- Beginner & Advanced level Classes.
- Hands-On Learning in Big Data.
- Best Practice for interview Preparation Techniques in Big Data.
- Lifetime Access for Student’s Portal, Study Materials, Videos & Top MNC Interview Question.
- Affordable Fees with Best curriculum Designed by Industrial Big Data Expert.
- Delivered by 9+ years of Java Certified Expert | 15454+ Students Trained & 400+ Recruiting Clients.
- Next Java Batch to Begin this week – Enroll Your Name Now!
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- Our Big Data certification training course lets you master the concepts of the Hadoop framework, Big Data tools, and methodologies to prepare you for success in your role as a Big Data Developer
- Ideal for those new to data science and interested in understanding why the Big Data era has come to be.
- You will gain an understanding of what insights big data can provide through hands-on-experience with the tools and systems used by big data scientists and engineers and also gain exposure to Industry best practices, Aptitude & SoftSkills
- Learn how various components of the Hadoop ecosystem fit into the Big Data processing lifecycle thorough experienced trainers and excellent lab facility
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This is How ACTE Students Prepare for Better Jobs
About Big Data Master Program Training Course in Chennai
Most Job Oriented Topics Covered
- Java Essentials
- Linux Administrator
- Big Data Hadoop
- Apache Spark And Scala
Is Big Data Master Program a good career choice?
What is the scope of Big Data Master Program in future?
What are the job opportunities in Big Data Master Program?
- Data Analyst.
- Database Administrator.
- Data Scientists.
- Big Data Architects.
- Database managers.
- Big Data Engineer.
- Machine Learning Engineer.
- Business Analyst.
Will ACTE Help Me With Placements After My Big Data Master Program Course Completion?
Is Big Data Master Program in demand?
What are the prerequisites for learning Big Data Master Program?
Is coding required for Big Data Master Program?
Will I Be Given Sufficient Practical Training In Big Data Master Program?
Is it worth learning Big Data Master Program?
How long would it take to master in Big Data Master Program?
Top reasons to consider a career in Big Data Master Program?
- Exponential Rise of Data.
- Higher Demand for Data Analysts Professionals.
- Huge Skill Gap.
- Unstructured/Semi-structured Data Analytics.
- Better Profile.
- 160+ Hours Course Duration
- 100% Job Oriented Training
- Industry Expert Faculties
- Free Demo Class Available
- Completed 500+ Batches
- Certification Guidance
ACTE TRAINING INSTITUTE PVT LTD is the unique Authorised Oracle Partner, Authorised Microsoft Partner, Authorised Pearson Vue Exam Center, Authorised PSI Exam Center, Authorised Partner Of AWS and National Institute of Education (nie) Singapore.
Master Page Curriculum
Syllabus of Java Essentials Course in ChennaiModule 1: Getting Familiar with Spark
- Apache Spark in Big Data Landscape and purpose of Spark
- Apache Spark vs. Apache MapReduce
- Components of Spark Stack
- Downloading and installing Spark
- Launch Spark
- Transformations and Actions in RDD
- Loading and Saving Data in RDD
- Key-Value Pair RDD
- MapReduce and Pair RDD Operations
- Playing with Sequence Files
- Using Partitioner and its impact on performance improvement
- Master SparkContext
- Initialize Spark with Java
- Create and Run Real-time Project with Spark
- Pass functions to Spark
- Submit Spark applications to the cluster
- AWS Architect
- Describe the features of AWS
- The features of AWS marketplace
- Describe the features of Amazon Compute Services
- Describe the features of Amazon Storage Services
- Describe the features of Amazon Network Services
- Describe the features of Amazon Database services
- Describe about various services in AWS
- Global Infrastruture – Regions and Availability Zones
- Create a free tier account in AWS and onboarding
- Introduction AWS management console
- Understand Identity Access Management of AWS
- Password policies set for users
- AWS User Account and Groups in detail
- Creating custom policies in AWS
- Creating Roles and associating policies
- Creating programmatic access and management console access for users
- Associating policies to the user and groups
- EC2 Instance
- Launch a basic EC2 instance
- Different types of Instances Reserved, On-demand, Spot, Dedicated
- Security groups and tags for EC2 instance
- Public key – Private key introduction and protecting EC2 with keys
- Attaching and detaching EBS volumes
- Launch an ec2 instance from an AMI
- Create custom AMI and working with different region
- Make use of amazon EBS volume and create snapshots
- Manage the configuration of your application
- Deploying a new instance from the created AMI
- Creating Launch configurations and make use of it for autoscaling groups
- Maintain a Fixed Number of Running EC2 Instances
- Dynamic Scaling
- The lifecycle of autoscaling
- Policies of autoscaling
- Load Balancing
- Different types of Loadbalancer in AWS
- Application Load balancer
- Network Load balancer
- Classic Load balancer
- Migrating classic load balancer to new load balancer
- Components and types of load balancing
- EBS (Elastic Block Storage)
- Delete EBS Volumes
- Attach and detach EBS volumes with EC2 instance
- Creating and deleting snapshots
- Object Storage in Cloud
- Introduction about S3 Buckets
- How S3 Uploading works and how to Download
- How to S3 Permissions
- How to implement S3 Object Versioning S3 Lifecycle Policies
- Storage Gateway
- Import Export
- S3 Transfer Acceleration
- Glacier storage
- Cloud Front
- Creating a cloud front distribution
- Hosting a website of cloud front distribution
- Implementing global restrictions
- Configuring origins and behaviors
- How to create hosted zones
- Hosting a website with custom domain name
- Understanding routing policies
- AWS Security Management
- AWS Shared Responsibilities and Securities
- Importance of Cloud Trail
- Describing Trust advisor
- Amazon Virtual Private Cloud (VPC)
- VPC Advantages and understanding IP addressing CIDR
- Default and Non-default VPC
- Different Components in VPC
- Describe, create, and manage Amazon Virtual Private Cloud
- Amazon VPC, Private Subnet, and Public Subnet
- AWS Networking, Security Groups, and Network ACLs
- Configuration and management of VPN connectivity
- ubnet and Subnet Mask
- Relational Database Service (RDS)
- Different database services of AWS: Amazon RDS, Dynamo DB, Redshift etc.
- Create MYSQL RDS Instance, Oracle RDS Instance, MS SQL RDS Instance
- Configuring the database
- Configuring backups
- Configuring the maintenance windows
- Connecting to the database
- Dynamo DB
- Learn about strong and eventual consistency
- Calculating Read write consistency
- Configuring alarms
- Monitoring Services
- Create and Configuring Monitoring services
- How to perform Setting thresholds and Configuring actions
- Creating a cloud watch alarm
- Getting statistics for ec2 instances
- Monitoring other AWS services
- Configuring Notifications
- Integrating cloud watch with Autoscaling
- Application Services – An Overview
- Creating a topic
- Create subscription
- Subscribed to the subscription
- SQS & SES
- Lambda and Elastic Beanstalk
- AWS Troubleshooting
- Troubleshooting using Cloud watch
- Troubleshooting using ELB
- Troubleshooting by using Cloud front
- AWS Architecture and Design
- How to manage Disaster Recovery and Backups
- Best Practice for DR and Backups
- AWS High Availability Design
- DevOps Fundamentals
- The ability to automate all aspects of a modern code delivery and deployment pipeline using:
- Source code management tools – CVS, Git
- Build tools – Apache ant, Maven
- Test automation tools – JUnit
- Continuous Integration Tools – Jenkins, Team city
- Configuration management tools – Chef, Puppet, Ansible
- Migration applications to AWS
- Introduction to AWS Services
- AWS Migration Strategy
- Stack creation using an AWS CloudFormation template
- AWS CAF (Cloud Adoption Framework)
- Application Migration To AWS
- Migrating an on premise Server or VM to cloud.
- Server Migration services;
- Agent based and agentless server migration service
- igrating on Premises Hyper VM to AWS AMI
- Migrating on Premises VMware VM to AWS AMI
- Database Migration to AWS
- AWS Database Migration services & challenges
- Usage of pre & post migration activities by using AWS
- portfolio of DB migration services
- Data Migration to AWS
- mazon Aurora DB within AWS environment:
- Transferring data to AWS in large scale
- Speeding up a large-scale data migration to S3 by enabling S3 Acceleration
- Elastic Docker Services
- Understanding the ECS usage in Docker
- Docker package usage in a monolithic application inside docker container services
- AWS elastic container service(ECS) used to migrate monolithic application to AWS Cloud
- AWS transfer for SFTP
- Snowball & Snowball edge services
- Direct Connect tool usage
- Understand various components of Spark cluster
- Configure Spark to modify
- Spark properties
- environmental variables
- logging properties
- Visualizing Jobs and DAGs
- Monitor Spark using the web UIs, metrics, and external instrumentation
- Understand performance tuning requirements
- Understanding the Streaming Architecture – DStreams and RDD batches Receivers
- Common transformations and actions on DStreams
Syllabus of SQL Course in ChennaiModule 1: Introduction to Java
- Introduction to Oracle Database
- Retrieve Data using the SQL SELECT Statement
- Learn to Restrict and Sort Data
- Usage of Single-Row Functions to Customize Output
- Invoke Conversion Functions and Conditional Expressions
- Aggregate Data Using the Group Functions
- Display Data From Multiple Tables Using Joins
- Use Sub-queries to Solve Queries
- The SET Operators
- Data Manipulation Statements
- Use of DDL Statements to Create and Manage Tables
- Other Schema Objects
- Control User Access
- Management of Schema Objects
- Manage Objects with Data Dictionary Views
- Manipulate Large Data Sets
- Data Management in Different Time Zones
- Retrieve Data Using Sub-queries
- Regular Expression Support
Syllabus of Linux Administrator Course in ChennaiModule 1 : Automating Programs
- Run Levels
- /etc/rc.d Files
- Customization of Run Levels
- cron and anacron
- at and batch
- Console Logon
- Controlling Console Login
- Virtual Consoles
- Serial Login
- Remote Login
- ssh Login
- Kernel Versions
- Kernel Source Files
- Kernel Patch Files
- Kernel Configuration
- Kernel Building
- Testing a New Kernel
- Partition Types
- Filesystem Types
- File Types
- File Security
- Boot Files
- User Files
- Administrator Files
- Configuration Files
- Log Files
- Process Info
- Kernel Config Info
- Hardware Info
- Changing /proc Info
- Key /bin Commands
- Key /sbin Commands
- man and info
- Using Shell Scripts
- Users and Groups
- Home Directories
- Password Files
- NIS Intro
- tar Files
- Patch Files
- Types of Devices
- /dev Namespace
- Types of Network Devices
- Monitoring Network Devices
- Controlling Network Services
- Squid Proxy Server
- X Servers and X Clients
- X Fonts
- GTK and KDE
Syllabus of BigData Hadoop Course in ChennaiModule 1: Introduction to Hadoop
- High Availability
- Advantages and Challenges
- What is Big data
- Big Data opportunities,Challenges
- Characteristics of Big data
- Hadoop Distributed File System
- Comparing Hadoop & SQL
- Industries using Hadoop
- Data Locality
- Hadoop Architecture
- Map Reduce & HDFS
- Using the Hadoop single node image (Clone)
- HDFS Design & Concepts
- Blocks, Name nodes and Data nodes
- HDFS High-Availability and HDFS Federation
- Hadoop DFS The Command-Line Interface
- Basic File System Operations
- Anatomy of File Read,File Write
- Block Placement Policy and Modes
- More detailed explanation about Configuration files
- Metadata, FS image, Edit log, Secondary Name Node and Safe Mode
- How to add New Data Node dynamically,decommission a Data Node dynamically (Without stopping cluster)
- FSCK Utility. (Block report)
- How to override default configuration at system level and Programming level
- HDFS Federation
- ZOOKEEPER Leader Election Algorithm
- Exercise and small use case on HDFS
- Map Reduce Functional Programming Basics
- Map and Reduce Basics
- How Map Reduce Works
- Anatomy of a Map Reduce Job Run
- Legacy Architecture ->Job Submission, Job Initialization, Task Assignment, Task Execution, Progress and Status Updates
- Job Completion, Failures
- Shuffling and Sorting
- Splits, Record reader, Partition, Types of partitions & Combiner
- Optimization Techniques -> Speculative Execution, JVM Reuse and No. Slots
- Types of Schedulers and Counters
- Comparisons between Old and New API at code and Architecture Level
- Getting the data from RDBMS into HDFS using Custom data types
- Distributed Cache and Hadoop Streaming (Python, Ruby and R)
- Sequential Files and Map Files
- Enabling Compression Codec’s
- Map side Join with distributed Cache
- Types of I/O Formats: Multiple outputs, NLINEinputformat
- Handling small files using CombineFileInputFormat
- Hands on “Word Count” in Map Reduce in standalone and Pseudo distribution Mode
- Sorting files using Hadoop Configuration API discussion
- Emulating “grep” for searching inside a file in Hadoop
- DBInput Format
- Job Dependency API discussion
- Input Format API discussion,Split API discussion
- Custom Data type creation in Hadoop
- ACID in RDBMS and BASE in NoSQL
- CAP Theorem and Types of Consistency
- Types of NoSQL Databases in detail
- Columnar Databases in Detail (HBASE and CASSANDRA)
- TTL, Bloom Filters and Compensation
- HBase Installation, Concepts
- HBase Data Model and Comparison between RDBMS and NOSQL
- Master & Region Servers
- HBase Operations (DDL and DML) through Shell and Programming and HBase Architecture
- Catalog Tables
- Block Cache and sharding
- DATA Modeling (Sequential, Salted, Promoted and Random Keys)
- JAVA API’s and Rest Interface
- Client Side Buffering and Process 1 million records using Client side Buffering
- HBase Counters
- Enabling Replication and HBase RAW Scans
- HBase Filters
- Bulk Loading and Co processors (Endpoints and Observers with programs)
- Real world use case consisting of HDFS,MR and HBASE
- Hive Installation, Introduction and Architecture
- Hive Services, Hive Shell, Hive Server and Hive Web Interface (HWI)
- Meta store, Hive QL
- OLTP vs. OLAP
- Working with Tables
- Primitive data types and complex data types
- Working with Partitions
- User Defined Functions
- Hive Bucketed Tables and Sampling
- External partitioned tables, Map the data to the partition in the table, Writing the output of one query to another table, Multiple inserts
- Dynamic Partition
- Differences between ORDER BY, DISTRIBUTE BY and SORT BY
- Bucketing and Sorted Bucketing with Dynamic partition
- RC File
- INDEXES and VIEWS
- MAPSIDE JOINS
- Compression on hive tables and Migrating Hive tables
- Dynamic substation of Hive and Different ways of running Hive
- How to enable Update in HIVE
- Log Analysis on Hive
- Access HBASE tables using Hive
- Hands on Exercises
- Pig Installation
- Execution Types
- Grunt Shell
- Pig Latin
- Data Processing
- Schema on read
- Primitive data types and complex data types
- Tuple schema, BAG Schema and MAP Schema
- Loading and Storing
- Filtering, Grouping and Joining
- Debugging commands (Illustrate and Explain)
- Validations,Type casting in PIG
- Working with Functions
- User Defined Functions
- Types of JOINS in pig and Replicated Join in detail
- SPLITS and Multiquery execution
- Error Handling, FLATTEN and ORDER BY
- Parameter Substitution
- Nested For Each
- User Defined Functions, Dynamic Invokers and Macros
- How to access HBASE using PIG, Load and Write JSON DATA using PIG
- Piggy Bank
- Hands on Exercises
- Sqoop Installation
- Import Data.(Full table, Only Subset, Target Directory, protecting Password, file format other than CSV, Compressing, Control Parallelism, All tables Import)
- Incremental Import(Import only New data, Last Imported data, storing Password in Metastore, Sharing Metastore between Sqoop Clients)
- Export data to RDBMS,HIVE and HBASE
- Hands on Exercises
- HCatalog Installation
- Introduction to HCatalog
- About Hcatalog with PIG,HIVE and MR
- Hands on Exercises
- Flume Installation
- Introduction to Flume
- Flume Agents: Sources, Channels and Sinks
- Log User information using Java program in to HDFS using LOG4J and Avro Source, Tail Source
- Log User information using Java program in to HBASE using LOG4J and Avro Source, Tail Source
- Flume Commands
- Use case of Flume: Flume the data from twitter in to HDFS and HBASE. Do some analysis using HIVE and PIG
- HUE.(Hortonworks and Cloudera)
- Workflow (Action, Start, Action, End, Kill, Join and Fork), Schedulers, Coordinators and Bundles.,to show how to schedule Sqoop Job, Hive, MR and PIG
- Real world Use case which will find the top websites used by users of certain ages and will be scheduled to run for every one hour
- Zoo Keeper
- HBASE Integration with HIVE and PIG
- Proof of concept (POC)
- Spark Overview
- Linking with Spark, Initializing Spark
- Using the Shell
- Resilient Distributed Datasets (RDDs)
- Parallelized Collections
- External Datasets
- RDD Operations
- Basics, Passing Functions to Spark
- Working with Key-Value Pairs
- RDD Persistence
- Which Storage Level to Choose?
- Removing Data
- Shared Variables
- Broadcast Variables
- Deploying to a Cluster
- Unit Testing
- Migrating from pre-1.0 Versions of Spark
- Where to Go from Here
Syllabus of Apache Spark & Scala Course in ChennaiModule 1: Introduction to Spark and Hadoop platform
- What is Hadoop platform
- Why Hadoop platform
- What is Spark
- Why spark
- Evolution of Spark
- Functional Programing Vs Object Orient Programing
- Scalable language
- Scala Overview
- Configuring Apache Spark
- JAVA Setup
- SCALA Editor
- Benefits of Scala
- Language Offerings
- Type inferencing
- Control Structures
- Traits and Mixins
- Classes and Objects
- First class functions
- Sub classes
- Case Classes
- Pattern Matching
- Exception Handling
- FILE Operations
- Spark Shell
- Parallel Programming
- Programming with RDD
- Broadcast Variables
- Spark Streaming
- Spark SQL
Hands-on Real Time Big Data Projects
Analyzing Historical Insurance claims
Use Hadoop features to predict patterns and share actionable insights for a car insurance company.
Analyzing employee sentiment
Perform sentiment analysis on employee review data gathered from Google, Netflix, and Facebook
Our Top Hiring Partner for Placements
ACTE Chennai offers placement opportunities as add-on to every student / professional who completed our classroom or online training. Some of our students are working in these companies listed below.
- We are associated with top organizations like HCL, Wipro, Dell, Accenture, Google, CTS, TCS, IBM etc. It make us capable to place our students in top MNCs across the globe
- Data is currently present everywhere be it a startup or a well-established organization, the data is being produced at a mammoth level. And this has subsequently mandated the need for the Big Data Analytics professional.
- Thus, Big Data provides Bigger career opportunities for both the freshers and experienced candidates with the right skills and knowledge. We will arrange the interview calls to students & prepare them to F2F interaction
- Our Trainers assist students in developing their resume matching the current industry needs
- We have a dedicated Placement support team wing that assist students in securing placement according to their requirements
- We will schedule Mock Exams and Mock Interviews to find out the GAP in Candidate Knowledge
Get Certified By IBM & Industry Recognized ACTE Certificate
Acte Certification is Accredited by all major Global Companies around the world. We provide after completion of the theoretical and practical sessions to fresher's as well as corporate trainees.
Our certification at Acte is accredited worldwide. It increases the value of your resume and you can attain leading job posts with the help of this certification in leading MNC's of the world. The certification is only provided after successful completion of our training and practical based projects.
Complete Your Course
a downloadable Certificate in PDF format, immediately available to you when you complete your Course
a physical version of your officially branded and security-marked Certificate.
About Experienced DevOps Trainer
- Our Big Data Training in Chennai. Trainers are highly certified professionals with 7+ years of experience in their respective domain as well as they are currently working with Top MNCs.
- A rigorous selection process is followed to recruit the trainers for this training program and only those who are able to demonstrate their thorough understanding of the subject are selected.
- All our Trainers are working with companies such as Cognizant, Dell, Infosys, IBM, L&T InfoTech, TCS, HCL Technologies, etc.
- The Instructors for the big data training are professionally qualified and certified. They have real-life experiences in the field. You will be learning from the best in the industry..
- Trainers have been actively working as consultants in the same domain, which has made them subject matter experts providing Best Big Data training to the students.
- We have received various prestigious awards for Big Data Training in Chennai from recognized IT organizations.
Big Data Course Reviews
I had completed my java with advance in by ACTE. The best place to excel your next phase of career. The trainers and faculty here were very friendly and comfortable. My trainer had explained each and every topics clearly and he won't move to the another topic until I was clear in it. Thanks to my trainer and ACTE for this wonderful opportunity!!
It is a great curse for beginners and for filling in some gaps for intermediate programmers. I wouldn't recommend it though for advanced programmers as the knowledge is rather basic and even at x2.0 speed it will become boring. Again, great course overall of beginners who want to get started with Java. Thanks!
This course is really great, it's very awesome that the course constantly get updated and you get answers in Q&A very fast, also instructor explanation is very good and clear, this is the only course you need to master Java and Mr.Venket does a really good job on that, the only con for me was that it didn't have much theory covered it went right to code without showing slides about how it works, but thankfully they are adding them now, so this is really a 5 star course, thank you ACTE for these amazing courses.
One of the best Programming courses that i have taken in a long time , ACTE has put lot of effort into making the course easy to learn , even for a Java Novice like me, which makes it truly a masterclass course to attend ,and the responses from Goran and others have been very helpful .
This Course is really a masterclass, covers from basic to advanced level. Would definitely recommend to anyone interested in learning core Java. All concepts explained in a well structured course. Tim teaches the concepts really well with coding examples. Follow along with him on code, you will learn a lot on writing a professional code too!.. Thanks ACTE & Team
Big Data Master Program Course FAQs
Looking for better Discount Price?
Does ACTE provide placement?
- ACTE is the Legend in offering placement to the students. Please visit our Placed Students List on our website
- We have strong relationship with over 700+ Top MNCs like SAP, Oracle, Amazon, HCL, Wipro, Dell, Accenture, Google, CTS, TCS, IBM etc.
- More than 3500+ students placed in last year in India & Globally
- ACTE conducts development sessions including mock interviews, presentation skills to prepare students to face a challenging interview situation with ease.
- 85% percent placement record
- Our Placement Cell support you till you get placed in better MNC
- Please Visit Your Student Portal | Here FREE Lifetime Online Student Portal help you to access the Job Openings, Study Materials, Videos, Recorded Section & Top MNC interview Questions
Is ACTE certification good?
- ACTE Gives Certificate For Completing A Course
- Certification is Accredited by all major Global Companies
- ACTE is the unique Authorized Oracle Partner, Authorized Microsoft Partner, Authorized Pearson Vue Exam Center, Authorized PSI Exam Center, Authorized Partner Of AWS and National Institute of Education (NIE) Singapore
Work On Live Projects?
- The entire Big Data Master Program training has been built around Real Time Implementation
- You Get Hands-on Experience with Industry Projects, Hackathons & lab sessions which will help you to Build your Project Portfolio
- GitHub repository and Showcase to Recruiters in Interviews & Get Placed
Who are the Trainers?
What if I miss one (or) more class?
What are the modes of training offered for this Big Data Master Program Course?
Why Should I Learn Big Data Master Program Course At ACTE?
- Big Data Master Program Course in ACTE is designed & conducted by Big Data Master Program experts with 10+ years of experience in the Big Data Master Program domain
- Only institution in India with the right blend of theory & practical sessions
- In-depth Course coverage for 60+ Hours
- More than 50,000+ students trust ACTE
- Affordable fees keeping students and IT working professionals in mind
- Course timings designed to suit working professionals and students
- Interview tips and training
- Resume building support
- Real-time projects and case studies
Can I Access the Course Material in Online?
What certification will I receive after course completion?
How Old Is ACTE?
What Will Be The Size Of A Big Data Master Program Batch At ACTE?
Will I Be Given Sufficient Practical Training In Big Data Master Program?
How Do I Enroll For The Big Data Master Program Course At ACTE?
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