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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM43176

Talent Acceleration System

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM43176

Volume:

9 |

3 |

Mar 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM43176

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

PDK

Prof. Deepak Khadse1

PP

Prashant Parshuramkar2

UI

Umeroddin Inamdar3

SN

Sudhanshu Narayane4

SK

Sayali Khedikar5

TV

Tanushree Vaitage6

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Abstract

The rapid digital transformation of education has increased the demand for self-paced and career-focused learning platforms. The Talent Acceleration System (TAS) is a next-generation Learning Management System (LMS) designed to enhance students’ and job seekers’ skills through courses in communication, coding, and programming languages like C, C++, Java, and Python. Unlike traditional LMS platforms, TAS offers a learner-centric experience with real-time progress tracking, interactive quizzes, and certification upon course completion. With Razor pay integration, the platform ensures seamless course enrolments, making quality education more accessible. Its secure authentication protects user data while fostering an independent learning environment, allowing users to track progress without external dependencies. By eliminating instructor profiles, TAS empowers learners to advance at their own pace.This research paper examines the technological framework, system architecture, implementation methodologies, and impact of TAS in bridging the skill gap. The findings highlight its potential as a scalable, efficient, and cost-effective solution for modern education.

KEYWORDS

Talent Acceleration Learning Management System (LMS) Skill Development Digital Education Adaptive Learning Adaptive Learning.

Cite This Article

Prof. Deepak Khadse1, Prashant Parshuramkar2, Umeroddin Inamdar3, Sudhanshu Narayane4, Sayali Khedikar5, Tanushree Vaitage6, "Talent Acceleration System," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 3, Mar 2025. https://doi.org/10.55041/IJSREM43176

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Publication Date

3/28/2025

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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5

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Conflict of Interest

The authors declare no conflict of interest related to this research work.

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No funding information available for this research.

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