Big Data with Apache Spark using Scala @LearnSocial.com
Event on 2015-11-14 07:00:00
Big Data World has been offering various Open Source Technologies and framework that are enabling organizations to optimize iterative workloads and makes the computing faster, but high latency processing act as a detriment to the overall execution. Apache Spark is an alternative to this as it provides fast processing of large datasets, enables in-memory cluster computing; and improves the speed of iterative algorithms and interactive data mining tasks. Big Data with Apache Spark using Scala Course @LearnSocial comes to the rescue of Big Data Enthusiasts, Professionals and Novice Programmers/Developers who are looking forward to enhance their skills and get a grip on this nex-gen Big Data processing engine.
What is Apache Spark?
Apache Spark is poised to be one of the fastest and most efficient Distributed Computing tool to handle Big Data Projects; eliminating the pain of separate processing engines such as batch analytics, stream processing and statistical modeling. It fits into Hadoop open-source community, and is built on top of the Hadoop Distributed File System (HDFS).
What is Scala? Where does it fit in?
Scala (Scalable Language) is a multi-paradigm, Object Oriented (OO) and Functional, programming language used for general software applications. Scala is fast and interoperates with JRE because it’s statically typed and compiles in a known way to the JVM (Java Virtual Machine). Even though, Apache Spark supports Java, Scala, and Python APIs for ease of development but Scala achieves greater performance with Resilient Distributed Datasets (RDDs).
Also, Spark’s codebase is written in Scala which helps in understanding what Spark does internally, and it performs really well for Heavy Processing. Scala, being a Functional Programming Language, also makes Data Transformation and Mapping in Spark much easier and is recommended for large scale systems.
‘Big Data with Apache Spark using Scala’ Course has been structured in a manner where learners will firstly gain acquaintance with concepts of Big Data and then understand the nitty-gritties of concepts encompassing Apache Spark and Scala Programming Language. This course is a part of Developer Learning Path. Post completion of this course, learners will be able to write refined parallel applications to execute faster decisions, better decisions, and real-time actions, which can applied to a wide range of use cases, architectures, and industries.
Understand the Significance of Apache Spark, its concepts, architecture and applications
Learn Scala Programming and use Scala to create & run a Spark Application
Work with Spark Primary Abstraction, Resilient Distributed Datasets and its applications
Become conversant with concepts like Traits, OOPs and Functional Programming in Scala
Write applications with Spark, run Spark on a Cluster and learn Parallel Processing with Spark
Create applications using Spark SQL, (Machine Learning) MLlib, Spark Streaming, and GraphX
Gain Insights on using Spark Shell for Interactive Data Analysis and execute SQL Queries on Large sc
Tune Spark job performance and troubleshoot errors using logs & administration UIs
30 hours of Live Instructor-Led Online Sessions
30 hours of Hands on Project work, Exercises, Assignments, Quizzes and Assessments
20 hours of 1 Major Real Time project will be allotted to give Real-Time Industry Experience
5 Use Cases, Case Studies & Real-Time Scenarios to make you familiar with Current Industry Practices
80% Practical & 20% Theoretical Approach to give the learners Holistic View of Subject Matter
Post Completion of each session, Practice Tasks will be allotted to track your progress of learning
Easily accessible courseware and related resources on User-Friendly interface
Good quality audio and high resolution of pre-recorded session videos to enhance your experience
Fundamental understanding on Big Data Concepts would be beneficial
Knowledge of SQL Concepts
Basic understanding of Functional Programming and Object Oriented Programming
Target Audience for this Course:
Data Scientists & Big Data Consultants
Big Data/ETL Developers
Analysts and Project Managers
Project & Certification Process:
Towards the end of the course, the instructor will allot you real-time project to have a clear understanding of how to conceptualize and implement the real-world application. The instructor will provide constant support and assist you in completing the project assignment. On successful completion of this assignment, it will be reviewed by instructor and you will be awarded a certificate with performance based grading. After the instructor's review, if your project is not approved, then we will be providing you with extra assistance for any queries/doubts and let you reattempt it free of cost.
Discover the Peer Advantage:
Exposure to newest technologies and latest programming in today’s fast pace IT environment becomes easy when you are linked to like-minded technical people and with the right level of confidence, you are all set to take your leap into the huge ocean of Information and Technology.
Come and explore the milieu of LearnSocial which brings about a thousand reasons as to why you should be included into a batch of highly enthusiastic and fun-loving people.
What’s in it for me (WIIFM)?
Most of organizations dealing with huge chunks of data are utilizing various Big Data Technologies/Tools to make the processing faster, supplementing the decision making process. Hence, Apache Spark Professionals can land themselves in these organizations and put their knowledge to practice
Online Giants like Yahoo, Amazon, Baidu, Opentable, ebay, Alibaba Taobao, IBM etc. make use of Apache Spark which makes this Big Data Processing engine luring for Big Data Enthusiast
As per the Indeed Job Data, Big Data Professionals who have expertise with Apache Spark have seen an explosive rise in their Salary Structure and are in huge demand by renowned organizations
Learners, having expertise in Apache Spark, can envision their designations as Big Data Engineers, Big Data Consultants, Data Analytics Engineer, Data Scientist and many more
For Big Data Professionals, having a hold over technologies like Hadoop and MapReduce, learning Apache Spark should be their next step as it is 100 times faster than MapReduce in-memory (that is, processed while stored in memory as opposed to on drives) and 10 times faster than MapReduce on disk
Course Delivery: (How will the learning happen?)
All our courses are live instructor led and interactive sessions handled by highly reputed and experienced professionals from industry giants such as Microsoft, Google, IBM etc
All the classes are conducted through LIVE Video Streaming, where learners can interact with the instructor by speaking, chatting and sharing screen.
We use all kind of modern tools and equipment to train you for the course. Instructor trains learners by sharing their screen and through other technology tools.
In addition to this, our instructors will track your learning in a step by step procedure to make you an expert in the field.
Before the start of every session, our instructors recap the previous class session to reinforce the concepts in the minds of learners.
We pay utmost attention to each feedback, reviews and ratings of yours and proactively take the required action on your grievances
All you need is a PC with a webcam, microphone and a 1 MBPS internet connection to attend the LIVE classes. However, we have seen people attending the classes from a much slower internet.