ARTiBA accreditation strengthens the academic delivery mechanisms for programs and courses in Ai and machine learning offered by universities and technology schools. Modernization and standards-alignments of the curricula and significant enhancement of employability and career outcomes for students are the most critical upshots of accreditation for academic educators. The ARTiBA accreditation system is fast, intuitively automated and thoroughly digital from start to finish, ensuring project completion in 8-10 weeks with zero disruption in academic activities.
The ARTIBA accreditation process seeks to comprehensively assess the extent to which the curricula, policies and practices, delivery quality, delivery infrastructure and assessment mechanism are aligned to the real-world technology requirements and how they impact the learning and career outcomes of students.
The digital accreditation process ensures that all informational and documentary disclosures are done electronically on the dedicated accreditation dashboards created individually for institutions. The ARTIBA accreditation process is completely non-disruptive and objective and managed remotely by experts.
ARTIBA's accreditation approach focuses on evaluating student learning outcomes; instruction and teaching approaches; organicity and industry-alignment of curricula, and degree of formalization of kaizan consciousness – continuous improvement.
Institutions with programs accredited by ARTIBA exhibit an unwavering commitment for continuous improvement ensuring, that their Ai and machine learning program(s) will give students the knowledge and skills the employers and the industry want.
In early 2020, ARTiBA joined hands with two other global standards bodies in Ai and machine learning and blockchain under the World Data Science Initiative (WDSI) for accrediting higher-education programs in Ai and machine learning on the fast track and on subsidy. WDSI lists deserving institutions that exhibit a clear intent, promise and potential for adopting and embracing latest technology teaching-learning standards, and which can be turned into actual capabilities through accreditation. As one of the sponsors of WDSI, ARTIBA is committed to assessing and accrediting more than two hundred institutions recommended for WDSI subsidy in the next two years.
ARTIBA accreditation helps technology schools and computer science departments and faculties of universities enhance student learning and employability outcomes by upgrading their academic delivery systems and curricula to ARTiBA’s rigorous AMDEX™ standards in Ai and machine learning. Accreditation equips institutions with a streamlined mechanism to augment their undergraduate and graduate programs with the globally renowned AiE™ -ARTIBA’s most advanced Ai and machine learning certification.
ARTiBA accredited institutions can also introduce new undergrad and master’s programs in Ai and machine learning if they do not have them yet. ARTIBA accreditation ensures that students are learning through curricula, content, material and process that are provenly optimized for maximum internalization of theoretical and conceptual knowledge, and development of advanced skills that turns students into perceptive Ai and machine learning professionals upon graduation.
The ARTIBA accreditation program is open for universities, higher-education institutions, and government ICT academies. Institutions already accredited by other international accreditation bodies are placed on the accelerated accreditation track. Institutions shortlisted under the World Data Science Initiative are accredited on a subsidized fee. In early 2020, ARTIBA and Data Science Council of America (DASCA) joined hands to introduce the Twinned Accreditation Program for Ai and machine learning & data science. Under this, DASCA shares all audit information of institutions getting DASCA-accredited with ARTiBA, and will be considered for ARTiBA accreditation at a fast pace.
All accreditation applications are approved only when institutions meet and qualify ARTIBA's norms on academic intent, quality, excellence and reputation. Accreditation applications are approved by ARTIBA using independent industry and market intelligence processes. Once approved, institutions are sent a link to the ARTIBAnet portal to commence their participation in the accreditation process. Institutions can choose either of the tabs below to initiate their accreditation request.
The Edvantic worldwide credentialing support network and its global partners have been officially assigned the responsibility of reaching out to universities around the world – especially the young and promising ones in developing nations in Asia, Africa and Latin America. The Edvantic network is helping these institutions leverage ongoing global assistance and subsidy programs such as the World Data Science Initiative (WDSI) and other programs under the World Bank.
The ARTIBA accreditation program is now open for governments, universities, and vocational training institutions in several countries. Institutions can apply for ARTIBA accreditation along either the Standard or the Accelerated accreditation track. Please note that the cost of the accreditation project does not depend on the track chosen. The difference is that the Standard accreditation track involves six stages of assessment, whereas the Accelerated accreditation track is faster and involves only two stages.
STANDARD ACCREDITATION TRACK ACCELERATED ACCREDITATION TRACKAi and machine learning programs of universities and technology schools are evaluated by ARTiBA along seven core standards to determine their accreditability. These standards are connected to Vision & Strategic Planning; Academic & Institutional Leadership quality; Student and Stakeholder Focus; Student Learning & Assessment systems; Faculty Quality Focus; Curriculum management and Education unit/ department performance history.
ARTIBA accreditation standards are uniquely modeled blending ARTIBA knowledge standards and the principles and criteria of Malcolm Balridge education quality assessment for performance excellence assurance. These standards are on the leading edge of validated management practices that have been proven to work in high performing higher education institutions.
To obtain a ARTIBA accreditation for its Ai and machine learning programs, an institution must:
Have offered (a) degree(s) in Ai and machine learning or related technology areas for at least two years and have alumni from the programs. Institutions shortlisted under WDSI, however are exempt from this condition, and their accreditation application will be accepted even if they do not have a history of offering Ai and machine learning education.
Have a publicly-stated purpose appropriate to a college or university that has been approved by the institution’s governing body (i.e. Regents, Trustees, etc.)
If the institution’s response to the team’s report is substantially in agreement with the team’s report. If not, the experts will obtain clarification of conflicting information.
Ensure that the program being filed for a ARTIBA accreditation has a clear roadmap of eventually embedding ARTIBA certification curricula within one year of the award of accreditation.
To know more about how your institution can get its programs accredited by ARTiBA, please write to accreditation@artiba.org.
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