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Intellipaat Big Data Course in Sydney lets you master Big Data Hadoop and Spark online to get ready for the Cloudera CCA Spark and Hadoop Developer Certification (CCA175), as well as master Hadoop administration with 14 real-time industry-oriented case-study projects. Get the best Hadoop training in Sydney from certified mentors as well as earn IBM Big Data Certificate.
Intellipaat is one of the biggest e-learning institutes best known for providing highly competitive Big Data Hadoop training in Sydney, Australia. This training is divided into four different verticals, i.e., Developer, Admin, Analyst and Testing. Some of the significant topics covered by this master’s program are HDFS, ZooKeeper, Sqoop, Impala, etc. Once a learner successfully carries out the project work at the end of the course, he will be awarded with the IBM certification.
There is no pre-requisite to take up this Big Data training and to master Hadoop. But basics of UNIX, SQL and Java would be beneficial. At Intellipaat, we provide the complimentary Linux and Java courses with our Big Data certification training to brush-up the required skills so that you are good on your Hadoop learning path.
Sydney is the economic and financial hub for the world’s top-notch firms in the entire Asia Pacific region. Growing at a swift pace, this city is filled with the companies which are investing heavily into research and analytics. As Big Data is driving most of the industries nowadays, the application of technologies like Hadoop is rising rapidly. Therefore, there is a huge scope of Hadoop professionals in this city.
Sydney is one of the most developed cities in Australia inviting investors from across the globe. As Data Analytics has emerged as a vital operation over past few years, the companies have started paying extra attention towards extracting meaningful insights from these data. As it is possible only through skilled Big Data professionals, the trend for job opportunities is constantly going upwards in this city.
Big Data has become the definite way to success in this highly digitized technology world. Since Hadoop is a prominent name in this direction, learning this technology will help the candidates launch their careers in this space.
As part of this training, learners will be carrying out 14 real-time projects based on Hadoop and its components like MapReduce, Hive, Spark, Pig, Oozie, Flume, Weblog Analytics, etc. Moreover, this training course helps them prepare for CCA175 and CCAH exams through practical lab sessions, assignments and interactive sessions.
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1.1 The architecture of Hadoop cluster
1.2 What is High Availability and Federation?
1.3 How to setup a production cluster?
1.4 Various shell commands in Hadoop
1.5 Understanding configuration files in Hadoop
1.6 Installing a single node cluster with Cloudera Manager
1.7 Understanding Spark, Scala, Sqoop, Pig, and Flume
2.1 Introducing Big Data and Hadoop
2.2 What is Big Data and where does Hadoop fit in?
2.3 Two important Hadoop ecosystem components, namely, MapReduce and HDFS
2.4 In-depth Hadoop Distributed File System – Replications, Block Size, Secondary Name node, High Availability and in-depth YARN – resource manager and node manager
Hands-on Exercise:
1. HDFS working mechanism
2. Data replication process
3. How to determine the size of the block?
4. Understanding a data node and name node
3.1 Learning the working mechanism of MapReduce
3.2 Understanding the mapping and reducing stages in MR
3.3 Various terminologies in MR like Input Format, Output Format, Partitioners, Combiners, Shuffle, and Sort
Hands-on Exercise:
1. How to write a WordCount program in MapReduce?
2. How to write a Custom Partitioner?
3. What is a MapReduce Combiner?
4. How to run a job in a local job runner
5. Deploying a unit test
6. What is a map side join and reduce side join?
7. What is a tool runner?
8. How to use counters, dataset joining with map side, and reduce side joins?
4.1 Introducing Hadoop Hive
4.2 Detailed architecture of Hive
4.3 Comparing Hive with Pig and RDBMS
4.4 Working with Hive Query Language
4.5 Creation of a database, table, group by and other clauses
4.6 Various types of Hive tables, HCatalog
4.7 Storing the Hive Results, Hive partitioning, and Buckets
Hands-on Exercise:
1. Database creation in Hive
2. Dropping a database
3. Hive table creation
4. How to change the database?
5. Data loading
6. Dropping and altering table
7. Pulling data by writing Hive queries with filter conditions
8. Table partitioning in Hive
9. What is a group by clause?
5.1 Indexing in Hive
5.2 The ap Side Join in Hive
5.3 Working with complex data types
5.4 The Hive user-defined functions
5.5 Introduction to Impala
5.6 Comparing Hive with Impala
5.7 The detailed architecture of Impala
Hands-on Exercise:Â
1. How to work with Hive queries?
2. The process of joining the table and writing indexes
3. External table and sequence table deployment
4. Data storage in a different table
6.1 Apache Pig introduction and its various features
6.2 Various data types and schema in Hive
6.3 The available functions in Pig, Hive Bags, Tuples, and Fields
Hands-on Exercise:Â
1. Working with Pig in MapReduce and local mode
2. Loading of data
3. Limiting data to 4 rows
4. Storing the data into files and working with Group By, Filter By, Distinct, Cross, Split in Hive
7.1 Apache Sqoop introduction
7.2 Importing and exporting data
7.3 Performance improvement with Sqoop
7.4 Sqoop limitations
7.5 Introduction to Flume and understanding the architecture of Flume
7.6 What is HBase and the CAP theorem?
Hands-on Exercise:Â
1. Working with Flume to generate Sequence Number and consume it
2. Using the Flume Agent to consume the Twitter data
3. Using AVRO to create Hive Table
4. AVRO with Pig
5. Creating Table in HBase
6. Deploying Disable, Scan, and Enable Table
8.1 Using Scala for writing Apache Spark applications
8.2 Detailed study of Scala
8.3 The need for Scala
8.4 The concept of object-oriented programming
8.5 Executing the Scala code
8.6 Various classes in Scala like getters, setters, constructors, abstract, extending objects, overriding methods
8.7 The Java and Scala interoperability
8.8 The concept of functional programming and anonymous functions
8.9 Bobsrockets package and comparing the mutable and immutable collections
8.10 Scala REPL, Lazy Values, Control Structures in Scala, Directed Acyclic Graph (DAG), first Spark application using SBT/Eclipse, Spark Web UI, Spark in Hadoop ecosystem.
Hands-on Exercise:
1. Writing Spark application using Scala
2. Understanding the robustness of Scala for Spark real-time analytics operation
9.1 Detailed Apache Spark and its various features
9.2 Comparing with Hadoop
9.3 Various Spark components
9.4 Combining HDFS with Spark and Scalding
9.5 Introduction to Scala
9.6 Importance of Scala and RDD
Hands-on Exercise:Â
1. The Resilient Distributed Dataset (RDD) in Spark
2. How does it help to speed up Big Data processing?
10.1 Understanding the Spark RDD operations
10.2 Comparison of Spark with MapReduce
10.3 What is a Spark transformation?
10.4 Loading data in Spark
10.5 Types of RDD operations viz. transformation and action
10.6 What is a Key/Value pair?
Hands-on Exercise:Â
1. How to deploy RDD with HDFS?
2. Using the in-memory dataset
3. Using file for RDD
4. How to define the base RDD from an external file?
5. Deploying RDD via transformation
6. Using the Map and Reduce functions
7. Working on word count and count log severity
11.1 The detailed Spark SQL
11.2 The significance of SQL in Spark for working with structured data processing
11.3 Spark SQL JSON support
11.4 Working with XML data and parquet files
11.5 Creating Hive Context
11.6 Writing Data Frame to Hive
11.7 How to read a JDBC file?
11.8 Significance of a Spark data frame
11.9 How to create a data frame?
11.10 What is schema manual inferring?
11.11 Work with CSV files, JDBC table reading, data conversion from Data Frame to JDBC, Spark SQL user-defined functions, shared variable, and accumulators
11.12 How to query and transform data in Data Frames?
11.13 How data frame provides the benefits of both Spark RDD and Spark SQL?
11.14 Deploying Hive on Spark as the execution engine
Hands-on Exercise:
1. Data querying and transformation using Data Frames
2. Finding out the benefits of Data Frames over Spark SQL and Spark RDD
12.1 Introduction to Spark MLlib
12.2 Understanding various algorithms
12.3 What is Spark iterative algorithm?
12.4 Spark graph processing analysis
12.5 Introducing Machine Learning
12.6 K-Means clustering
12.7 Spark variables like shared and broadcast variables
12.8 What are accumulators?
12.9 Various ML algorithms supported by MLlib
12.10 Linear regression, logistic regression, decision tree, random forest, and K-means clustering techniques
Hands-on Exercise:Â
1. Building a recommendation engine
13.1 Why Kafka?
13.2 What is Kafka?
13.3 Kafka architecture
13.4 Kafka workflow
13.5 Configuring Kafka cluster
13.6 Basic operations
13.7 Kafka monitoring tools
13.8 Integrating Apache Flume and Apache Kafka
Hands-on Exercise:
1. Configuring Single Node Single Broker Cluster
2. Configuring Single Node Multi Broker Cluster
3. Producing and consuming messages
4. Integrating Apache Flume and Apache Kafka.
14.1 Introduction to Spark streaming
14.2 The architecture of Spark streaming
14.3 Working with the Spark streaming program
14.4 Processing data using Spark streaming
14.5 Requesting count and DStream
14.6 Multi-batch and sliding window operations
14.7 Working with advanced data sources
14.8 Features of Spark streaming
14.9 Spark Streaming workflow
14.10 Initializing StreamingContext
14.11 Discretized Streams (DStreams)
14.12 Input DStreams and Receivers
14.13 Transformations on DStreams
14.14 Output Operations on DStreams
14.15 Windowed operators and its uses
14.16 Important Windowed operators and Stateful operators
Hands-on Exercise:
1. Twitter Sentiment analysis
2. Streaming using Netcat server
3. Kafka-Spark streaming
4. Spark-Flume streaming
15.1 Create a 4-node Hadoop cluster setup
15.2 Running the MapReduce Jobs on the Hadoop cluster
15.3 Successfully running the MapReduce code
15.4 Working with the Cloudera Manager setup
Hands-on Exercise:
1. The method to build a multi-node Hadoop cluster using an Amazon EC2 instance
2. Working with the Cloudera Manager
16.1 Overview of Hadoop configuration
16.2 The importance of Hadoop configuration file
16.3 The various parameters and values of configuration
16.4 The HDFS parameters and MapReduce parameters
16.5 Setting up the Hadoop environment
16.6 The Include and Exclude configuration files
16.7 The administration and maintenance of name node, data node directory structures, and files
16.8 What is a File system image?
16.9 Understanding Edit log
Hands-on Exercise:
1. The process of performance tuning in MapReduce
17.1 Introduction to the checkpoint procedure, name node failure
17.2 How to ensure the recovery procedure, Safe Mode, Metadata and Data backup, various potential problems and solutions, what to look for and how to add and remove nodes
Hands-on Exercise:
1. How to go about ensuring the MapReduce File System Recovery for different scenarios
2. JMX monitoring of the Hadoop cluster
3. How to use the logs and stack traces for monitoring and troubleshooting
4. Using the Job Scheduler for scheduling jobs in the same cluster
5. Getting the MapReduce job submission flow
6. FIFO schedule
7. Getting to know the Fair Scheduler and its configuration
18.1 How ETL tools work in Big Data industry?
18.2 Introduction to ETL and data warehousing
18.3 Working with prominent use cases of Big Data in ETL industry
18.4 End-to-end ETL PoC showing Big Data integration with ETL tool
Hands-on Exercise:
1. Connecting to HDFS from ETL tool
2. Moving data from Local system to HDFS
3. Moving data from DBMS to HDFS,
4. Working with Hive with ETL Tool
5. Creating MapReduce job in ETL tool
19.1 Working towards the solution of the Hadoop project solution
19.2 Its problem statements and the possible solution outcomes
19.3 Preparing for the Cloudera certifications
19.4 Points to focus on scoring the highest marks
19.5 Tips for cracking Hadoop interview questions
Hands-on Exercise:
1. The project of a real-world high value Big Data Hadoop application
2. Getting the right solution based on the criteria set by the Intellipaat team
20.1 Importance of testing
20.2 Unit testing, Integration testing, Performance testing, Diagnostics, Nightly QA test, Benchmark and end-to-end tests, Functional testing, Release certification testing, Security testing, Scalability testing, Commissioning and Decommissioning of data nodes testing, Reliability testing, and Release testing
21.1 Understanding the Requirement
21.2 Preparation of the Testing Estimation
21.3 Test Cases, Test Data, Test Bed Creation, Test Execution, Defect Reporting, Defect Retest, Daily Status report delivery, Test completion, ETL testing at every stage (HDFS, Hive and HBase) while loading the input (logs, files, records, etc.) using Sqoop/Flume which includes but not limited to data verification, Reconciliation, User Authorization and Authentication testing (Groups, Users, Privileges, etc.), reporting defects to the development team or manager and driving them to closure
21.4 Consolidating all the defects and create defect reports
21.5 Validating new feature and issues in Core Hadoop
22.1 Report defects to the development team or manager and driving them to closure
22.2 Consolidate all the defects and create defect reports
22.3 Responsible for creating a testing framework called MRUnit for testing of MapReduce programs
23.1 Automation testing using the OOZIE
23.2 Data validation using the query surge tool
24.1 Test plan for HDFS upgrade
24.2 Test automation and result
25.1 Test, install and configure
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Working with MapReduce, Hive, and Sqoop
In this project, you will successfully import data using Sqoop into HDFS for data analysis. The transfer will be from Sqoop data transfer from RDBMS to Hadoop. You will code in Hive query language and carry out data querying and analysis. You will acquire an understanding of Hive and Sqoop after completion of this project.
Work on MovieLens Data For Finding the Top Movies
Create the top-ten-movies list using the MovieLens data. For this project, you will use the MapReduce program for working on the data file, Apache Pig for analyzing data, and Apache Hive data warehousing and querying. You will be working with distributed datasets.
Hadoop YARN Project: End-to-End PoC
Bring the daily incremental data into the Hadoop Distributed File System. As part of the project, you will be using Sqoop commands to bring the data into HDFS, working with the end-to-end flow of transaction data, and the data from HDFS. You will work on a live Hadoop YARN cluster. You will work on the YARN central resource manager.
Table Partitioning in Hive
In this project, you will learn how to improve the query speed using Hive data partitioning. You will get hands-on experience in partitioning of Hive tables manually, deploying single SQL execution in dynamic partitioning, and bucketing of data to break it into manageable chunks.
Connecting Pentaho with Hadoop Ecosystem
Deploy ETL for data analysis activities. In this project, you will challenge your working knowledge of ETL and Business Intelligence. You will configure Pentaho to work with Hadoop distribution as well as load, transform, and extract data into the Hadoop cluster.
Multi-node Cluster Setup
Set up a Hadoop real-time cluster on Amazon EC2. The project will involve installing and configuring Hadoop. You will need to run a Hadoop multi-node using a 4-node cluster on Amazon EC2 and deploy a MapReduce job on the Hadoop cluster. Java will need to be installed as a prerequisite for running Hadoop.
Hadoop Testing Using MRUnit
In this project, you will be required to test MapReduce applications. You will write JUnit tests using MRUnit for MapReduce applications. You will also be doing mock static methods using PowerMock and Mockito and implementing MapReduce Driver for testing the map and reduce pair
Hadoop Web Log Analytics
Derive insights from web log data. The project involves the aggregation of log data, implementation of Apache Flume for data transportation, and processing of data and generating analytics. You will learn to use workflow and data cleansing using MapReduce, Pig, or Spark.
Hadoop Maintenance
Through this project, you will learn how to administer a Hadoop cluster for maintaining and managing it. You will be working with the name node directory structure, audit logging, data node block scanner, balancer, Failover, fencing, DISTCP, and Hadoop file formats.
Twitter Sentiment Analysis
Find out what is the reaction of the people to the demonetization move by India by analyzing their tweets. You will have to download the tweets, load them into Pig storage, divide the tweets into words to calculate sentiment, rate the words from +5 to −5 on the AFFIN dictionary, filter them and analyze sentiment.
Analyzing IPL T20 Cricket
This project will require you to analyze an entire cricket match and get any details of the match. You will need to load the IPL dataset into HDFS. You will then analyze that data using Apache Pig or Hive. Based on the user queries, the system will have to give the right output.
Movie Recommendation
Recommend the most appropriate movie to a user based on his taste. This is a hands-on Apache Spark project, which will include the creation of collaborative filtering, regression, clustering, and dimensionality reduction. You will need to make use of the Apache Spark MLlib component and statistical analysis.
Twitter API Integration for Tweet Analysis
Analyze the user sentiment based on a tweet. In this Twitter analysis project, you will integrate the Twitter API and use Python or PHP for developing the essential server-side codes. You will carry out filtering, parsing, and aggregation depending on the tweet analysis requirement.
Data Exploration Using Spark SQL – Wikipedia Data Set
In this project, you will be making use of the Spark SQL tool for analyzing Wikipedia data. You will be integrating Spark SQL for batch analysis, Machine Learning, visualizing, and processing of data and ETL processes, along with real-time analysis of data.
This training course is designed to help you clear the Cloudera Spark and Hadoop Developer Certification (CCA175) exams. The entire training course content is in line with these certification programs and helps you clear these certification exams with ease and get the best jobs in the top MNCs.
As part of this Big Data course in Sydney, you will be working on real-time projects and assignments that have immense implications in the real-world industry scenarios, thus helping you fast-track your career effortlessly.
At the end of this Big Data Hadoop training in Sydney, there will be quizzes that perfectly reflect the type of questions asked in the respective certification exams and help you score better.
Intellipaat Course Completion Certificate will be awarded upon the completion of the project work (after expert review) and upon scoring at least 60% marks in the quiz. Intellipaat certification is well recognized in top 80+ MNCs like Ericsson, Cisco, Cognizant, Sony, Mu Sigma, Saint-Gobain, Standard Chartered, TCS, Genpact, Hexaware, etc.
I'm really thankful to Intellipaat about the Hadoop Architect Course with Big Data certification. First of all, the team supported me in finding the best Big Data online course based on my experiences and current assignment. Also, the session is so practical, and the trainers are seasoned and available for any queries even in offline mode after the sessions of Big Data Hadoop course in Sydney. I'm really recommending this training to anyone who wants to understand the concept of Big Data by learning Hadoop and its ecosystem and obtain a most valuable certification in Hadoop from a recognized institution.
This is regards to conveying my deepest gratitude to Intellipaat. The quality and methodology of the online Hadoop training is matchless. The self-study program for which I had enrolled for big data Hadoop training ticked all the right boxes. I had access to free tutorials and videos to help me in my learning endeavour. A special mention must be made regarding the promptness and enthusiasm that Intellipaat showed when it comes to query resolution and doubt clearance. Kudos!
I wish I knew about Intellipaat online Hadoop training before. I have hugely benefitted from this big data Hadoop certification course. Excellent course material and highly recommended Hadoop trainers will provide you full understanding of Hadoop concepts.
Matt Peter
This online big data Hadoop training is extremely industry-focused and job-oriented. Overall I am giving 10 out of 10 for this Hadoop certification course from Intellipaat!
Mohit Rana
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A big thank you to the entire Intellipaat Big Data Hadoop Team! You have delivered a great Hadoop online certification training course, with equally informative Hadoop online tutorials, Big Data video tutorials that are absolutely free. Highly experienced and qualified Big Data Hadoop trainers made the learning process completely effortless and enjoyable for me. I am extremely happy for having enrolled for the best Hadoop training!
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sheelam Khan
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I had taken Intellipaat Big Data Hadoop Online. An excellent online mode of learning. Now I am confident I can look out for a career in Big Data. Upon successfully completing this big data course Thanks again and looking forward to a lot more learning from Intellipaat !! I highly recommend the big data online course. All the best.
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I am completely satisfied with the Intellipaat big data hadoop training. The trainer came with over a decade of industry experience. The entire big data online course was segmented into modules that were created with care so that the learning is complete and as per the industry needs.
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Full marks for the Intellipaat support team for providing excellent support services. Hadoop was new to me and I used to have many queries, but the support team was very qualified and very patient in listening to my queries and resolving them to my highest expectations. The entire Big Data course was completely oriented towards the practical aspects.
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I work as a Senior Technology Architect at Infosys. I work on many projects related to big data technology. After joining Intellipaat, one of the best Hadoop training institutes in Sydney, I feel more confident in working on hadoop related pojects and the outcome is much better compared to before. Thanks intellipaat team.
I took hadoop online training course from intellipaat and successfully completed it. I have already started working with big data hadoop team in my company. It feels amazing to be a part of hadoop group I highly recommend this as one of the best Big Data Training institutes in Sydney to everybody who wants to make their career in big data domain.
Intellipaat big data Hadoop developer course with spark is a boom for building your skills from beginning to advanced level. As I wanted to start with a big data course but I was not knowing how because I had no idea how to start, from where to start, and what to start, then I finally decided to take a course of big data Hadoop developer from Intellipaat. Intellipaat showed me the right career path to me. After completion of course Intellipaat provided course completion certificate and certificate from IBM . These certificates helped me to stand out among many in interview. Intellipaat - "The Career guide for Big Data Developer"
Excellent course, I found Intellipaat's training team to be talented in their respective domain. My training was very good as it helped me in upgrading my skills, which proved to be a turning point in my career. Intellipaat's mentor was well-experienced and his teaching method was really great. This online course helped me to get deep understanding of the technology. Moreover, the excercise and projects provided as a part of the course made me to get hands-on experience. Besides, the online support team was very helpful and offered their assistance as and when I needed via calls and emails.
Genuine platform for learning. I finished my course recently from Intellipaat. The trainers were excellent in teaching. Further, the course was well-structured and the lectures are really flexible. I am currently working and I still get the time to complete the course within the given time and it is mainly possible because of the 24*7 support system and the clarity of their teaching. Besides, they make us do hands-on exercises and project, making us gain in-depth knowledge of the concepts. I strongly recommend others to take this course as well.
Amazing course learning experience It was a great learning experience with Intellipaat. The coursware is comprehensive, and has a variety of material like videos, PPTs, and PDFs that are neatly organized. Further, there are hands-on projects, assignments, code files for each module. And most importantly, the support I received as a learner while pursuing my course was exemplary.
It is a known fact that the demand for Hadoop professionals far outstrips the supply. So, if you want to learn and make a career in Hadoop, then you need to enroll for Intellipaat Hadoop course online which is the most recognized name in Hadoop training and certification. Intellipaat Hadoop training includes all major components of Big Data and Hadoop like Apache Spark, MapReduce, HBase, HDFS, Pig, Sqoop, Flume, Oozie and more. The entire Intellipaat Big Data training in Sydney has been created by industry professionals. You will get 24/7 lifetime support, high-quality course material and videos and free upgrade to latest version of course material. Thus, it is clearly a one-time investment for a lifetime of benefits.
Intellipaat has a plethora of courses that will help you become a Data Analyst. The comprehensive Data Scientist courses, Big Data, Python, Machine Learning, Data Science Masters course, and others will help you to process, inspect, cleanse, transform, and create model data to gain useful information.
At Intellipaat, you can enroll in either the instructor-led online training or self-paced training. Apart from this, Intellipaat also offers corporate training for organizations to upskill their workforce. All trainers at Intellipaat have 12+ years of relevant industry experience, and they have been actively working as consultants in the same domain, which has made them subject matter experts. Go through the sample videos to check the quality of our trainers.
Intellipaat is offering the 24/7 query resolution, and you can raise a ticket with the dedicated support team at anytime. You can avail of the email support for all your queries. If your query does not get resolved through email, we can also arrange one-on-one sessions with our trainers.
You would be glad to know that you can contact Intellipaat support even after the completion of the training. We also do not put a limit on the number of tickets you can raise for query resolution and doubt clearance.
Intellipaat is offering you the most updated, relevant, and high-value real-world projects as part of the training program. This way, you can implement the learning that you have acquired in real-world industry setup. All training comes with multiple projects that thoroughly test your skills, learning, and practical knowledge, making you completely industry-ready.
You will work on highly exciting projects in the domains of high technology, ecommerce, marketing, sales, networking, banking, insurance, etc. After completing the projects successfully, your skills will be equal to 6 months of rigorous industry experience.
Intellipaat actively provides placement assistance to all learners who have successfully completed the training. For this, we are exclusively tied-up with over 80 top MNCs from around the world. This way, you can be placed in outstanding organizations such as Sony, Ericsson, TCS, Mu Sigma, Standard Chartered, Cognizant, and Cisco, among other equally great enterprises. We also help you with the job interview and résumé preparation as well.
You can definitely make the switch from self-paced training to online instructor-led training by simply paying the extra amount. You can join the very next batch, which will be duly notified to you.
Once you complete Intellipaat’s training program, working on real-world projects, quizzes, and assignments and scoring at least 60 percent marks in the qualifying exam, you will be awarded Intellipaat’s course completion certificate. This certificate is very well recognized in Intellipaat-affiliated organizations, including over 80 top MNCs from around the world and some of the Fortune 500companies.
Apparently, no. Our job assistance program is aimed at helping you land in your dream job. It offers a potential opportunity for you to explore various competitive openings in the corporate world and find a well-paid job, matching your profile. The final decision on hiring will always be based on your performance in the interview and the requirements of the recruiter.
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