Online Classroom Batches Preferred
Weekdays Regular
(Class 1Hr - 1:30Hrs) / Per Session
Weekdays Regular
(Class 1Hr - 1:30Hrs) / Per Session
Weekend Regular
(Class 3hr - 3:30Hrs) / Per Session
Weekend Fasttrack
(Class 4:30Hr - 5:00Hrs) / Per Session
No Interest Financing start at ₹ 5000 / month
Skills You Will Gain
- Big Data, HDFS
- YARN, Spark
- MapReduce
- PIG, HIVE
- Mahout, Spark MLLib
- Solar, Lucene
- Zookeeper
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Apache Spark with Scala Course Curriculam
Trainers Profile
Trainers are certified professionals with 11+ years of experience in their respective domains as well as they are currently working with Top MNCs. As all Trainers from Apache Spark with Scala Certification Course are respective domain working professionals so they are having many live projects, trainers will use these projects during training sessions.
Pre-requisites
Following is sufficient for basics of Apache Spark with Scala technologies :
Syllabus of Apache Spark with Scala Online Course Download syllabus
- What is Big Data?
- Big Data Customer Scenarios
- What is Hadoop?
- Hadoop’s Key Characteristics
- Hadoop Ecosystem and HDFS
- Hadoop Core Components
- Rack Awareness and Block Replication
- YARN and its Advantage
- LHadoop Cluster and its Architecture
- Hadoop: Different Cluster Modes
- Why Spark is needed?
- What is Spark?
- How Spark differs from other frameworks?
- What is Scala?
- Why Scala for Spark?
- Scala in other Frameworks
- Introduction to Scala REPL
- Basic Scala Operations
- Variable Types in Scala
- Control Structures in Scala
- Foreach loop, Functions and Procedures
- Collections in Scala- Array
- ArrayBuffer, Map, Tuples, Lists
- Variables in Scala
- Methods, classes, and objects in Scala
- Packages and package objects
- Traits and trait linearization
- Java Interoperability
- Introduction to functional programming
- Functional Scala for the data scientists
- Types and hierarchies
- Performance characteristics
- Java interoperability
- Using Scala implicits
- Apache Spark installation
- Spark Applications
- The back bone of Spark – RDD
- Loading Data
- What is Lambda?
- Using the Spark shell
- Actions and Transformations
- Associative Property
- What is RDD, Its Operations, Transformations & Actions
- Data Loading and Saving Through RDDs
- Key-Value Pair RDDs
- RDD Lineage
- RDD Persistence
- WordCount Program Using RDD Concepts
- RDD Partitioning & How It Helps Achieve Parallelization
- Passing Functions to Spark
- Need for Spark SQL
- What is Spark SQL?
- Spark SQL Architecture
- SQL Context in Spark SQL
- User Defined Functions
- Data Frames & Datasets
- Interoperating with RDDs
- JSON and Parquet File Formats
- Spark – Hive Integration
- Need for stream analytics
- 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
- A brief introduction to graph theory
- GraphX
- VertexRDD and EdgeRDD
- Graph operators
- Pregel API
- PageRank
- Why Machine Learning?
- What is Machine Learning?
- Where Machine Learning is Used?
- Different Types of Machine Learning Techniques
- Introduction to MLlib
- Features of MLlib and MLlib Tools
- Various ML algorithms supported by MLlib
- Optimization Techniques
- Machine Learning MLlib
- K- Means Clustering
- Linear Regression
- Logistic Regression
- Decision Tree
- Random Forest
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Apache Spark with Scala Training Objectives
- The Apache Spark with Scala Certification Training course is designed to provide you with the comprehensive knowledge and skills required to develop, deploy and manage advanced analytics with Apache Spark. This program focuses on the fundamentals of distributed systems along with the implementation of Spark 2.x DataFrames and Spark Streaming applications designed for real-time analytics and machine learning.
This certification programme will teach you the principles of distributed computing, in-depth knowledge of Apache Spark, and Scala to enable you master the implementation and management of sophisticated Analytics applications with Spark. The following are the goals of this certification programme:
- Work with data frames using Spark and Scala;
- Recognise and use the terms, components, and architecture of Spark;
- Recognise and use Spark for machine learning
- With an increasing demand for big data analytics solutions, Apache Spark is a technology that is going to be in high demand in the coming future. Employees of any organization who are certified in Spark can make a great contribution to the organization’s data analytics initiatives. This course will equip participants to perform real-time analytics with Apache Spark, leveraging its superior tools with a view to developing sophisticated data-driven decisions and uncovering valuable insights.
- Apache Spark with Scala Certification Training provides excellent career opportunities for professionals including software engineers, data scientists, analytics architects, and big data professionals. Apart from being well-equipped to develop and manage advanced analytics with Apache Spark, they will be eligible for positions such as Hadoop Developers, Big Data Architects, Data Engineers, Data Analysts, Analytics Managers, and DevOps Engineers.
- Yes, Apache Spark with Scala Certification is a trend that will lead the tech industry in future. Apache Spark is one of the most powerful and popular big data tools today, and its use is continually growing. Apache Spark with Scala Certification will not only equip the developer with the knowledge of Hadoop and big data but also with the programming language Scala necessary to work with Spark. With Spark and Scala working together, a data scientist has tools that are superior to writing plain Java and working with batch processing.
- Yes, there is a tremendous demand for Apache Spark with Scala Certification Training. Spark certification is becoming increasingly important for organizations that want to maximize the value of their big data initiatives. Those who get certified from this course are accredited internationally, and this certification proves their ability to work with Spark for advanced analytics and machine learning.
- The online lab is available based on the schedules and durations specified in the training. It is structured to give you the best environment for learning and working with Apache Spark and Scala, thus helping you to hone your skills and build up confidence to work with advanced analytics applications.
- Apache Spark with Scala Certification Training enables professionals to become eligible for roles such as Hadoop Developers, Big Data Architects, Data Engineers, Data Analysts, Analytics Managers, and DevOps Engineers. Additionally, they can start their own data analytics firms or work as a Spark analyst in a wide variety of organizations such as government agencies, retail companies, BFSI, and telecommunication sectors.
- Distributed computing basics
- Working with dataframes and Spark SQL
- Spark operations and maintenance
- Streaming data with Spark
- Integrating Spark with Hadoop components like HDFS and YARN
- Setting up and deploying Spark clusters
- Creating and deploying applications on the cluster
- Laptop/PC with internet access
- Knowledge of Core Java, Scala, and Machine Learning
- Basic understanding of Hadoop
- Familiarity with the command line
- Ability to install necessary software
Exam & Certification
- Participate and Complete One batch of Apache Spark with Scala Training Course
- Successful completion and evaluation of any one of the given projects
- Complete 85% of the Apache Spark with Scala course
- Successful completion and evaluation of any one of the given projects
- Oracle Certified Associate (OCA)
- Oracle Certified Professional (OCP)
- Oracle Certified Expert (OCE)
- Oracle Certified Master (OCM)
- Learn About the Certification Paths.
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Pranav Srinivas
Software Testing, CapgeminiApache Spark with Scala Course FAQ's
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