IBM Apache Spark for Data Engineering and Machine Learning Free Online Course applications are open for international applicants. The principles of Data Engineering and Machine Learning with Apache Spark, including Spark Structured Streaming, ETL for Machine Learning (ML) Pipelines, and Spark ML, are covered in this brief course. You will have practical experience integrating Spark abilities into ETL and ML operations by the end of the course.

You’ll discover how to rapidly integrate features for extraction, selection, and transformation on structured data sets, as well as how to build pipelines. Learn how to use Spark for regression and classification. You will know what supervised and unsupervised learning are and how to distinguish them. Discover the basics of clustering and how to use Spark MLlib to implement the k-mean s clustering algorithm. Focused, practical labs and a final project where you apply Spark to a real-world problem-inspired scenario will help you reinforce your knowledge.

Quick Details:

• Offered by: IBM
• Format: Online
• Deadline: Ongoing
• Duration: 3 weeks at 2–3 hours per week
• Subject: Computer Science
• Language: English
• Associated programs: Professional Certificate in NoSQL, Big Data and Spark Fundamentals, Professional Certificate in Data Engineering
• Associated skills: Apache Hadoop, Machine Learning, Apache Spark, Stream Processing, Unsupervised Learning, Big Data, Data Engineering, Spark Dataframes, SQL (Programming Language), Extract Transform Load (ETL), Cluster Analysis, Batch Processing, Graph Theory, Operations
• Gender: Any
• Type: Online Course
• Level: Intermediate
• Eligible Nations: All (Except: Iran, Cuba and the Crimea region of Ukraine)

Syllabus:

• Module 1 – Spark for Data Engineering
• Module 2 – Spark ML for Machine Learning
• Module 3 – Final Project

Benefits:

Upon completion of the course, you will discover:

• Describe Apache Spark Structured Streaming’s characteristics, advantages, restrictions, and uses.
• Explain the basics of graph theory and the advantages of GraphFrames for developers.
• Describe the application of extract, transform, and load (ETL) procedures using Spark for developers.
• Explain how the development of machine learning is supported by Spark ML.
• Use Spark ML for classification and regression.
• Distinguish between uncontrolled and supervised learning. Machine learning”
• Describe the use of clustering in Spark ML.
• Show that you understand how to use Spark for ETL workflows practically.

Note: You have to spend $49 if you require a shareable certificate. Check out their FAQ, to learn more.

Eligibility Criteria:

• This is a free online course that anyone can take.
• There is no upper age limit.
• Applications are invited from students in any academic discipline.
• Students must have a stable internet connection because the course is offered online.
• Applicants must have a strong desire to pick up and apply new skills.

How to Apply?

Through edX, online enrollment is possible. To initiate the registration process, click on this link:

                 Apply Now

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For more details, kindly refer to edX’s website.