Apache Spark and Scala Course - Classroom
1.995,00 EUR
- 24 hours
Unlock the full potential of big data by mastering Apache Spark with Scala—one of the most powerful combinations in modern data engineering. This hands-on course is designed to help you process, analyze, and derive insights from massive datasets using Spark’s high-speed, in-memory computing capabilities. You’ll learn how to build scalable data pipelines, perform real-time analytics, and implement machine learning models—all while developing strong programming skills in Scala.
Key Features
Language
Course material in English
Level
Beginner - intermediate level
24 hours of instructor-led, hands-on training
50+ hours recommended study time
3 real-world projects for practical application
70+ hours of quizzes, assignments, and practice material
Practical labs with real-world datasets
Coverage of Spark ecosystem tools like Spark SQL, MLlib, and Streaming
Hands-on experience with Scala programming
Expert mentorship and guidance throughout the course
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Program completion certification included
Learning Outcomes
At the end of this program, you will be able to:
Big Data Fundamentals
Develop a solid understanding of big data concepts, key components, and frameworks, including Hadoop architecture and its operating modes.
Introduction to Scala
Learn the fundamentals of Scala programming, including its core syntax and concepts required for working with Apache Spark.
Introduction to Spark
Understand the core principles of Apache Spark and how to build and run Spark applications.
Spark Framework & Deployment
Explore the Spark framework in depth, including its architecture and different deployment approaches.
Spark Data Structures
Work with Spark’s internal data structures such as RDDs, and use APIs and Scala functions to create and transform data.
Spark Ecosystem
Gain hands-on experience with key components of the Spark ecosystem, including Spark SQL, Streaming, MLlib, GraphX, and more.
Course timeline
Introduction to Big Data, Hadoop, and Spark
Lesson 1
- Big data concepts and real-world use cases
- Hadoop ecosystem and HDFS
- Cluster architecture and YARN
- Batch vs real-time processing
- Introduction to Spark and its advantages
Introduction to Scala
Lesson 2
- Scala basics and REPL
- Variables, control structures, and functions
- Collections (Array, Map, Lists, Tuples)
- Scala in big data ecosystems
Object-Oriented & Functional Programming in Scala
Lesson 3
- Classes, objects, and packages
- Traits and inheritance
- Functional programming concepts
- Higher-order functions and error handling
Scala Collection APIs
Lesson 4
- Collection types and hierarchies
- Performance characteristics
- Java interoperability
- Using Scala implicits
Introduction to Spark & RDDs
Lesson 5
- Spark architecture and setup
- Spark applications and Spark shell
- RDD (Resilient Distributed Datasets)
- Data transformations and actions
- Caching and persistence
- Loading and saving data
Spark SQL & Data Processing
Lesson 6
- Spark SQL architecture
- DataFrames and Datasets
- Working with JSON and Parquet
- User-defined functions (UDFs)
- Integration with Hive
Machine Learning with Spark MLlib
Lesson 7
- Introduction to machine learning concepts
- MLlib features and tools
- Supervised and unsupervised algorithms
- Linear regression, decision trees, random forests
- Clustering techniques
Streaming with Kafka and Flume
Lesson 8
- Real-time data processing concepts
- Kafka architecture and cluster setup
- Data ingestion and streaming pipelines
Who Should Enroll in this Program?
Prerequisites
- Basic understanding of SQL and databases
- Familiarity with programming (Python, Java, or Scala recommended)
- Basic knowledge of Linux/Unix (helpful but not mandatory)
- Exposure to Hadoop concepts is beneficial but not required
Data Scientists and Data Engineers
Data Analysts and BI Professionals
Software Developers and Architects
Research professionals working with data
Statements
Licensing and accreditation
The course is offered according to Partner Program Agreement and complies with the License Agreement requirements.
Equity Policy
Candidates are encouraged to reach out to AVC for guidance and support throughout the accommodation process.
Frequently Asked Question
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