Apache Spark and Scala Course offers a perfect blend of in-depth theoretical knowledge and strong practical skills via implementation of real-life Spark projects to give you a headstart and enable you to bag top Big Data Spark jobs in the industry.
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Why should you learn Apache Spark?
Upcoming Batches for Spark training
Limited seats available
Pick a time that suits you and grab your seat for Apache Spark Online Certification Course
|Self-Pacedv/s Live Course||Whenever you’d like||24+10 Hrs||
Rs. 4990 | $99
|4 Apr – 26 Apr||05.00 PM – 08.00 PM IST (Sat-Sun)||24+10 Hrs||
Rs. 12990 | $257
|25 Apr – 17 May||07.00 AM – 10.00 AM IST (Sat-Sun)||24+10 Hrs||
Rs. 12990 | $257
What you will take home from Big Data Spark Online Course
- Learn how Spark solves these Big Data challenges
- Grasp concepts of Scala and implement them
- Become adept in Apache Spark and Spark installation
- Understand the Apache Spark architecture
- Play with Spark RDDs – Transformation, Action, Load
- Learn to handle in-memory data efficiently
- Develop complex real-time Apache Spark applications
- Master the concepts of Spark stream analytics and learn streaming APIs
- Learn MLlib APIs in Spark for machine learning algorithms
- Learn Spark GraphX APIs to implement graph algorithms
- Work on live Spark project to get hands-on experience
What to do before you begin your Spark online training?
Although if you’d like, you can brush up on your skills with our complementary Java course right in your LMS.
Spark and Scala Course Curriculum
- What is Scala
- Setup and configuration of Scala
- Developing and running 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 and visibility rules
- Functional structures
- Functional programming constructs
- Call by Name, Call by Value
- Introduction to Big Data
- Challenges to old Big Data solutions
- Batch vs Real-time vs in-Memory processing
- MapReduce and its limitations
- Apache Storm and its limitations
- Need for a general purpose solution - Apache Spark
- What is Apache Spark?
- Components of Spark architecture
- Apache Spark design principles
- Spark features and characteristics
- Apache Spark ecosystem components and their insights
- Setting up the Spark Environment
- Installing and configuring prerequisites
- Installing Apache Spark in local mode
- Working with Spark in local mode
- Troubleshooting encountered problems in Spark
- Installing Spark in standalone mode
- Installing Spark in YARN mode
- Installing & configuring Spark on a real multi-node cluster
- Playing with Spark in cluster mode
- Best practices for Spark deployment
- Playing with the Spark shell
- Executing Scala and Java statements in the shell
- Understanding the Spark context and driver
- Reading data from the local filesystem
- Integrating Spark with HDFS
- Caching the data in memory for further use
- Distributed persistence
- Testing and troubleshooting
- What is an RDD in Spark
- How do RDDs make Spark a feature-rich framework
- Transformations in Apache Spark RDDs
- Spark RDD action and persistence
- Spark Lazy Operations - Transformation and Caching
- Fault tolerance in Spark
- Loading data and creating 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
- The 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
- Why Machine Learning is needed
- What is Spark Machine Learning
- Various Spark ML libraries
- Algorithms for clustering, statistical analytics, classification etc.
- What is GraphX
- The need for different graph processing engines
- Graph handling using Apache Spark
Awesome Apache Spark projects you’ll get to build in this Spark course
Set Top Box Data Analysis
Learn to analyze Set-Top-Box data and generate insights about smart tv usage patterns. Analyze set top box media data and generate patterns of channel navigation and VOD. This Spark Project includes details about users’ activities tuning a channel or duration, browsing for videos, or purchasing videos using VOD.
E-commerce Reviews Analysis
Learn to analyze e-commerce review data and generate various insights of products. Companies use these reports and patterns to understand the sentiments of users about their products. E-commerce reviews are made of fields like product-id, star-rating, reviews, timestamp, and reviewer-id.
Twitter Trends Analysis
Collect Twitter data in real-time and find out current trends in various categories. In this Apache Spark project, you will collect live Twitter streams and analyze them using Spark Streaming to generate insights like finding current trends in Politics, Finance, Entertainment, and such.
YouTube Data Analysis
Learn to analyze YouTube Data and generate insights like the 10 topmost videos in various categories, user demographics, no. of views, ratings and such. The data holds fields like id, age, category, length, views, ratings, and comments.
Titanic Data Analysis
Titanic was one of the most colossal disasters in the history of mankind, and it happened because of both natural events and human mistakes. The objective of this Spark project is to analyze multiple Titanic data sets to generate essential insights pertaining to age, gender, survived, class, and embarked.
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Spark Training Reviews
Is this Apache Spark Course for you?
Big Data is the truth of today and Spark proves to be efficient in processing it. So while anyone can benefit from a career in it, here are the kind of professionals who go for this Apache Spark course:
- Software developers, project managers, and architects
- BI, ETL and Data Warehousing professionals
- Mainframe and testing professionals
- Business analysts and analytics professionals
- DBAs and DB professionals
- Professionals willing to learn Data Science techniques
- Any graduate focusing to build a career in Apache Spark and Scala
Still can’t decide? Let our Big Data experts answer your questions
Learn Spark the way you like
|Features||Self-Paced Pro Course
Rs. 4990 | $91
|Live Instructor-Led Course
Rs. 12990 | $236
|Course mode||Video Based||Live Online with Trainer|
|Course Objective||Express Learning||Job readiness|
|Extensive hands-on practicals||In recordings & in LMS||Live with instructor & in LMS|
|No. of Projects||One||Five|
|Doubt Clearance||Through discussion forum||In regular sessions|
|Discussion Forum Access||✓||✓|
|100% Interactive Live Classes||✗||✓|
|Support for real-life project||✗||✓|
|Complementary Job Assistance||✗||✓|
|Resume & Interview Preparation||✗||✓|
|Personalized career guidance from instructor||✗||✓|
Rs. 4990 | $91
Rs. 12990 | $236
We’re here to help you find the best Spark jobs
Once you finish the Apache Spark course, our job grooming program will help you build your resume while also furthering it to prospective employers. Our Spark mock interviews will help you better understand the interview psychology so you go in prepared.
Apache Spark Course FAQ’s
If you miss any session, you need not worry as 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 during the next Spark session. You can also ask him to explain the concepts that you did not understand and were covered in session you missed. Alternatively, you can attend the missed online Spark training session in any other batch running parallely.
To perform these Spark and Scala practicals, the instructor will help you in setting up a virtual lab on your own system. The manual to set up this virtual lab will be available in your LMS if you want to go through the steps again. The virtual lab can be set up on MAC or Windows machines also.
All the sessions will be recorded and you will have lifetime access to the Spark and Scala training course recordings along with the complete study material, POCs, Spark project etc.
To attend online Spark training, you just need a laptop or PC with a good internet connection of around 1 MBPS (But the lesser speed of 512 KBPS will also work). The broadband connection is recommended but you can connect through data card as well.
If you have any doubts during Apache Spark sessions, you can clear it with the instructor immediately. If you get queries after the session, you can get it cleared from the instructor in the next session as before starting any session, instructor spends around 15 minutes in 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 gain access to LMS and it will be there for lifetime. Complimentary courses will also be added then, so 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 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 10-12 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.