Spark and Scala Course with Certification

11 Lesson

40 Hours

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igmGuru offers industry-focused Spark and Scala Training Online designed to help learners build strong expertise in Apache Spark and Scala programming. The course content is created by certified professionals with more than 20 years of experience in Big Data and Apache Spark technologies. In this Spark and Scala course, you will learn important concepts, including Apache Spark Architecture, Scala Programming, RDDs, DataFrames, Spark SQL, and more. Upon successful completion of the training, learners can prepare for the Spark and Scala Certification Exam and enhance their career opportunities with a recognized certification.

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Apache Spark and Scala Course Overview

Apache Spark and Scala are widely used technologies for big data processing and analytics, helping organizations manage large datasets, improve data performance, and build scalable data solutions. By the end of this course, you will be able to develop efficient data pipelines and work on real-world big data projects.

Prerequisites

Basic knowledge of programming (any language like Java, Python, or C++)
Understanding of databases and SQL fundamentals
Familiarity with basic data concepts (tables, records, queries)
Basic knowledge of Linux or command-line usage (recommended)

Who Should Enroll in the Spark Scala Course Online

Freshers interested in big data and data engineering
Software developers working with Spark and Scala
Data analysts handling large datasets
ETL developers upgrading to modern tools
IT professionals working on data processing

What You Will Learn In This Spark Scala Online Training?

The following are the essential skills you will acquire during the Spark Scala training program

Understand Apache Spark architecture and core components
Write programs using Scala for big data processing
Work with RDDs, DataFrames, and Datasets in Spark
Perform data transformations and actions on large datasets
Use Spark SQL for structured data processing
Build batch and real-time data pipelines using Spark Structured Streaming
Work with file formats like Parquet, ORC, and Avro
Understand Delta Lake and modern data lakehouse concepts
Deploy and run Spark on cloud platforms like AWS, Azure, and Databricks
Apply performance tuning techniques using caching, partitioning, and optimization tools

Job Roles After Spark Scala Training

Upon successful completion of the training, you can apply for the following job roles:

Big Data Engineer
Data Engineer
Apache Spark Developer
Scala Developer
Data Analyst
ETL Developer

Key Features

Instructor Led Training : 40 Hrs
1 On 1 Training Option Available
24 X 7 Lifetime Support & Access
Small Batches Upto 10 Participants
Experienced & Professional Trainers
Get Certified & Get Placed

Spark and Scala Training Modules

Lesson 1 - Introduction to Big Data & Apache Spark

1. Big Data concepts and challenges

2. Batch vs Real-time data processing

3. Hadoop ecosystem overview (HDFS, YARN)

4. Limitations of MapReduce

5. Introduction to Apache Spark ecosystem

6. Spark components: Core, SQL, Streaming, MLlib, GraphX

Lesson 2 - Scala Programming Fundamentals

1. Introduction to Scala

2. Scala vs Java

3. Variables, Data Types, Operators

4. Control structures (if, loops)

5. Functions and recursion

6. Object-Oriented Programming (OOP) in Scala

7. Functional Programming concepts

8. Collections (List, Set, Map)

Lesson 3 - Spark Architecture & Setup

1. Spark architecture (Driver, Executors, Cluster Manager)

2. Spark execution model

3. DAG (Directed Acyclic Graph

4. Lazy evaluation

5. Installing Spark and Scala

6. Running Spark applications (Local & Cluster mode)

Lesson 4 - Spark Core (RDD)

1. Introduction to RDD (Resilient Distributed Dataset)

2. Creating RDDs

3. Transformations and Actions

4. Key operations: map, filter, reduce

5. RDD persistence and caching, Partitioning and parallelism

6. Handling shared variables (Broadcast, Accumulators)

Lesson 5 - Spark SQL, DataFrames & Datasets

1. Introduction to Spark SQL

2. DataFrames and Datasets

3. Schema inference and data types

4. Reading and writing data (JSON, CSV, Parquet, Hive)

5. SQL queries on DataFrames

6. Joins, aggregations, window functions

7. Catalyst optimizer basics

Lesson 6 - Data Processing & Integration

1. Working with structured and unstructured data

2. Data ingestion techniques

3. Integration with Hive and external databases

4. ETL processing using Spark, Handling large-scale datasets

Lesson 7 - Spark Streaming (Real-Time Processing)

1. Introduction to Spark Streaming

2. DStreams vs Structured Streaming

3. Streaming architecture, Window operations

4. Stateful stream processing

5. Integration with Kafka, Flume and Building real-time pipelines

Lesson 8 - Machine Learning with MLlib

1. Introduction to MLlib

2. Supervised vs Unsupervised learning

3. Classification (Logistic Regression, Decision Trees)

4. Clustering (K-Means), Feature engineering, ML pipelines

Lesson 9 - Graph Processing with GraphX

1. Introduction to GraphX

2. Graph concepts (Vertices, Edges) and Graph processing use cases

3. Basic graph algorithms

Lesson 10 - Spark Performance Optimization

1. Performance tuning techniques and Memory management

2. Partitioning strategies and Broadcast joins

3. Caching strategies and Debugging Spark jobs

Lesson 11 - Deployment & Cluster Management

1. Running Spark on YARN, Mesos, Kubernetes

2. Spark on cloud (AWS, Databricks)

3. Job scheduling and monitoring

4. Logging and debugging

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Spark Scala Online Course Fees

Online Class Room Program

US $ 799.00

100% Money Back Guarantee

Duration : 40 Hrs
Plus Self Paced

Classes Starting From

Fast Track Batch 02 Jun 2026
Weekday Batch 08 Jun 2026
Weekend Batch 06 Jun 2026

Corporate Training

Customized Training Delivery Model
Flexible Training Schedule Options
Industry Experienced Trainers
24x7 Support

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Apache Spark Scala Certification Exam

Our Spark and Scala Training prepares you for the Databricks Certified Associate Developer for Apache Spark certification, which is the most recognized and industry-standard credential for Apache Spark professionals.

Official Certification Exam Name: Databricks Certified Associate Developer for Apache Spark

Exam Details

Duration: 90 minutes
Number of Questions: ~60 multiple-choice questions
Passing Score: Around 70%
Exam Format: Multiple-choice and scenario-based questions
Mode: Online proctored exam
Exam Cost: $200 USD (approx.)

Also, upon successful completion of this Online Spark and Scala Course, you will receive an igmGuru Course Completion Certificate to validate your skills in Spark and Scala.

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Spark and Scala Course with Certification