Functional Programming in Scala Specialization Course Syllabus

Overview: This specialization offers a comprehensive journey into functional programming using Scala, designed for professionals seeking to master modern programming techniques. The course spans approximately 170 hours of content, divided into five core courses followed by a capstone project. Learners will progress from foundational concepts to advanced topics such as parallel programming and big data analysis with Apache Spark. With a flexible schedule, the program accommodates working professionals while emphasizing hands-on learning through practical projects and real-world applications.

Module 1: Functional Programming Principles in Scala

Estimated time: 56 hours

• Introduction to functional programming and Scala basics
• Recursion and structural induction
• Pattern matching and case classes
• Higher-order functions and function composition

Module 2: Functional Program Design in Scala

Estimated time: 35 hours

• Leveraging immutability and persistent data structures
• Lazy evaluation and streams
• Monads and their role in functional design
• Type-directed programming and implicit parameters

Module 3: Parallel Programming

Estimated time: 32 hours

• Foundations of parallel and concurrent computing
• Designing parallel algorithms
• Using Scala’s parallel collections for performance

Module 4: Big Data Analysis with Scala and Spark

Estimated time: 27 hours

• Introduction to Apache Spark and distributed computing
• Processing large datasets using Spark RDDs and DataFrames
• Applying functional programming techniques in Spark transformations

Module 5: Capstone Project: Functional Programming in Scala

Estimated time: 20 hours

• Designing a data-intensive application using Scala
• Integrating functional programming principles with real-world datasets
• Implementing scalable processing with Spark

Module 6: Final Project

Estimated time: 20 hours

• Deliverable 1: Functional Scala application design
• Deliverable 2: Implementation of parallel data processing
• Deliverable 3: Analysis of big data using Spark and functional techniques

Prerequisites

• Familiarity with basic programming concepts
• Understanding of object-oriented programming
• Basic knowledge of data structures and algorithms

What You'll Be Able to Do After

• Write purely functional programs using recursion, pattern matching, and higher-order functions
• Design immutable data structures and understand their applications
• Implement parallel algorithms and leverage parallel collections for performance gains
• Manipulate and analyze big data using Apache Spark and Scala
• Apply functional programming principles to real-world data-intensive applications