Upon completing the PySpark for Data Science Specialization, you will be able to:

• Process Big Data: Efficiently handle large-scale datasets using PySpark's RDDs and DataFrames, applying transformations and actions for data manipulation.

• Implement Machine Learning Models: Utilize PySpark MLlib to build, evaluate, and deploy machine learning models, including regression, classification, and clustering techniques.

• Analyze and Process Text Data: Apply natural language processing (NLP) techniques using PySpark to extract meaningful information from text, enhancing your data analysis capabilities.

• Stream Data in Real Time: Master structured streaming with PySpark to process and analyze data in real-time, allowing for timely insights and actions.

It’s ideal for roles in data engineering, big data analytics, and data science, especially in cloud and distributed systems.

Yes, it is intended for learners who have basic knowledge of Python; no prior experience with Spark is required.

Yes, PySpark is free to use as part of the open-source Apache Spark project under the Apache 2.0 license. It can be used for personal and commercial projects without any licensing fees.

This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.

Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.