big Data (Udemy.com)

Spark and Hadoop for distributed machine learning

4.5

61 reviews

Created by: Ameema Zainab

Last updated November 2025

What you will learn

Use of big data machine learning for smart grid big data. ML model training on multiple processes
2 weeks to complete the course
No risks involved. Its advisable to have access to high performance computing infrastructure if possible
3 case studies to try the project at your end too

How it compares

Against the other 1,182 rated Udemy courses in IT & Software on CourseDuck:

Rating4.5 out of 5higher than 45% of them
Reviews61#1,080 of 1,183 by number of reviews
Length0.9 hoursshorter than 97% of them
Last updatedNovember 2025more recently than 57% of them

Course Description

The course will commence with an introduction to smart grids and the significance of data management in the energy sector. We will discuss the fundamental concepts of big data and machine learning techniques and the importance of the Apache Spark and Hadoop frameworks in real-time processing of data. The next few sessions will focus on an overview of specific multiprocessing schemes for processing big data in the smart grid infrastructure.

Additionally, the course would include a significant focus on analyzing distributed real-time data using the Apache Spark framework. The course tackles big data problems for machine learning in production using Hadoop to implement distributed computation. Students will gain an in-depth understanding of Hadoop and Spark, including their usage for parallel processing of large data sets.

Moreover, the course also covers three case studies demonstrating the practical application of big data and machine learning. Students will also get hands-on experience with Apache Spark-based programs, covering distributed computing setup, program writing, and using complex algorithms for use cases.

At the end of this course, students would possess the skills required to manage big data in the energy sector efficiently, including the application of machine learning techniques and Apache Spark and Hadoop frameworks. Students will also be able to handle use cases that can be encountered in the industry.

All Levels

Time: 54 mins

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Instructor Details

Ameema Zainab

4.5 Rating
61 Reviews

I hold a Ph.D. in Machine Learning from Texas A&M University in College Station, Texas, and have worked in corporations and academic organizations for over ten years. During my time in these positions, I gained a thorough grasp of the numerous ML and NLP techniques used for predictive modeling and recommendation syatems. Furthermore, I am well-versed in Big Data technologies such as Hadoop, Spark, and others that are required to design effective data pipelines. I've worked for corporations, research organizations, and universities. I have a numerous publications for my work and have about 500+ citations.