Certified Spark and Scala Training course from DataFlair provides in-depth theoretical knowledge coupled with strong practical skills to enable you enhance your competence in Big Data Spark.
30+ Hrs of instructor-led sessions
100+ Hrs of practicals & assignments
5 Real-time apache spark projects
Lifetime access to course with support
Job oriented course with job assistance
★★★★★Reviews | 11079 Learners
Offers: Get HDFS & Java courses free with instructor-led Course
About Spark and Scala Course
Apache Spark and Scala online training course is designed by industry experts as per market standards to make you quite apt to advance your career in 2nd Gen Big Data Tool as thousands of other professionals have already done by joining spark course.
Become certified Spark developer by mastering the concepts of Spark and its ecosystem, RDD, Spark Streaming, MLlib GraphX, Spark SQL and Scala. Individual topics are explained using multiple workshops to provide hands-on knowledge. Spark online course also includes spark real life use-cases, multiple POCs and real time Spark project to make you ready to take Apache Spark jobs in India, US, UK, Europe, Singapore, etc.
Objectives of Online Apache Spark and Scala Training
- Understand problems with Hadoop Map Reduce
- Learn how Apache Spark provides solution to these Big data challenges
- Grasp the concepts of Scala and learn their implementation
- Become adept in Apache Spark and Spark installation
- Understand the Apache Spark architecture
- Play with Spark RDDs – Transformation, Action, Load
- Learn how to handle in-memory data efficiently
- Develop complex real-time Apache Spark applications
- Master the concepts of Spark stream analytics
- Learn Apache Spark streaming APIs for streaming of data
- Learn MLlib APIs in Spark for machine learning algorithms
- Understand Spark GraphX APIs to implement graph algorithms
- Work on live Spark project to get hands-on experience
Prerequisites to attend Apache Spark Training
Basic Knowledge of Java or Scala is required to learn Spark. In case you feel any need to brush up these technologies, Java & Scala courses will be added in your LMS as complimentary with this Apache Spark course.
Upcoming Batch Schedule
|22 Dec – 13 Jan||07.00 AM – 10.00 AM IST
8.30 PM – 11.30 PM EST
|12 Jan – 3 Feb||05.00 PM – 08.00 PM IST
6.30 AM – 9.30 AM EST
Why you should learn Apache Spark and Scala
Average salary of Big Data Spark Developers is $135k -Indeed
There will be a shortage of 1.5M Big Data experts by 2018 -McKinsey
Big Data market will reach $99B by 2022 at the CAGR of 42% -Forbes
More than 77% of organizations consider Big Data a top priority -Peer Research
What will you get from this Spark and Scala online Course
30+ hrs of live online instructor-led sessions by industry veterans
Industry renowned Apache Spark certification to give boost to your resume
100+ hrs of Spark practicals, workshops, labs, and assignments
Personalized one to one career discussion directly with the trainer
Real life Spark case studies and live project to solve real problem
Mock interview & resume preparation to excel in Spark interviews
Lifetime access to Spark course, study materials, ppts, manuals, practical codes
Premium Spark job assistance and support to step ahead in your career
Discussion forum for resolving your Spark queries & interacting with fellow batch-mates
Auto Upgradation of the Spark course and study material in the LMS to latest version
Who should go for this Apache Spark Online Course
YOU, yes you should go for this course if you are looking to advance your Big Data career with Apache Spark. This course will be useful for:
- Software engineers and project managers
- BI, ETL and data warehousing professionals
- Mainframe and testing professionals
- Business analysts and architects
- DBAs, Analytics and DW professionals
- Any graduate focusing to build career in Apache Spark and Scala
Apache Spark Course Curriculum
- What is Scala
- Setup and configuration of Scala
- Develop and run basic Scala Programs
- Scala operations
- Functions and procedures in Scala
- Different Scala APIs for common operations
- Loops and collections Array, Map, Lists, Tuples
- Pattern matching for advanced operations
- Eclipse with Scala
- Introduction to object oriented programming
- Different oops concepts
- Constructor, getter, setter, singleton, overloading and overriding
- Nested Classes, Visibility Rules
- Functional Structures
- Functional programming constructs
- Call by Name, Call by Value
- Introduction to Big Data
- Challenges with old Big Data solutions
- Batch vs Real-time vs in-Memory processing
- MapReduce and its limitations
- Apache Storm and its limitations
- Need for general purpose solution – Apache Spark
- What is Apache Spark?
- Internals of Spark architecture
- Apache Spark design principles
- Spark features and characteristics
- Apache Spark Eco-system components and their insights
- Setup of Spark Environment
- Install and configure prerequisites
- Installation of Apache Spark in local mode
- Work with Spark in local mode
- Troubleshooting the encountered problems
- Installation of Spark in standalone mode
- Installation of Spark in YARN mode
- Installation & configuration of Spark on a real multi-node cluster
- Play with Spark in cluster mode
- Best practices for Spark deployment
- Play with Spark shell
- Execute Scala and Java statements in shell
- Understand Spark Context and driver
- Read data from local filesystem
- Integrate Spark with HDFS
- Cache the data in memory for further use
- Distributed persistence
- Testing and troubleshooting
- What is RDD in Spark
- How RDDs make Spark a feature rich framework
- Transformations in Apache Spark RDDs
- Spark RDDs action and persistence
- Spark Lazy operations - Transformation as well as Caching
- Fault tolerance in Spark
- Load data and create RDD in Spark
- Persist RDD in memory or disk
- Pair operations and key-value in Spark
- Spark Integration with Hadoop
- Apache Spark practicals and workshops
- Need for stream analytics
- Comparison with Storm and S4
- Real-time data processing using Spark streaming
- Fault tolerance and check-pointing
- Stateful Stream Processing
- DStream and window operations
- Spark Stream execution flow
- Connection to various source systems
- Performance optimizations in Spark
- What is Spark SQL
- Apache Spark SQL Features and Data flow
- Spark SQL architecture and components
- Hive and Spark SQL together
- Play with Data frames and Data states
- Data loading techniques in Spark
- Hive Queries through Spark
- Various Spark SQL DDL and DML operations
- Performance tuning in SparK
- Need for Machine Learning
- Introduction to Spark machine learning
- Various Spark ML libraries
- Algorithms for clustering, statistical analytics, classification etc.
- Introduction to GraphX
- Need for different graph processing engine
- Graph handling using Apache Spark
Apache Spark Projects
Set Top Box Data Analysis
Analyze Set Top Box data and generate various insights about the smart tv usage pattern. The objective of the project is to analyze set top box media data and generate patterns of channel navigation, VOD, etc.. The data contains details about users’ activities like tuning a channel, duration, browsing for videos, purchase video using VOD (video on demand), etc.
Twitter Trends Analysis
Collect Twitter data in real-time and find out what is currently trending on twitter in various categories. In this project, we will collect live Twitter streams and analyze the same using Spark Streaming to generate insights like finding the current trends in Politics, Finance, Entertainment, etc.
Titanic Data Analysis
Titanic was one of the biggest disasters in the history of mankind, which happened due to natural events and human mistakes. The objective is to analyze Titanic data sets and generate various insights related to age, gender, survived, class, emabrked, etc.
Ecommerce Reviews Analysis
Analyze the Ecommerce review data and generate various insights of products, companies can use these reports / patterns and understand the sentiments of users about their product. Ecommerce reviews contain fields like product-Id, star rating, reviews, timestamp, reviewer-Id, etc.
YouTube Data Analysis
Analyze the YouTube Data and generate insights like top 10 most videos in various categories, User demographics, no of views, ratings etc. The data contains fields like Id, Age, Catagory, Length, Views, ratings, comments, etc.
Extensive hands-on practicals
No of Projects
Discussion Forum Access
Complementary Job Assistance
Resume & Interview Preparation
Interaction in Live class
Personalized career guidance
Yes, in recordings & in LMS
Through discussion forum
Yes, post course completion
Java, with lifetime access
Live Online with Trainer
Yes, live with instructor & in LMS
Yes, with support
In regular sessions
Yes, post course completion
Java & HDFS, with lifetime access
100% interactive classes
Yes, from instructor
On completion of Apache Spark training course, DataFlair’s job grooming program will help you in resume building and interview preparation. Mock interviews and resume referrals will make you job ready to excel in the interviews.
Build a favourable impression with the resume that stands out.
Get connected with top employers to boost your career prospects.
Make yourself job ready with multiple in-depth mock interviews.
Get ready to work from day one with multiple projects & best practices
Companies you could land up with
Corporate Clients /
Offers made to
Hours of classes
Spark Training FAQs
All our sessions will be recorded and recordings will be uploaded in LMS immediately as the session gets over. You can go through it and get your queries cleared from the instructor in next session. Alternatively, you can attend the missed Spark training online session in any other batch running in parallel.
To do Spark and Scala practicals, Instructor will help you in setting virtual lab on your own system. Manual to set virtual lab will be available in your LMS if you want to go through the steps again. Virtual lab can be set on MAC or Windows machine also.
You will have lifetime access to the spark and scala training course, recorded sessions along with the complete study material, POCs, project etc.
You just need a laptop or PC with a good internet connection of around 1 MBPS (But lesser speed of 512 KBPS will also work) for joining online classes. Broadband connection is recommended but you can connect through data card as well.
During session, you can get your doubts cleared from the instructor immediately. After the session, you can get your doubts cleared from the instructor in the next session as before starting any session, instructor spends sufficient time for doubt clearing. Post training, you can post your query over discussion forum and our support team will assist you. Still if you are not comfortable, you can drop mail to instructor or directly interact with him.
Immediately with your enrolment for the spark and scala course, you will get access to LMS and then it will be there for lifetime. Complimentary course will also be added that time only so that you can start learning immediately.
Our online Spark training includes in-depth theoretical knowledge, multiple workshops, POCs, project etc. that will prepare you to the level that you can start working from day 1 wherever you go. You will be assisted in resume preparation and Mock interview that will help you in getting ready to face interviews. We will also guide you with the Spark job openings matching your resume. All this will help you in landing your dream job in Big Data industry requiring Spark skills.
You will be equipped with theoretical and practical skills that industry is looking for and will become certified Apache Spark and Scala professional who is ready to take Big Data with Spark Projects in top organisations.
You can interact to the instructor via voice or chat during live training.
This is completely Spark online training with 8-10 students per batch. Individual interaction will be there with all. The trainer ensures that every student is clear of all the concepts taught before proceeding ahead. So there will be complete environment of Spark classroom learning.
Yes, you can enroll for the Spark Scala course at any time and join any batch starting thereafter.
Hadoop is not at all mandatory to learn Spark. We will provide basic knowledge on both Hadoop and Java if you want to brush your skills.
Apache Spark is one of the fastest growing community in IT world. Spark developers earn highest average package as compared to other technologies. Big data with Apache Spark combination is the most demanding in industry.
You can do the payment via credit card, debit card or net banking through any of the banks. You can use our payment gateway Payu for payment in INR. For payments in USD, you can do via Paypal. We also have part payment option.