Introduction to Functional and Stream Programming for Big Data Systems
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Brief Introduction
An introduction to the basic concepts of functional programming (FP) and its application to stream and distributed processing of large volumes of dataCourse Summary
Learn about functional and stream programming in big data systems. This course will teach you how to develop scalable and efficient data processing systems using functional programming concepts and stream processing techniques.Key Learning Points
- Understand functional programming concepts and how they can be applied to big data systems
- Learn about stream processing techniques and how to use them to develop efficient data processing systems
- Develop skills in using popular big data processing frameworks such as Spark and Flink
Related Topics for further study
Learning Outcomes
- Develop scalable and efficient data processing systems using functional programming concepts and stream processing techniques
- Understand the advantages and limitations of functional programming in big data systems
- Gain proficiency in using Spark and Flink for big data processing
Prerequisites or good to have knowledge before taking this course
- Basic knowledge of programming concepts
- Familiarity with at least one programming language
Course Difficulty Level
IntermediateCourse Format
- Online Self-Paced
- Video Lectures
- Hands-On Exercises
Similar Courses
- Big Data Analytics
- Data Science Essentials
- Machine Learning with TensorFlow on Google Cloud Platform
Related Education Paths
Notable People in This Field
- Chief Architect, Cloudera
- Creator of Scala programming language
Related Books
Description
Course description
This course is an introduction to the basic concepts of functional programming (FP) and its application to stream and distributed processing of large volumes of data. As the explosion of available social, internet of things (IoT), device, marketing, and other types of data continues at an ever increasing rate, it becomes paramount to be able to process and analyze this data in real time. In order to do that, highly scalable systems have to be designed and developed that are capable of performing data- and compute-intensive operations in a distributed manner over hundreds of physical servers. This course focuses on building the foundation of such systems, which are applications capable of processing data in a highly parallel fashion. In this course, students learn core FP concepts and basic design patterns, understand how they are used as a foundation of parallel and distributed programming, and learn how to apply these concepts and foundations to stream processing of big data volumes. Students get hands-on experience writing basic functional programs and using them for stream processing.
Summary of User Reviews
Discover the world of functional and stream programming for big data systems with Harvard's online course. Students were impressed with the course content, structure, and the expertise of the instructors. However, some users found the course difficult to follow and recommended prior knowledge of programming.Key Aspect Users Liked About This Course
The course content was comprehensive and well-structured.Pros from User Reviews
- Great course content
- Expert instructors
- In-depth coverage of functional and stream programming
- Engaging exercises and projects
- High-quality video lectures
Cons from User Reviews
- Challenging for beginners
- Requires prior knowledge of programming
- Some topics are covered too quickly
- Limited interaction with instructors
- Not enough practical examples
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