Big Data Hadoop Developer Certification Training
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Hadoop developer, Architect, Tester, Administrator, Analyst or a Data Scientist. Learn the basics, Hadoop applications, HBase data model and architecture, schema design, MapReduce and Apache Drill. This course covers the concepts of MapReduce, Yarn, Pig, Hive, HBase, Oozie, Flume and Sqoop. Our trainers give hands on experience with real-time scenario – based projects in the United States. You have the flexibility to watch the class recording (which is posted on LMS) if you miss any class. For Self-paced video training program, you will be provided recorded videos for all topics covered.
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DescriptionHadoop is a revolutionary open-source framework for software programming that took the data storage and processing to next level. With its tremendous capability to store and process huge clusters of data, it unveiled opportunities to business around the world with artificial intelligence. It stores data and runs applications on clusters in commodity hardware which massively reduces the cost of installation and maintenance. It provides huge storage for any kind of data, enormous processing power and to have all kinds of analytics such as real-time analytics, predictive analytics data and so on at a click of a mouse. The volume of data being handled by organizations keeps growing exponentially with each passing day! This ever-demanding scenario calls for powerful big data handling solutions such as Hadoop for a truly data-driven decision-making approach. Students who start as Hadoop developers evolve into Hadoop Administrators by the end of a certification course and in the process guarantee a bright future. Become a certified Hadoop professional to bag a dream job offer. Acquiring proper training on Hadoop technology would definitely be a boon to professionals in terms of using Hadoop resources effectively and save huge time and effort.
Did you KnowIt is noticeable that the world is revolutionized by data and Information Technology. More than ‘2.5 quintillion bytes of data is created daily across the globe. Surprisingly, the data developed in last 2 years accounts for 90% of the entire data in the world! every day this rate of data creation is increasing rapidly. Big Data professionals play a vital role in this tremendous evolution as they are responsible to handle such huge volumes of data!
Why learn and get Certified in Big Data and Hadoop Admin?1. Leading multinational companies are hiring for Hadoop technology – Big Data & Hadoop market is expected to reach $99.31B by 2022 growing at a CAGR of 42.1% from 2015 (Forbes). 2. Streaming Job Opportunities – McKinsey predicts that by 2018 there will be a shortage of 1.5M data experts (Mckinsey Report). 3. Hadoop skills will boost salary packages – Average annual salary of Big Data Hadoop Developers is around $135k (Indeed.com Salary Data). 4. Future of Big Data and Hadoop looks bright – The world’s technological per-capita capacity to store information has roughly doubled every 40 months since the 1980s; as of 2012, every day 2.5 exabytes (2.5×1018) of data is generated. “Technology professionals should be volunteering for Big Data projects, which make them more valuable to their current employer and more marketable to other employers” – (Dice.com)
Pre-requisitesThere are no prerequisites as such for learning Hadoop. Knowledge of Core Java and SQL skills will help, but certainly not a requirement. If you want to learn Core Java, CoursesIT offers the students a complimentary self-paced course in “Core Java” when you enroll in our Big Data Hadoop Certification course.
Course ObjectiveAfter the completion of this course, Trainee will: 1. Expertise in writing customize Java MapReduce jobs to summarize data and helps in solving common data manipulation problems 2. Knowledge in Debugging and implementation of workflows and common algorithms are the best practices for Hadoop development 3. Capability to assist an individual to create custom components such as input formats and writable comparables to manage difficult data types 4. Ability to understand comprehend Advanced Hadoop API topics 5. Expertise in Hadoop ecosystem projects like leveraging Hive, Oozie, Pig, Flume, Sqoop etc.
Who should attend this Training?1. Architects, Java developers and testers who want to build effective data processing applications by querying Apache Hadoop, also who insists to learn to write code 2. Technical managers involved in the development process also take active participation in Hadoop Developer classes 3. Business Analysts, Database Administrators and SQL Developers 4. Software engineers with a background in ETL/Programming and managers dealing with latest technologies and data management 5. .NET Developers and data analysts who have to develop applications and perform big data analysis using the Hortonworks Data Platform for Windows will also find this helpful
Prepare for Certification!Our training and certification program gives you a solid understanding of the key topics covered on the certification exams. In addition to boosting your income potential, becoming certified Professional will provide you to display your ability and expertise in the relevant domain. Upon completion of course, students are encouraged to proceed to study and register for the Cloudera Certified Developer for Apache Hadoop (CCDH) Exam. Once the students successfully clears the online exam, they are eligible for CCA & CCP Certifications by Cloudera. The Developer program includes two certification tiers – Cloudera Certified Associate (CCA175) and Cloudera Certified Professional (CCP-DE575).
Basic Unit 1: Introduction and Overview of Hadoop 1. What is Hadoop? 2. History of Hadoop 3. Building Blocks - Hadoop Eco-System 4. Who is behind Hadoop? 5. What Hadoop is good for and what it is not? Unit 2: Hadoop Distributed FileSystem (HDFS) 1. HDFS Overview and Architecture 2. HDFS Installation 3. HDFS Use Cases 4. Hadoop File System Shell 5. File System Java API 6. Hadoop Configuration Unit 3: HBase – The Hadoop Database 1. HBase Overview and Architecture 2. HBase Installation 3. HBase Shell 4. Java Client API 5. Java Administrative API 6. Filters 7. Scan Caching and Batching 8. Key Design 9. Table Design Unit 4: Map/Reduce 2.0/YARN 1. Decomposing Problems into MapReduce Workflow 2. Using JobControl 3. Oozie Introduction and Architecture 4. Oozie Installation 5. Developing, deploying, and Executing Oozie Workflows Unit 5: Pig 1. Pig Overview 2. Installation 3. Pig Latin 4. Developing Pig Scripts 5. Processing Big Data with Pig 6. Joining data-sets with Pig Unit 6: Hive 1. Hive Overview 2. Installation 3. Hive QL Unit 7: Sqoop 1. Introduction 2. Sqoop Tools 3. Sqoop Import 4. Sqoop Import all tables 5. Sqoop Export 6. Sqoop Job 7. Sqoop metastore 8. Sqoop Eval 9. Sqoop Codegen 10. Sqoop List Databases and List Tables 11. Sqoop Create Hive Table Advance Unit 1: Integrating Hadoop Into The Workflow 1. Relational Database Management Systems 2. Storage Systems 3. Importing Data from RDBMSs With Sqoop 4. Hands-on exercise 5. Importing Real-Time Data with Flume 6. IAccessing HDFS Using FuseDFS and Hoop Unit 2: Delving Deeper Into The Hadoop API 1. More about ToolRunner 2. Testing with MRUnit 3. Reducing Intermediate Data With Combiners 4. The configure and close methods for Map/Reduce Setup and Teardown 5. Writing Partitioners for Better Load Balancing 6. Hands-On Exercise 7. Directly Accessing HDFS 8. Using the Distributed Cache Unit 3: Common Map Reduce Algorithms 1. Sorting and Searching 2. Indexing 3. Machine Learning With Mahout 4. Term Frequency – Inverse Document Frequency 5. Word Co-Occurrence Unit 4: Using Hive and Pig 1. Hive Basics 2. Pig Basics Unit 5: Practical Development Tips and Techniques 1. Debugging MapReduce Code 2. Using LocalJobRunner Mode For Easier Debugging 3. Retrieving Job Information with Counters 4. Logging 5. Splittable File Formats 6. Determining the Optimal Number of Reducers 7. Map-Only MapReduce Jobs Unit 6: More Advanced Map Reduce Programming 1. Custom Writables and WritableComparables 2. Saving Binary Data using SequenceFiles and Avro Files 3. Creating InputFormats and OutputFormats Unit 7: Joining Data Sets in Map Reduce 1. Map-Side Joins 2. The Secondary Sort 3. Reduce-Side Joins Unit 8: Graph Manipulation in Hadoop 1. Introduction to graph techniques 2. Representing graphs in Hadoop 3. Implementing a sample algorithm: Single Source Shortest Path Unit 9: Creating Workflows With Oozie 1. The Motivation for Oozie 2. Oozie’s Workflow Definition Format
About Hadoop Developer CertificationProfessional certifications will help you to showcase your proficiency and expertise in the particular domain. Upon completion of course, participants are encouraged to register for the Cloudera Certified Developer for Apache Hadoop (CCDH) Exam. Once the candidate clears the online exam, he is eligible for CCA & CCP Certifications by Cloudera.
Hadoop Developer Certification TypesThe Developer program includes two certification tiers: 1. Cloudera Certified Associate (CCA175) 2. Cloudera Certified Professional (CCP-DE575)
CCA- Cloudera Certified Associate (CCA175) CertificationxCloudera Certified Associate (CCA175) validates foundational skills and sets forth the groundwork to achieve expertise under CCP program
PrerequisitesFor Cloudera certification exam, no prerequisites are required. CCA175 follows the same features as Cloudera developer training for Spark and Hadoop.
Exam Details1. Registration fee is $295 2. Exam duration is 120 minutes 3. There are 10-12 performance-based tasks on CHD5 cluster 4. 70% is the passing score
CCP- Cloudera Certified Professional (CCP Data Engineer – DE575) CertificationCloudera Certified Professional (CCP) identifies and validates candidate’s expertise in technical skills.
PrerequisitesCandidates for CCP Data Engineer (DE575) should have in detail expertise and experience in developing data engineering solutions. 1. Registration fee is $600 2. Exam duration is 4 hours 3. Exam Question format – Eight customer problems with each with a unique, large data set, a 7-node high performance CDH5 cluster
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