Powered by
Completion
CERTIFICATE
Data Streaming and NLP with PySpark
This course is part of PySpark for Data Science.
Course Cost
Free course
Intermediate
Skill Level
16 Hours
Self-paced lessons
This course explores data streaming and Natural Language Processing (NLP) using the power of PySpark distributed computing. Through comprehensive modules, you'll gain practical skills to build scalable data-streaming applications and perform advanced NLP tasks on large datasets. You'll learn to analyze real-time data streams, implement Spark's Structured Streaming for fault-tolerant processing, and apply sophisticated NLP techniques for text analysis. The course covers stream processing fundamentals, Spark Streaming architecture, Structured Streaming operations, deep learning integration, and optimization strategies. With hands-on assignments and projects, you'll develop expertise in designing data pipelines, processing streaming data efficiently, and communicating insights through visualizations. This knowledge is essential for modern data professionals working with big data and real-time analytics applications.
What you'll learn
Analyze streaming data to extract insights and trends in real-time applications
Design and implement data pipelines for real-time streaming sources
Implement advanced data processing techniques with PySpark for large-scale datasets
Evaluate different NLP techniques for data processing and sentiment analysis
Create interactive visualizations to communicate insights from streaming data
Apply fault-tolerant processing using Spark's Structured Streaming
Skills you'll gain
This course includes:
7.3 Hours PreRecorded video
16 assignments
Access on Mobile, Tablet, Desktop
Batch access
Shareable certificate
Get a Completion Certificate
Share your certificate with prospective employers and your professional network on LinkedIn.
CREATED BY
PROVIDED BY
Get a Completion Certificate
Share your certificate with prospective employers and your professional network on LinkedIn.
CREATED BY
PROVIDED BY
Top companies offer this course to their employees
Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.
There are 5 modules in this course
Data Streaming and NLP with PySpark equips learners with skills to build scalable data pipelines and perform advanced natural language processing on large datasets. The course covers stream processing fundamentals, Spark Streaming architecture and evolution, Structured Streaming programming models, input sources, transformations, and output sinks. Students also explore deep learning integration with PySpark, NLP techniques including tokenization, lemmatization, and TF-IDF, and optimization strategies for performance tuning. Through hands-on labs and practical assignments, learners gain experience in processing real-time data streams, implementing window operations, handling failures with checkpointing, and creating interactive visualizations to communicate insights effectively.
Stream Processing with Apache Spark
Module 1 · 3 Hours to complete
Spark Streaming
Module 2 · 2 Hours to complete
Foundations of Structured Streaming
Module 3 · 4 Hours to complete
Spark NLP
Module 4 · 4 Hours to complete
Course-Wrap up and Assessment
Module 5 · 1 Hours to complete
Reviews
Testimonials and success stories are a testament to the quality of this program and its impact on your career and learning journey. Be the first to help others make an informed decision by sharing your review of the course.
Faculties
These are the expert instructors who will be teaching you throughout the course. With a wealth of knowledge and real-world experience, they're here to guide, inspire, and support you every step of the way. Get to know the people who will help you reach your learning goals and make the most of your journey.
44,228
Students
47
Courses
Frequently asked Questions
Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.