Scala Course Content

Introduction of Scala

Introducing Scala and deployment of Scala for Big Data applications and Apache Spark analytics.

Pattern Matching

The importance of Scala, the concept of REPL (Read Evaluate Print Loop), deep dive into Scala pattern matching, type interface, higher order function, currying, traits, application space and Scala for data analysis.

Executing the Scala code

Learning about the Scala Interpreter, static object timer in Scala, testing String equality in Scala, Implicit classes in Scala, the concept of currying in Scala, various classes in Scala.

Classes concept in Scala

Learning about the Classes concept, understanding the constructor overloading, the various abstract classes, the hierarchy types in Scala, the concept of object equality, the val and var methods in Scala.

Case classes and pattern matching

Understanding Sealed traits, wild, constructor, tuple, variable pattern, and constant pattern.

Concepts of traits with example

Understanding traits in Scala, the advantages of traits, linearization of traits, the Java equivalent and avoiding of boilerplate code.

Scala java Interoperability

Implementation of traits in Scala and Java, handling of multiple traits extending.

Scala collections

Introduction to Scala collections, classification of collections, the difference between Iterator, and Iterable in Scala, example of list sequence in Scala.

Mutable collections vs. Immutable collections

The two types of collections in Scala, Mutable and Immutable collections, understanding lists and arrays in Scala, the list buffer and array buffer, Queue in Scala, double-ended queue Deque, Stacks, Sets, Maps, Tuples in Scala.

Use Case bobsrockets package

Introduction to Scala packages and imports, the selective imports, the Scala test classes, introduction to JUnit test class, JUnit interface via JUnit 3 suite for Scala test, packaging of Scala applications in Directory Structure, example of Spark Split and Spark Scala.

Spark Course Content

Introduction to Spark

Introduction to Spark, how Spark overcomes the drawbacks of working MapReduce, understanding in-memory MapReduce,interactive operations on MapReduce, Spark stack, fine vs. coarse grained update, Spark stack,Spark Hadoop YARN, HDFS Revision, YARN Revision, the overview of Spark and how it is better Hadoop, deploying Spark without Hadoop,Spark history server, Cloudera distribution.

Spark Basics

Spark installation guide,Spark configuration, memory management, executor memory vs. driver memory, working with Spark Shell, the concept of Resilient Distributed Datasets (RDD), learning to do functional programming in Spark, the architecture of Spark.

Working with RDDs in Spark

Spark RDD, creating RDDs, RDD partitioning, operations & transformation in RDD,Deep dive into Spark RDDs, the RDD general operations, a read-only partitioned collection of records, using the concept of RDD for faster and efficient data processing,RDD action for Collect, Count, Collectsmap, Saveastextfiles, pair RDD functions.

Aggregating Data with Pair RDDs

Understanding the concept of Key-Value pair in RDDs, learning how Spark makes MapReduce operations faster, various operations of RDD,MapReduce interactive operations, fine & coarse grained update, Spark stack.

Writing and Deploying Spark Applications

Comparing the Spark applications with Spark Shell, creating a Spark application using Scala or Java, deploying a Spark application,Scala built application,creation of mutable list, set & set operations, list, tuple, concatenating list, creating application using SBT,deploying application using Maven,the web user interface of Spark application, a real world example of Spark and configuring of Spark.

Parallel Processing

Learning about Spark parallel processing, deploying on a cluster, introduction to Spark partitions, file-based partitioning of RDDs, understanding of HDFS and data locality, mastering the technique of parallel operations,comparing repartition & coalesce, RDD actions.

Spark RDD Persistence

The execution flow in Spark, Understanding the RDD persistence overview,Spark execution flow & Spark terminology, distribution shared memory vs. RDD, RDD limitations, Spark shell arguments,distributed persistence, RDD lineage,Key/Value pair for sorting implicit conversion like CountByKey, ReduceByKey, SortByKey, AggregataeByKey

Spark Streaming & Mlib

Spark Streaming Architecture, Writing streaming programcoding, processing of spark stream,processing Spark Discretized Stream (DStream), the context of Spark Streaming, streaming transformation, Flume Spark streaming, request count and Dstream, multi batch operation, sliding window operations and advanced data sources. Different Algorithms, the concept of iterative algorithm in Spark, analyzing with Spark graph processing, introduction to K-Means and machine learning, various variables in Spark like shared variables, broadcast variables, learning about accumulators.

Improving Spark Performance

Introduction to various variables in Spark like shared variables, broadcast variables, learning about accumulators, the common performance issues and troubleshooting the performance problems.

Spark SQL and Data Frames

Learning about Spark SQL, the context of SQL in Spark for providing structured data processing, JSON support in Spark SQL, working with XML data, parquet files, creating HiveContext, writing Data Frame to Hive, reading JDBC files, understanding the Data Frames in Spark, creating Data Frames, manual inferring of schema, working with CSV files, reading JDBC tables, Data Frame to JDBC, user defined functions in Spark SQL, shared variable and accumulators, learning to query and transform data in Data Frames, how Data Frame provides the benefit of both Spark RDD and Spark SQL, deploying Hive on Spark as the execution engine.

Scheduling/ Partitioning

Learning about the scheduling and partitioning in Spark,hash partition, range partition, scheduling within and around applications, static partitioning, dynamic sharing, fair scheduling,Map partition with index, the Zip, GroupByKey, Spark master high availability, standby Masters with Zookeeper, Single Node Recovery With Local File System, High Order Functions.

Apache Spark – Scala Project

Project 1: Movie Recommendation

Topics – This is a project wherein you will gain hands-on experience in deploying Apache Spark for movie recommendation. You will be introduced to the Spark Machine Learning Library, a guide to MLlib algorithms and coding which is a machine learning library. Understand how to deploy collaborative filtering, clustering, regression, and dimensionality reduction in MLlib. Upon completion of the project you will gain experience in working with streaming data, sampling, testing and statistics.

Project 2: Twitter API Integration for tweet Analysis

Topics – With this project you will learn to integrate Twitter API for analyzing tweets. You will write codes on the server side using any of the scripting languages like PHP, Ruby or Python, for requesting the Twitter API and get the results in JSON format. You will then read the results and perform various operations like aggregation, filtering and parsing as per the need to come up with tweet analysis.

Project 3: Data Exploration Using Spark SQL – Wikipedia data set

Topics – This project lets you work with Spark SQL. You will gain experience in working with Spark SQL for combining it with ETL applications, real time analysis of data, performing batch analysis, deploying machine learning, creating visualizations and processing of graphs.

What if I miss a class?

Don’t worry. You will always get a recording for the class in your inbox. Have a look at that and reach out to the faculty in case of doubts. All our live classes are recorded for self-study purpose. Hence, in case you miss a class, you can refer to the video recording and then reach out to the faculty during their doubts clearing time or ask your question in the beginning of the subsequent class.

Can I download the recordings?

Yes. We provide url for the video downloads.

Recordings are integral part of BSAI Academy intellectual property. The downloading/distribution of these recordings in anyway is strictly prohibited and illegal as they are protected under copyright act. Incase a student is found doing the same, it will lead to an immediate and permanent suspension in the services, access to all the learning resources will be blocked, course fee will be forfeited and the institute will have all the rights to take strict legal action against the individual.

Will I get a certificate in the end?

Yes. All our course are certified. As part of the course, students get weekly assignments and module-wise case studies and Exam will be taken at end after course completion. Candidates must bring 85% score on exam. Once all your submissions are received and evaluated, the certificate shall be awarded.

Do you help in placements?

We follow a comprehensive and a self-sustaining system to help our students with placements. This is a win-win situation for our candidates and corporate clients. As a pre-requisite for learning validation, candidates are required to submit the case studies and project work provided as a part of the course (flexible deadline). Support from our side is continuous and encompasses help in profile building, CV referrals (as and when applicable) through our ex-students, HR consultants and companies directly reaching out to us.

We will provide guidance to you in terms of what are the right profiles for you based on your education and experience, interview preparation and conducting mock interviews, if required. The placement process for us doesn’t end at a definite time post your course completion, but is a long relationship that we will like to build.

Do you guarantee placements?

No institute can guarantee placements, unless they are doing so as a marketing gimmick! It is on a best effort basis.

In professional environment, it is not feasible for any institute to do so, except for a marketing gimmick. For us, it is on a best effort basis but not time – bound – in some cases students reach out to us even after 3 years for career support.

Do you have a classroom option?

No. We provide only online let training.

What do I need to attend the online classes?

To attend the online classes, all you need is a laptop/PC with a basic internet connection. Students have often shared good feedback of attending these live classes through their data card or even their mobile 3G connection, though we recommend a basic broadband connection.

For best user experience, a mic-headphone is recommended to enhance the voice quality, though the laptop’s in-built mic works fine and you can ask your question over the chat as well.

How can I reach out to someone if I have doubts post class?

Students can always connect with the trainer or even schedule one-to-one time via online. During the course we also schedule periodic doubts-clearing classes though students can also ask doubts of a class in the subsequent class.

I am having difficulty coping up with my classes. What can I do?

For all the courses, we also provide the recordings of each class for their self-reference as well as revision in case you miss any concept in the class. In case you still have doubts after revising through the recordings, you can communicate with your trainer/tutor via email.

Can I pay in instalments?

Not for this course. The instalment options are available only for our courses which are atleast 3 months long.

What are the system requirements for the software?

It is recommended to have 64-bit operating system with minimum 8GB RAM so that the virtual lab can be installed easily

Is it feasible to attend a demo session before enrollment?

Unfortunately participation in a live class without enrollment is not possible. However, We can provide you the sample class recording and it would give you a clear insight about how are the classes conducted, quality of instructors and the level of interaction in the class.

Apache Spark and Scala Certification

The entire training course content is in line with the certification program and helps you clear Apache Spark and Scala Certification Exam with ease and get the best jobs in the top MNCs. As part of this training you will be working on real time projects and assignments that have immense implications in the real world industry scenario thus helping you fast track your career effortlessly.

At the end of this training program there will be a exam that helps you score better marks in certification exam.