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Spark: PySpark
Learn PySpark from basics in this free online tutorial. PySpark is taught hands-on by experts. Gain skills to work with Spark MLlib, RDD, data frames, and clustering with case studies for structured and semi-structured data.
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About this course
The PySpark course begins by giving you an introduction to PySpark and will further discuss examples to explain it. Moving further, you will gain expertise working with Spark libraries, like MLlib. Next, in this PySpark tutorial, you will learn to move RDD to Dataframe API and become familiar with Clustering in PySpark. The course also comprehends a case study to help you gain hands-on on the learned topics.
Adding value to your learning experience, the Introduction to PySpark course is taught by an industry expert. A quiz is assigned to test your gains at the end of the course. Complete the quiz and gain a course completion certificate.
To expand your learning in the Data Science domain, consider pursuing Data Science certificate courses that offer specialization/electives to escalate your career.
Course Outline
This section gives a clear overview of how Spark contributes to Hadoop, and the Spark framework. It explains PySpark with examples and code demonstrations.
This section discusses the Machine Learning library supported by Spark. It then explains ML pipelines, Transformers, Estimator, and architecture. You will also gain an understanding of K-means and Tf-ldf through hands-on code demonstrations.
You will understand Spark dataframes, and SQL. You will gain enough experience to understand why you need to shift from RDD to dataframe API while working with Data Science and Big Data tasks through demonstrated code samples.
This section will explain k-means clustering in MLlib and TFID, most commonly used in neural networks, with demonstrated code.
This section demonstrates a case study on the Music dataset to understand the aforementioned topics with hands-on experience.
What our learners enjoyed the most
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61% of learners found all the desired skills & tools
Frequently Asked Questions
Will I receive a certificate upon completing this free course?
Is this course free?
What are the prerequisites to learning this PySpark course?
PySpark is a beginner-level course. You can learn from this course swiftly if you have a basic understanding of Python programming language and SQL.
Is there any limit on how many times I can take this free course?
Once you enroll in the Pyspark course, you have lifetime access to it. So, you can log in anytime and learn it for free online.
Can I sign up for multiple courses from Great Learning Academy at the same time?
Yes, you can enroll in as many courses as you want from Great Learning Academy. There is no limit to the number of courses you can enroll in at once, but since the courses offered by Great Learning Academy are free, we suggest you learn one by one to get the best out of the subject.
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Spark:Pyspark Course
Spark: PySpark is a popular open-source, distributed computing framework used for big data processing. It is built on Apache Spark and provides a Python API for data processing tasks, making it a powerful tool for data engineers, data scientists, and business analysts.
One of the key benefits of Spark: PySpark is its ease of use, especially for those familiar with Python. It also offers high-level APIs for tasks like SQL, machine learning, and graph processing, allowing data professionals to quickly and easily process and analyze large amounts of data.
In terms of use cases, Spark: PySpark is widely used across industries such as finance, healthcare, and e-commerce for data processing, data analysis, and machine learning model development. Spark: PySpark is capable of handling both structured and unstructured data, making it an ideal tool for big data processing.
In conclusion, learning Spark: PySpark is a valuable investment for anyone working with big data. Whether you're a data engineer, data scientist, or business analyst, knowledge of Spark: PySpark can help you and your business extract valuable insights and make better-informed decisions. Don't miss this opportunity to enhance your skills and advance your career.