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Mastering Scala with Apache Spark for the Modern Data Enterprise (TTSK7520)

Name: Mastering Scala with Apache Spark for the Modern Data Enterprise (TTSK7520)
Availability: InStock
Rating: 4.6 (5878 reviews)

4.6 out of 5 rating
Last updated : 23/07/2026
English

Available as Instructor Led Training, Live Online & In Person at your Offices or Ours.

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Duration:

40.00 hours

32.5 CPD hours

Overview:

®Mastering Scala with Apache Spark for the Modern Data Enterprise®is a five day hands-on course designed to provide you with the essential skills and tools to tackle complex data projects using Scala programming language and Apache Spark, a high-performance data processing engine. Mastering these technologies will enable you to perform a wide range of tasks, from data wrangling and analytics to machine learning and artificial intelligence, across various industries and applications.

Description:

Embark on a journey to master the world of big data with our immersive course on Scala and Spark! Mastering Scala with Apache Spark for the Modern Data Enterprise is a five day hands-on course designed to provide you with the essential skills and tools to tackle complex data projects using Scala programming language and Apache Spark, a high-performance data processing engine. Mastering these technologies will enable you to perform a wide range of tasks, from data wrangling and analytics to machine learning and artificial intelligence, across various industries and applications.
Guided by our expert instructor, you'll explore the fundamentals of Scala programming and Apache Spark while gaining
valuable hands-on experience with Spark programming, RDDs, DataFrames, Spark SQL, and data sources. You'll also explore Spark Streaming, performance optimization techniques, and the integration of popular external libraries, tools, and cloud platforms like AWS, Azure, and GCP. Machine learning enthusiasts will delve into Spark MLlib, covering basics of machine learning algorithms, data preparation, feature extraction, and various techniques such as regression, classification, clustering, and recommendation systems.
You'll also gain experience working with graph processing using Spark GraphX, as well as innovative generative AI
technologies, integrating GPT with Spark and Scala for practical applications. Time permitting, you will also be introduced to Spark NLP, covering text preprocessing, classification, and sentiment analysis. With a focus on practical skills and best practices, you'll work on interesting learning objectives and gain hands-on experience with innovative tools in a live, interactive environment.
Upon completing this course, you'll be ready to confidently apply your newly acquired Scala and Apache Spark skills to a wide range of projects. You'll be able to develop efficient and scalable applications, harness the power of machine learning, and analyze large datasets, giving you a competitive edge in the rapidly evolving world of big data and analytics. By integrating these technologies into your daily work, you'll be better prepared to solve complex problems, streamline processes, and ultimately drive value for your organization.

Course Outline:

Introduction to Scala
Brief history and motivation
Differences between Scala and Java
Basic Scala syntax and constructs
Scala's functional programming features
Introduction to Apache Spark
Overview and history
Spark components and architecture
Spark ecosystem
Comparing Spark with other big data frameworks
Lab: Practice basic Scala syntax and functional programming concepts using the REPL.
Setting up the Development Environment
Basics of Spark Programming SparkContext and SparkSession
Resilient Distributed Datasets (RDDs)
Transformations and Actions
Working with DataFrames
Spark SQL and Data Sources
Spark SQL library and its advantages
Structured and semi-structured data sources
Reading and writing data in various formats (CSV, JSON, Parquet, Avro, etc.)
Data manipulation using SQL queries
Lab: Setting up the Environment and Running a Simple Spark Application.
Lab: Load and query data from different data sources using Spark SQL.
Data Processing and Spark Programming

Basic RDD Operations
Creating and manipulating RDDs
Common transformations and actions on RDDs
Working with key-value data
Basic DataFrame and Dataset Operations
Creating and manipulating DataFrames and Datasets
Column operations and functions
Filtering, sorting, and aggregating data
Lab: RDD and DataFrame Operations
Introduction to Spark Streaming
Overview of Spark Streaming
Discretized Stream (DStream) operations
Windowed operations and stateful processing
Performance Optimization Basics
Best practices for efficient Spark code
Broadcast variables and accumulators
Monitoring Spark applications
Integrating External Libraries and Tools, Spark Streaming
Using popular external libraries, such as Hadoop and HBase
Integrating with cloud platforms: AWS, Azure, GCP
Connecting to data storage systems: HDFS, S3, Cassandra, etc.
Lab: Building an End-to-End Spark Application: Create a Spark application to process a large dataset, perform aggregations, and save the results.
Lab: Implement a simple Spark Streaming application to process real-time data.
Machine Learning Basics with Spark MLlib

Introduction to Machine Learning Basics
Overview of machine learning
Supervised and unsupervised learning
Common algorithms and use cases
Introduction to Spark MLlib
Overview of Spark MLlib
MLlib's algorithms and utilities
Data preparation and feature extraction
Lab: Data Preparation with Spark MLlib
Linear Regression and Classification
Linear regression algorithm
Logistic regression for classification
Model evaluation and performance metrics
Clustering Algorithms
Overview of clustering algorithms
K-means clustering
Model evaluation and performance metrics
Collaborative Filtering and Recommendation Systems
Overview of recommendation systems
Collaborative filtering techniques
Implementing recommendations with Spark MLlib
Lab: Basic Machine Learning with Spark MLlib
Lab: Implementing a Recommendation System
Graph Processing and Generative AI Technologies

Introduction to Graph Processing
Overview of graph processing
Use cases and applications of graph processing
Graph representations and operations
Introduction to Spark GraphX
Overview of GraphX
Creating and transforming graphs
Graph algorithms in GraphX
Lab: Graph Processing with GraphX
Big Data Innovation! Using GPT and Generative AI Technologies with Spark and Scala
Overview of generative AI technologies
Integrating GPT with Spark and Scala
Practical applications and use cases
Bonus Topics / Time Permitting

Introduction to Spark NLP
Overview of Spark NLP
Preprocessing text data
Text classification and sentiment analysis
Lab: Generative AI Technologies and Spark NLP: Integrate GPT for text generation in a Spark application and explore basic NLP tasks using Spark NLP.
Lab: Text Classification with Spark NLP
Putting It All Together
Work on a capstone project that integrates multiple aspects of the course, including data processing, machine learning, graph processing, and generative AI technologies.

Available Delivery Options for Mastering Scala with Apache Spark for the Modern Data Enterprise (TTSK7520)

Live Instructor Led Classroom Online (Live Online)
Traditional Instructor Led Classroom training (TILT/ILT)
Delivery at your offices in United Kingdom
Private dedicated course for your staff

How many CPD hours does Mastering Scala with Apache Spark for the Modern Data Enterprise (TTSK7520) provide?

The 5 day Mastering Scala with Apache Spark for the Modern Data Enterprise (TTSK7520) course gives you up to 32.5 CPD hours/structured learning hours.

Who is the correct audience for Mastering Scala with Apache Spark for the Modern Data Enterprise (TTSK7520)?

This intermediate and beyond level course is geared for experienced technical professionals in various roles, such as developers, data analysts, data engineers, software engineers, and machine learning engineers.
Practical programming experience is required.

Do you provide training for Mastering Scala with Apache Spark for the Modern Data Enterprise (TTSK7520)?

Yes, we provide corporate training, dedicated training and closed classes for Mastering Scala with Apache Spark for the Modern Data Enterprise (TTSK7520). This can take place anywhere in United Kingdom including London, Manchester, Birmingham, Edinburgh or live online.

What is the duration of Mastering Scala with Apache Spark for the Modern Data Enterprise (TTSK7520)?

The Mastering Scala with Apache Spark for the Modern Data Enterprise (TTSK7520) training takes place over 5 day(s), with each day lasting approximately 40.00 hours including breaks.

What other terms do people search for?

Popular related searches include: Scala; Spark; Data Science

Why are Nexus Human the best provider for Mastering Scala with Apache Spark for the Modern Data Enterprise (TTSK7520)?

Nexus Human are recognised as one of the best training companies. Our trainers have won awards including Small Firms Best Trainer, national training partner of the year for Ireland, and global top 30 instructor awards in 2012, 2019 and 2021.

Is there a discount code for Mastering Scala with Apache Spark for the Modern Data Enterprise (TTSK7520)?

Yes, the discount code PENPAL5 is currently available for Mastering Scala with Apache Spark for the Modern Data Enterprise (TTSK7520) training. Only one discount code can be used per booking.

DURATION 1 Day

No scheduled classes available at this time.

Training Insurance Included!

When you organise training, we understand that there is a risk that some people may fall ill, become unavailable.

To mitigate the risk we include training insurance for each delegate enrolled on our public schedule, they are welcome to sit on the same Public class within 6 months at no charge, if the case arises.