An exhaustive course designed to transform you into a Big Data specialist!
Our Big Data Training Course is designed to provide you with hands-on training on sophisticated systems and tools used by Big Data Architects. During this course, you will learn all essential Big Data skills including MapReduce, HDFS, Hive, HBase, Yarn, Pig, Sqoop, Oozie, Flume and Zookeeper.
Unlike other training programs, our Big Data Training Course is carefully curated and led by some of the biggest industry experts working for Amazon, TCS, Neustar, Anthem and Social Code. Our training program offers and exhaustive and comprehensive curriculum which you cannot expect from other short-term certifications offered elsewhere.
Why Learn Big Data and Hadoop?
Organizations all over the world are realizing the benefits offered by Big Data and Hadoop. Many large companies are recruiting Big Data engineers in huge numbers. Forbes, McKinsey, IDC and Gartner all predict that this trend will continue to rise over the next few years. Already, there is a shortage of high quality Big Data engineers and there will be a huge demand for it in the near future.
Also, Big Data and Hadoop engineers are amongst the highest paid IT professionals in the world today. The average salary for a Big Data and Hadoop engineer is $135,000 and it is predicted that salaries will rise. The market for Big Data and Hadoop engineers is huge and this offers a great opportunity to engineering students and young professionals. By getting certified in Big Data and Hadoop, you’ll be on your way to building a successful career in Big Data.
Who Should Go for this Course?
Our Big Data Training Course is specifically designed for engineering students and early professionals who want to build a career in Big Data and Hadoop.
While our course is only meant for early professionals and engineering students, we do have plans to open new modules for other professional groups in the future.
About the Training
Our Big Data Training Course is designed to help engineering students and early professionals build a career in Big Data and Hadoop. Our hands-on training includes essential Big Data concepts including MapReduce, HDFS, Hive, Hbase, Yarn, Pig, Sqoop, Oozie, Flume and Zookeeper. You will learn how to use these concepts in real-life industry-based use cases in our training course.
Our training course is a stepping stone to starting a career in Big Data. You’ll be exposed to theory, practical, assignments, use cases and plenty of interaction with peers and industry experts. After completing our course, you will be certified as a Big Data and Hadoop engineer.
By completing our Big Data Training Course, you will learn the essential skills and become a Big Data specialist. Our training course will help you:
What are the System Requirements for this Course?
In order to successfully undergo our course, you’ll need a computer which satisfies minimum system requirements. This includes:
If your system does not meet these minimum requirements and you’re not looking to upgrade, you can still be a part of our training course. Just let us know and we’ll arrange for remote access to our Hadoop Cluster.
How Will I Execute the Practical?
To execute the practical, we’ll help you set up a virtual machine with local access on your computer. We’ll provide you with all the instructions and a detailed guide for setting up the environment to execute the practical.
In case your computer does not meet the minimum system requirements, you can always execute your practical through remote access to our Hadoop Cluster. Just let us know in advance and we’ll arrange for remote access.
And, if you have any doubts regarding the practical, you can always get in touch with our support team. Our expert support team will address your doubts and queries promptly.
|Chapter 1 - Big Data Overview|
|Big Data Overview - Part 1||13:13|
|Big Data Overview - Part 2|
|Big Data Overview - Part 3|
|Chapter 2 - Hadoop Overview|
|Introduction to Hadoop - Part 1|
|Introduction to Hadoop - Part 2|
|Introduction to Hadoop - Part 3|
|Cloudera Virtual Machine Installation|
|Chapter 3 - Hadoop Distributed File System (HDFS)|
|HDFS Replication and Re-replication Process|
|HDFS Write and Read Process|
|HDFS HA, Failover, Fencing and File Permission|
|Chapter 4 - Yet Another Resource Negotiator (YARN)|
|Challenges with Hadoop 1.0 - An introduction to YARN|
|Chapter 5 - MapReduce Programming Framework|
|Introduction to MapReduce Programming - Part 1|
|Introduction to MapReduce Programming - Part 2|
|Introduction to MapReduce Programming - Part 3|
|MapReduce - Driver Class, Mapper Class|
|MapReduce - Writable and WritableComparable|
|MapReduce - Reducer, Combiner etc|
|MapReduce - Word Count Example|
|MapReduce - Hot and Cold Day - Problem Statement|
|MapReduce - Hot and Cold Day - Solution|
|MapReduce - Log File Analysis - Problem Statement|
|MapReduce - Log File Analysis - Solution|
|MapReduce - YouTube Data Analysis - Problem Statement|
|MapReduce - YouTube Data Analysis - Solution|
|MapReduce - Patent Data Analysis - Problem Statement|
|MapReduce - Patent Data Analysis - Solution|
|Calculate Maximum Temperature|
|Chapter 6 - HIVE|
|HIVE Architecture and Component|
|HIVE Data Types|
|HIVE Data Model|
|Hive - Hive Commands|
|Hive - Create,Drop and Alter Hive Database|
|Hive - Create , Describe and Show Hive Table|
|Hive - Hive Managed Table|
|Hive - Hive Managed Table and Location key Word|
|Hive - Hive External Table and Location key Word|
|Hive - Hive Partitioned|
|Hive - Hive DROP and ALTER Tables|
|Hive - Hive DML|
|Hive - Hive Queries|
|Hive - Hive Join|
|Hive - Hive Built In Operators and Functions|
|Indian Railways Train Time Table Analysis - Problem Statement|
|Indian Railways Train Time Table Analysis - Solution|
|Airplane Crash History Data Analysis - Problem Statement|
|Airplane Crash History Data Analysis - Solution|
|Active Satellite Around Earth Data Analysis - Problem Statement|
|Active Satellite Around Earth Data Analysis - Solution|
|Chapter 7 - Apache PIG|
|PIG Data Model|
|PIG - Grunt Shell|
|PIG - Data Model Examples|
|PIG - Data Types and Operators|
|PIG - Load and Store Operator|
|PIG - GROUP Operator|
|PIG - JOIN Operator|
|PIG - UNION,SPLIT,DISTINCT,FOREACH,ORDER BY & LIMIT operators|
|PIG - Built In Functions and UDF|
|Chapter 8 - Apache HBase|
|HBase Data Model|
|HBase ACID properties|
|HBase - General Commands|
|HBase - Data Definition Language|
|HBase - Data Manipulation Language|
|HBase - Tools and Utilities - ImportTsv|
|HBase - Tools and Utilities - all others|
|HBase - Mapreduce implementation|
|Chapter 9 - Apache SQOOP|
|Cloudera MySQL Db and Sqoop Commands|
|Sqoop Import Tool and Examples|
|Sqoop Import Tool and Examples|
|Sqoop Import Tool and Examples|
|Sqoop Import into Hive Tables|
|Sqoop Imports - Use of Delimiters|
|Sqoop saved Jobs|
|Sqoop Merge Tool|
|Sqoop import-all Tool and Examples|
|Sqoop export Tool and Examples|
|Sqoop export Tool and Examples|
|Miscellaneous Topics in Sqoop|
|Chapter 10 - Apache FLUME|
|Flume Data Flow|
|Flume Agent Set up|
|Flume - Generate events and log them to HDFS|
|Flume - Simulate Web Log|
|Flume - Sequence Generator|
|Flume - Use Case - Fetching Twitter Data|
|Chapter 11 - Apache OOZIE|
|Oozie Workflow Engine|
|Oozie Coordinator and Bundle|
|Create Oozie Workflow job|
|Create Oozie Coordinator Application|
|Chapter 12 - Apache Zookeeper|
Data Architect at Anthem, Orange County, California
Co-Founder of BigDataHorizon
Alumni of IIM AHMEDABAD
Harish Kumar P V
Data Engineer at Leading MNC in US
Big Data - Architect , Designer
Unlike most other short-term Big Data certification programs, our training course is unique. Our comprehensive course covers all the necessary elements to transform you from a college student or a young professional to a certified Big Data expert.
Here are some of the salient features of our exhaustive Big Data Training Course:
There are no specific prerequisites to be eligible for our Big Data Training Course. As an early professional or an engineering student, you can go ahead and enroll for our training course.
That being said, knowledge of SQL, Java or OOPS programming will be beneficial in understanding our course, but it is not mandatory. However, we do encourage applicants to familiarize themselves with working on Linux/Unix platforms.
We will be providing “Java for Hadoop” and “Linux Basics” as FREE “Self Paced” course part of the Big Data and Hadoop certification course.
Your doubts and queries regarding our Big Data Training Course – answered!
1. Who will train me? How do you select faculties?
You will be trained by leading industry experts who are highly qualified and certified as instructors. We select faculties with extreme care so that you get the best possible training experience.
All of our instructors are industry practitioners with 10-15 years of relevant experience. Our instructors are subject matters in Big Data and Hadoop working in firms innovative tech firms like Amazon, TCS, Neustar, Social Code, Anthem. We also specially train our instructors so that they can offer you an enriching learning experience.
2. What are the different training models you offer?
We offer two different training models – instructor-led training and self-paced training. You can choose whichever type of training model you’re comfortable with.
Our instructor-led training model includes prerecorded video content for you to go through. And, you’ll have access to 8 to 10 live training sessions (each 2 hours duration) with our faculties to discuss concepts, clarify doubts and get your questions answered.
Our self-paced training model allows you to complete the training course at your own speed. We’ll provide you with prerecorded video content and you can clarify doubts and discuss concepts in our online forum. Additionally we will arrange 6 to 8 doubt clearing sessions (1 hour each ) which will be communicated once you register for the course.
3. What if I miss a class or training session?
When you choose our Big Data Training Course, you need not worry about missing a class or training session. We’ll provide you with prerecorded video content which you can access at any time. And, if you miss any instructor session, you can always attend the missed session with any other live batch.
4. How can I enroll for your training?
You can enroll for our Big Data Training Course right here on our website
5. How do I pay for the training course?
We accept a variety of payment options, which include online money transfer, credit and debit cards (Visa, Mastercard. You can choose any of these payment options as per your convenience.
6. Do you offer group discounts?
Yes, we do! To find out more about what group discounts we offer on our Big Data Training Course, please get in touch with us.
7. How do I learn more about your training course?
If you’d like to learn more about our Big Data Training Course before enrollment, you can always get in touch with our support team. We’ll connect you to customer service representatives who will offer you all the information you need about our training course.
8. How do I get assistance on the training?
We’re committed to make our training a helpful and enriching learning experience. If you choose our instructor-led model, our expert instructors will offer you all the assistance you need on the training. Alternatively, if you choose our self-paced model, you can always use our online forum to interact with peers for any assistance.
9. What if I have any more queries?
If we haven’t answered all of your questions or if you have any specific query, please feel free to get in touch with us using our “Contact Us”page. We’ll do everything we can to resolve your queries.