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Apache Spark and Scala Certification Training in Baltimore, MD
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Get certified in Apache Spark and Scala from the comfort of your home and transform your career
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Also prepares you for the Cloudera Hadoop and Spark Developer Certification Exam (CCA175)
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Curated by industry experts, the course provides in-depth knowledge on Apache Spark, Spark Ecosystem, Scala Programming language and other concepts such as HDFS, Sqoop, FLume, Spark GraphX, and Kafka.
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30 hours of Instructor-led Apache Spark and Scala Online Classes with Hands-on practice with Cloud Lab
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We guarantee great value at lowest price in the industry
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Exclusive Buy 1 - Get 1 Free Offer (till 31st May, 2021) Know More
Online Self-Learning
USD 299 179
40
Live-Virtual Class
Date :
Apr 24 May 30 (Weekend)
Details
Time : 10:00 AM to 01:00 PM (CDT)
USD 549 429
Apr 24Sat Apr 25Sun May 01Sat May 02Sun May 08Sat May 09Sun May 15Sat May 16Sun May 22Sat May 23Sun May 29Sat May 30Sun
Date :
May 28 Jul 03 (Weekend)
Details
Time : 08:30 PM to 11:30 PM (CDT)
USD 549 429
May 28Fri May 29Sat Jun 04Fri Jun 05Sat Jun 11Fri Jun 12Sat Jun 18Fri Jun 19Sat Jun 25Fri Jun 26Sat Jul 02Fri Jul 03Sat
Apache Spark and Scala Certification Course Overview
Overview:
Spark is one of the most popular Big Data & Analytics tools and expertise in Spark offers promising career opportunities. This Apache Spark and Scala Certification Training Course is designed to provide you with the knowledge and skills to become a successful Big Data & Spark Developer. This course is aligned to Cloudera Hadoop and Spark Developer Certification (CCA175) and current industry requirements and best practices. At the successful completion of the course, you will be provided with Apache Spark and Scala Developer certification. In addition, you will also be ready to take the CCA Spark and Hadoop Developer (CCA175) Examination.
This course is an integral part of a Big Data Developer’s Career path and it covers all essentials concepts related to Apache Spark. Besides strong theoretical understanding, this course will also provide you with strong hands-on experience. Throughout the course, you will be working on various industry-based use-cases and projects incorporating big data and spark tools as a part of solution strategy.
Additionally, all your doubts will be addressed by an expert instructor and industry professional, currently working on real life big data and analytics projects.
Course Objectives:
The Spark Scala Course offers:
- Overview of Big Data & Hadoop including HDFS (Hadoop Distributed File System), YARN (Yet Another Resource Negotiator)
- Comprehensive knowledge of various tools that falls in Spark Ecosystem like Spark SQL, Spark MlLib, Sqoop, Kafka, Flume and Spark Streaming
- The capability to ingest data in HDFS using Sqoop & Flume, and analyze those large datasets stored in the HDFS
- The power of handling real time data feeds through a publish-subscribe messaging system like Kafka
- The exposure to many real-life industry-based projects which will be executed using CloudLab
- Projects which are diverse in nature covering banking, telecommunication, social media, and govenment domains
- Rigorous involvement of a SME throughout the Spark Training to learn industry standards and best practices
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Apache Spark and Scala Course Topics
- 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, and more
- Class in Scala
- Getters and Setters
- Custom Getters and Setters
- Properties with only Getters
- Auxiliary Constructor and Primary Constructor
- Singletons
- Extending a Class
- Overriding Methods
- Traits as Interfaces and Layered Traits
- Programming
- Higher Order Functions
- Anonymous Functions, and more
- What is Big Data?
- Big Data Customer Scenarios
- Limitations and Solutions of Existing Data Analytics Architecture with Uber Use Case
- How Hadoop Solves the Big Data Problem
- What is Hadoop?
- Hadoop’s Key Characteristics
- Hadoop Ecosystem and HDFS
- Hadoop Core Components
- Rack Awareness and Block Replication
- HDFS Read/Write Mechanism
- YARN and Its Advantage
- Hadoop Cluster and Its Architecture
- Hadoop: Different Cluster Modes
- Data Loading using Sqoop
- Big Data Analytics with Batch & Real-Time Processing
- Why Spark is Needed?
- What is Spark?
- How Spark Differs from Its Competitors?
- Spark at eBay
- Spark’s Place in Hadoop Ecosystem
- Spark Components & it’s Architecture
- Running Programs on Scala IDE & Spark Shell
- Spark Web UI
- Configuring Spark Properties
- Challenges in Existing Computing Methods
- Probable Solution & How RDD Solves the Problem
- What is RDD, It’s Functions, Transformations & Actions?
- Data Loading and Saving Through RDDs
- Key-Value Pair RDDs and Other Pair RDDs o RDD Lineage
- RDD Persistence
- WordCount Program Using RDD Concepts
- RDD Partitioning & How It Helps Achieve Parallelization
- Need for Spark SQL
- What is Spark SQL?
- Spark SQL Architecture
- SQL Context in Spark SQL
- Data Frames & Datasets
- Interoperating with RDDs
- JSON and Parquet File Formats
- Loading Data through Different Sources
- What is Machine Learning?
- Where is Machine Learning Used?
- Different Types of Machine Learning Techniques
- Face Detection: USE CASE
- Understanding MLlib
- Features of Saprk MLlib and MLlib Tools
- Various ML algorithms supported by Spark MLlib
- K-Means Clustering & How It Works with MLlib
- Analysis on US Election Data: K-Means Spark MLlib USE CASE
- Need for Kafka
- What is Kafka?
- Core Concepts of Kafka
- Kafka Architecture
- Where is Kafka Used?
- Understanding the Components of Kafka Cluster
- Configuring Kafka Cluster
- Producer and Consumer
- Need of Apache Flume
- What is Apache Flume
- Basic Flume Architecture
- Flume Sources
- Flume Sinks
- Flume Channels
- Flume Configuration
- Integrating Apache Flume and Apache Kafka
- Drawbacks in Existing Computing Methods
- Why Streaming is Necessary?
- What is Spark Streaming?
- Spark Streaming Features
- Spark Streaming Workflow
- How Uber Uses Streaming Data
- Streaming Context & DStreams
- Transformations on DStreams
- WordCount Program using Spark Streaming
- Describe Windowed Operators and Why it is Useful
- Important Windowed Operators
- Slice, Window and ReduceByWindow Operators
- Stateful Operators
- Perform Twitter Sentimental Analysis Using Spark Streaming
Project #1: US Election
Industry: Government
Technologies Used:
- HDFS (for storage)
- Spark SQL (for transformation)
- Spark MLlib (for machine learning)
- Zeppelin (for visualization)
Problem Statement : In the US Primary Election 2016, Hillary Clinton was nominated over Bernie Sanders from Democrats and on the other hand, Donald Trump was nominated from Republican Party to contest for the presidential position. As an analyst, you have been tasked to understand different factors that led to the winning of Hillary Clinton and Donald Trump in the primary elections based on demographic features to plan their next initiatives and campaigns.
Project #2: Design a system to replay the real time replay of transactions in HDFS using Spark.
Technology Used :
- Spark Streaming
- Kafka (for messaging)
- HDFS (for storage)
- Core Spark API (for aggregation)
Project #3: Instant Cabs
Industry: Transportation
Technologies Used :
- HDFS (for storage)
- Spark SQL (for transformation)
- Spark MLlib (for machine learning)
- Zeppelin (for visualization)
Problem Statement : A US cab service start-up (i.e. Instant cabs) wants to meet the demands in an optimum manner and maximize the profit. Thus, they hired you as a data analyst to interpret the available Uber’s data set and find out the beehive customer pick-up points & peak hours for meeting the demand in a profitable manner.
Project #4: Drop-page of signal during Roaming
Industry: Telecom
Technologies Used :
- HDFS (for storage)
- Spark SQL (for transformation)
Problem Statement : You will be given a CDR (Call Details Record) file, you need to find out top 10 customers facing frequent call drops in Roaming. This is a very important report which telecom companies use to prevent customer churn out, by calling them back and at the same time contacting their roaming partners to improve the connectivity issues in specific areas.
Apache Spark and Scala Certification & Exam
Prerequisites
There are no such prerequisites for this Spark and Scala Training Course. However, prior knowledge of Core Java and SQL will be helpful but is not at all mandatory.
Certification
Towards the end of the course, you will be working on a project. You will be certified as a Apache Spark and Scala Programmer based on the project. Once you successfully submit your Apache Spark and Scala certification project, it will be reviewed by the expert panel. After a successful evaluation, you will be awarded Apache Spark and Scala Programmer certificate.
In addition, you can also apply for Cloudera Hadoop and Spark Developer Certification (CCA175) separately.
Why Choose Us
Course Design
Based on years of experience in delivering effective professional training, our courses are designed not only to provide you the Apache Spark and Scala certification, but also to empower with best practices. We achieve this by providing a unique blend of concepts, case studies, and simulations that guarantee our students to become a successful Spark Developer in real life.
Trainers
All our trainers are highly qualified and certified in various industry frameworks. On an average, they have 10+ years of professional experience in their respective fields. Our trainers are not only experts in their domains but are also passionate about sharing their knowledge and expertise with other professionals thereby enriching careers of students.
Unmatched Quality
We along with our affiliate partners are dedicated in creating the best quality study materials and student experience across our products. All content complies with quality conformance standards to ensure that our content is the best in class and free of any errors.
Low Cost
Without compromising on quality, we have priced our Apache Spark and Scala certification training courses very competitively. We guarantee that you will find us more economical than any other training provider.
Never miss a class
In case you miss a session because of any reason, you can either attend the missed session in any other live batch or view the recorded session in the LMS.
Lifetime Access
You get lifetime access to the Learning Management System (LMS). Class recordings and presentations can be viewed online from the LMS.
Cloud Lab
Cloud Lab is provided to ensure you get real-time hands-on experience to practice your new skills on a pre-configured environment
Convenient Schedule
We have batches both on weekends and weekdays to accommodate the need of different professionals.
Popularity
More than 20,000 satisfied learners have taken this course on Apache Spark and Scala.
Customer Satisfaction
We are here to ensure you get heard 24/7, and to take care of every single questions and doubts you have. Our dedicated support team will provide you best in class round the clock customer support. Superior customer service is the hallmark of our company and we always go the extra mile to satisfy each of our customers whether an individual or a corporate client.
Apache Spark and Scala Training Frequently Asked Questions
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