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
Apache Spark with Scala Course Key Features 100% Money Back Guarantee
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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
- Certification enhances your career prospects, allowing you to gain an edge in an increasingly competitive job market. It proves your skill set and knowledge base, demonstrating to potential employers that you are an expert in Apache Spark. Additionally, certification also provides access to networking opportunities, especially those tailored to certified professionals.
- Generally, prerequisites for enrolling in this certification course include basic proficiency in coding languages such as Java, Python and Scala, as well as a general understanding of data analysis and data engineering principles. Additionally, some courses may require prior machine learning experience.
- Job opportunities in this field range from data engineer positions to Apache Spark developer and data scientist roles. Areas of expertise include data analysis, machine learning, business intelligence, and related technologies such as Hadoop and Cassandra. Job opportunities also exist with traditional business intelligence and analytics solutions, as Apache Spark can be used to enhance existing projects.
- Most certification courses provide hands-on practice that covers working with Apache Spark components, such as Spark Core and Spark SQL, to develop complex analytics applications. Additionally, courses also cover topics such as leveraging Apache Spark with other big data technologies like Hadoop, Cassandra, and the Hadoop Distributed File System (HDFS).
- Apache Spark with Scala Training is mainly used for tasks such as data streaming, data analysis, and real-time analytics. It is also an integral component in many big data solutions, as it greatly enhances existing machine learning and processing applications. Additionally, Apache Spark with Scala is a powerful tool for large-scale data engineering projects.
- To successfully complete a certification course, you should possess basic programming proficiency in Java, Python and Scala, as well as an understanding of data analysis and engineering principles. Additionally, experience with distributed systems and cloud services is beneficial for success in this course. Finally, having prior knowledge of machine learning and big data storage tools, such as the Hadoop Distributed File System (HDFS,) is a plus.
- Yes, most certification courses are tailored to help beginners learn Apache Spark with Scala, as well as those already experienced in the technology. The courses provide rich hands-on practice opportunities and teaching modules specific to each student’s individual skill set.
- Yes, Apache Spark with Scala Training is in high demand due to its vast capabilities and potential applications in the big data and analytics field. Additionally, its ability to be used in tandem with big data storage solutions and frameworks, such as Hadoop, Cassandra, and HDFS, makes it a tool of choice for large organizations.
- The advantages of Apache Spark with Scala Training include having the latest, most advanced big data solutions and skillset in your arsenal. As mentioned, Apache Spark solves a variety of data processing and analysis needs, so having a certification in this technology will open you up to a diverse range of job opportunities. Additionally, it helps expand your big data proficiency in areas such as analytics, data engineering, and machine learning.
- Learning Apache Spark with Scala in Houston, USA is generally not difficult if you have prior knowledge of big data technologies and coding languages. Prior machine learning and distributed system experience is also beneficial. However, the certification course structure makes the learning process easier by offering interactive classes and hands-on practice with real-world problems.
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.
- Write Code Daily This will help you develop Coding Reading and Writing ability.
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- Join LearnoVita Online Training Course That Gives you a High Chance to interact with your Subject Expert Instructors and fellow Aspirants Preparing for Certifications.
- Solve Sample Tests that would help you to Increase the Speed needed for attempting the exam and also helps for Agile Thinking.

Pranav Srinivas
Software Testing, CapgeminiApache Spark with Scala Course FAQ's
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