Programming for Big Data
Description
Essential programming skills and languages required for big data analytics including Python, R, SQL, Java, and Scala with focus on data manipulation, analysis, and distributed computing.
Learning Objectives
Students will develop proficiency in multiple programming languages essential for big data analytics, implement data processing algorithms, write efficient code for large-scale data manipulation, use programming libraries and frameworks for data analysis, and develop applications for distributed computing environments using modern programming paradigms.
Topics (8)
R programming fundamentals and advanced techniques for statistical computing and data analysis in big data environments.
Advanced SQL techniques adapted for big data environments including distributed query processing and optimization strategies.
Java programming principles and practices for building scalable, enterprise-grade big data applications and distributed systems.
Scala programming fundamentals and advanced techniques optimized for Apache Spark big data processing framework development.
Functional programming concepts and their applications in big data processing for creating more reliable and scalable data processing solutions.
Advanced data structures and algorithmic techniques specifically designed for handling and processing large volumes of data efficiently.
Comprehensive Python programming skills specifically tailored for big data analytics including data structures, libraries, and frameworks.
Software development best practices including version control, collaboration tools, and project management methodologies for big data projects.