Get updates on Eligibility, Admission, Placements Fees Structure
Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery | Frequency Of Classes |
|---|---|---|---|
| English | Self Study, Virtual Classroom | Video and Text Based | Weekends |
Course Overview
Investment interests are being observed by companies of all sizes in building Big Data capabilities to add value to their core business operations. Thus, the demand for Big Data Engineers skilled in Arithmetic, Business Management, and Technology is experiencing incremental developments. Moreover, especially applicable in developing nations, there is a lack of aptly skilled Big Data Engineers. Hence, recruiters are usually left with vacant spots in their organizations. This is where they are willing to chalk out very impressive remunerations for professionals in this field.
Globally, the advent of data and the kind of insights it can bring about is gold-dust, thereby catching the attention of businesses. Moreover, the quantum of data being tapped into has come a long way in the last 5 years and is only increasing every quarter. Additionally, there needs to be systems in place that can extract actionable insights from the data. It is then that it benefits the organization in its truest sense.
The Post Graduate Certification Program in Big Data Engineering will introduce the participants to the role of Linux, SQL, and Java in this arena. Moreover, there will be two Mid-Program projects and a final Industry-grade exposure. These facets will enable students to have a very realistic experience. Moving on, the Big Data Engineering program will dwell into the building blocks for big data, followed by Distributed and Parallel computing.
The Highlights
- Nine months program
- 450 hours of learning
- Weekend classes
- Over 100 case studies
Programme Offerings
- Online Classes
- 2 way Interaction
- 450+ hours of learning
- Industrial grade Project
Courses and Certificate Fees
| Certificate Availability | Certificate Providing Authority |
|---|---|
| yes | NIT RourkelaEdureka |
The tuition fee is as follows:
Program Fee | Rs. 1,97,500 |
EMI | Rs. 12,000 per month |
Eligibility Criteria
Education
Students from the science stream in grade-12, having graduated with a Bachelor's Degree from college, and an avid interest in Big Data may apply.
What you will learn
The Post Graduate Certification Program in Big Data Engineering with enabling the students to have a strong grasp on the following topics:
- The basic underlying principles of SQL, Linux, and Java
- Develop a deep understanding of Big Data, Data Structures, and Algorithms
- An introduction to distributed and parallel computing
- Gain a deep understanding of advanced hive concepts
- Explore digital disruptions of Big Data models
- Expertise to transform businesses with large-scale data warehousing
- Get a bird’s eye view of designing a scalable data pipeline
- Strategies to invest in Big Data Analytics
Who it is for
The Post Graduate Certification Program in Big Data Engineering at NIT Rourkela consists of a strong focus for the newly experienced, aspiring to formalize their learning. The following groups of students will benefit the most from this program:
- Early professionals looking to transition into the realm of Big Data
- Graduates looking for a specialized curriculum for Big Data Engineering
- Data Science professionals looking to further their skill sets
Admission Details
The admission steps are briefly outlined in the following section:
Registration:
- Please share details through a short form on our website
Program Application:
- Next, tell us about your academic history, work experience, and other relevant aspects in more detail. The format has been kept fairly simple to navigate.
Interview:
- This stage involves an online interview with industry experts who gauge your passion and capacity for the program. Choose an interview date from the available slots and pay the interview booking fee of Rs. 1,000.
Scholarship and Offer Letter:
- Based on the previous steps, the final offer may be made. If an offer is extended, be rest assured that it has also been considered for a scholarship. Thus, the offer has been vetted from all aspects and can thus be interpreted as complete.
For more information please contact:
- Phone Number: +91-804-042-3805
- Email: bigdata.pgp@edureka.co
Application Details
The Application form is linked on the program page. A fairly straightforward form opens up where the applicant would be required to enter their educational and professional background.
The Syllabus
- Career Assistance Services
- Workshop
- Linux Fundamentals
- SQL Essentials
- Java Essentials for Big Data
- Pre-requisites Test
- Introduction to Big Data, Data Structures and Algorithms
- Non-linear Data Structures for Big Data
- Designing High Performant Distributed Algorithms
- Tool Stack Options for Big Data
- Doubt Clearing Session 1
- Additional Resources
- Question Bank
- Background of Distributed and Parallel Computing Systems
- Hadoop - A Distributed and Highly Scalable Computing Platform
- Storing Big Data in a Distributed Cluster- HDFS
- Advanced HDFS Concepts
- MapReduce Computational Model
- Doubt Clearing Session 2
- Scala Essentials for Spark – I
- Scala Essentials for Spark – II
- In-memory Computation for Big Data
- Advanced RDDs Concepts in Spark
- Doubt Clearing Session 3
- Advanced MapReduce Concepts (Self-Paced)
- Additional Resources
- Question Bank
- Introduction to RDBMS
- Storing, Handling & Managing Data in Relational Database
- SQL Like Query Processing Engine for Big Data- Hive
- Advanced Hive Concepts
- Relational Data Processing with Spark: SparkSQL and DataFrames
- Handling Heterogeneous Data with NoSQL
- Exploring Column Based NoSQL Database- HBase
- Working with NoSQL Database Cluster- Apache Cassandra
- Deep Diving into Apache Cassandra
- Additional Resource I
- Additional Resource II
- End Course Test
- Question Bank
- Introduction to Data Warehousing
- Large Scale Data Ingestion Using Sqoop
- Performing ETL Using Hive
- Building Robust ETL Pipeline with Spark
- Workflow and Job Scheduling – I
- Workflow and Job Scheduling – II
- Question Bank
- Working with Streaming Data
- Streaming Data Processing With Spark
- Low Latency and Real-Time Data Processing with Kafka – I
- Low Latency and Real-Time Data Processing with Kafka – II
- Building Streaming Data Pipeline Using Kafka, Spark & NoSQL
- Building Scalable Data Pipeline using Kafka Connect & Streams API (Self-Paced)
- Question Bank
- Introduction to Big Data Analytics
- Feature Engineering and Collaborative Filtering using SparkML
- Advanced Analytics using SparkML - Supervised Learning - I
- Advanced Analytics using SparkML - Supervised Learning - II
- Advanced Analytics using SparkML - Unsupervised Learning
- Data Visualization using Tableau (Self-Paced)
- Question Bank
- Introduction to Data Governance
- Fundamentals of Data Security
- Securing Data in Big Data Platforms
- Data Governance and Security in Cloudera Distribution
- Question Bank
- Interview Preparation Question Bank
Instructors
NIT Rourkela Frequently Asked Questions (FAQ's)
The course structure has been designed with dedicated doubt-clearing sessions. Be rest assured that the faculty will be with you all along.
The recording of the class is provided within 12 hours from when the class finishes. Moreover, there will be round the clock technical support.
The classes are held on the weekends. Apart from these, it is advised that the students put in 9 to 10 hours per week.
The applicant needn’t apply for scholarships. Each application is considered for it as part of the process. There are no guarantees that it will be offered.
There are two Mid-program projects as well as an Industrial grade project designed into the courseware. Big Data Engineering applications will be introduced.
Yes, our course has partnerships with select banks. Please approach the admissions team to get further details.
Forecasting trends and demand, Customer retention strategy, and Predictive Analytics and Fraud detection are the three sectors that will be handled along with the program.