Language: English
Duration: 40 hours
Course Description
In today’s data-driven world, organizations are generating vast volumes of data at unprecedented speeds. To turn this raw information into actionable insights, professionals need powerful tools and skills in big data processing. The Big Data Analysis with Scala and Apache Spark course is designed to equip learners with the essential knowledge and hands-on experience to harness the power of big data technologies.
This comprehensive course introduces you to Apache Spark, one of the most widely used big data processing frameworks, known for its speed, scalability, and flexibility. You will learn to develop data processing applications using Scala, a concise and expressive programming language that is deeply integrated with the Spark ecosystem.
Pre Requisites
- Basic programming knowledge (Java, Python, or Scala preferred)
- Understanding of variables, loops, functions, and OOP concepts
- Basic knowledge of SQL
- Familiarity with data processing concepts (recommended)
- No prior experience with Big Data, Scala, or Spark required
Course Objectives
- Understand Big Data concepts and the role of Scala & Spark in data engineering.
- Write Scala code for functional and object-oriented programming.
- Use Spark SQL, DataFrames, and MLlib for structured and machine learning workflows.
- Implement real-time stream processing with Spark Streaming & Kafka.
- Optimize Spark jobs for performance in distributed environments.
Course Outline
- Introduction to Big Data Analysis
- Getting Started with Scala
- Introduction to Apache Spark
- Working with Spark DataFrames
- Spark SQL and Data Processing
- Spark Streaming
- Machine Learning with Spark MLlib
- Graph Processing with Spark GraphX
- Performance Optimization and Tuning
- Real-Time Big Data Processing
- Advanced Topics in Spark
- Scala and Spark Integration
