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Quick Facts

Medium Of Instructions	Mode Of Learning	Mode Of Delivery
English	Self Study	Video and Text Based

Course Overview

The Big Data Analytics For Smart Grid certification course is an 8-week course that uses the concepts of Python programming language is an open-source software to demonstrate the use of Big Data Analytics in smart grid systems. The data in today’s world is influenced by the fast developments taking place in cloud computing and digital technology involving human activity, communications, sensors and digital equipment.

The Big Data Analytics For Smart Grid training will involve case studies and begins with the introduction and importance of such analysis with data collection through intelligent devices, machine learning, deep learning, and its associated algorithms.

The coursework is intended for both academic based attendees such as students, faculty and industry professionals. This course is supported and framed in collaboration with industries such as IBM and Opal-RT. This Big Data Analytics For Smart Grid programme aims to explore the issues arising in the processing and analysis of large volumes of data which is challenging to be done in a structured way.

The Highlights

8 weeks of curriculum
Course category in Annual Refresher Programme in Teaching (ARPIT).
AICTE approved FDP course
Core type certificate course
Verified certificate by SWAYAM
Collaborated by Opal-RT and IBM
Instructed by Dr. Ritula Thakur, Associate Professor, NITTTR

Programme Offerings

Case Studies
Online discussion forums
Books
quizzes
references
Self assessment tests
video lectures
Printed reading materials.

Courses and Certificate Fees

Certificate Availability
no

Eligibility Criteria

Education

The candidate should have basic knowledge of power systems and statistics for enrolment into the Big Data Analytics For Smart Grid certification.

Certification Qualification Details

The Big Data Analytics For Smart Grid programme is free to enrol in, and after the proctored exam enrolment, passing and payment, the applicant will receive a validated certificate from SWAYAM.

What you will learn

Machine learningData science knowledgeKnowledge of Big DataKnowledge of cloud computing

In Big Data Analytics For Smart Grid by SWAYAM the students are taught the following

The students will learn about the need to use data analysis in smart grid systems.
The students will use the Smart grid intelligent devices for data collection.
The candidates will be exposed to the concepts of data science in smart grid analytics.
The candidates will learn to use the tools in big data analytics.
The candidates will learn to assimilate the concepts of data analytics based on conventional and advanced machine learning algorithms.
The candidates will learn insights from the case studies in big data analytics related to smart grid systems.
The candidates will learn to use cloud and edge computing related to big data analytics.

Who it is for

Data ScientistTeacher

Big Data Analytics For Smart Grid training is intended for

Undergraduate students and postgraduate students can get introduced to and pursue a career in data analytics.
Research scholars and faculties in technical institutes are looking to further their knowledge and application in the areas of smart grid systems.
Industry professionals such as data scientists and engineering seeking to learn about smart grid technologies.

Application Details

The steps below should be taken so as to realize admission in Big Data Analytics For Smart Grid online course.

Step 1: On the given web site of SWAYAM, click this link https://onlinecourses.swayam2.ac.in/arp20_ap10/preview

Step 2: Make an account with all of the mandatory info and log in.

Step 3: Once redirected to the course page, choose the “Enroll” option.

Step 4: Complete the registration method with all of the relevant info.

The course is presently current, and enrollment is closed. The courses are often registered online once open enrollment is declared.

The Syllabus

Instructors

NITTTR Chandigarh Frequently Asked Questions (FAQ's)

1: How long is the programme expected to last?

The Big Data Analytics For Smart Grid certification will take 16 weeks to complete and will be entirely online.

2: What is the procedure for receiving a SWAYAM-verified certificate?

Candidates who wish to obtain the certificate must first register and then take the proctored exam, following which they will be awarded the certificate.

3: How can students enrolled in this programme receive financial assistance?

There is currently no information available, and because it is a free course, candidates interested in receiving scholarships should contact SWAYAM officials.

4: How is the programme geared toward the candidates?

The Big Data Analytics For Smart Grid online course is designed for management and commerce faculty to provide a holistic learning experience while meeting the participants' dynamic needs.

5: How much does the curriculum for this course cost?

There is no amount set as Big Data Analytics For Smart Grid certification fees to be admitted or enrolled.

6: Where do I find the registration link for the programme?

Candidates who wish to participate in this course must first register online at this link. https://onlinecourses.swayam2.ac.in/arp20_ap10/preview

7: What are some of the course curriculum offerings?

Video tutorials, books, references, printable reading materials, self-assessment assessments, online discussion boards, and quizzes are all included in this course.

8: When will the enrolment application be available?

Enrollment is currently closed because this is a continuing course of study; however, enrollment will reopen once the new admissions cycle begins.

9: What is the program's level of difficulty?

Enrollment in the programme is not restricted to a specific level of difficulty.

10: What are the main topics covered in this course?

The topics of discussion in the Big Data Analytics For Smart Grid certification syllabus are data collection, smart grid analytics, tools for big data analytics, machine learning algorithms, cloud and edge computing.