Survey Questionaire
Background
The Indo-U.S. Science and Technology Forum (IUSSTF) recently launched the U.S. - India Artificial Intelligence (USIAI) Initiative, a platform for key stakeholders to discuss opportunities and barriers for bilateral AI R&D collaboration, share ideas for developing an AI workforce, and recommend modes and mechanisms for catalyzing partnerships between the two countries. (For more details, please visit https://usiai.iusstf.org/)
As part of its AI-Workforce track, USIAI will organize a series of events (Roundtables, Panels, Workshops) that bring together U. S. and Indian representatives from academic institutions, industry, and government to 1) Identify emerging research areas in AI and related areas; 2) Define knowledge and skills needed for different AI careers; 3) Address Program and Curriculum Development at different levels; and 4) Identify Infrastructure and Resource needs.
This Survey is intended to assess the current state of AI, Data Science, and AI-related curriculum in Indian institutions, understand the underlying challenges, and identify infrastructure and resource needs including faculty recruitment.
Results from the survey will form part of IUSSTF’s recommendations to key stakeholders, including government agencies, academic institutions, industry, and foundations. IUSSTF in collaboration with its Knowledge Partners will prepare white papers that address the technical, research, infrastructure, and workforce opportunities and challenges, highlight best practices for training and program development, and recommend mechanisms/models to facilitate partnerships between Indian and U.S. institutions with the goal of developing a robust AI workforce. The white paper will be shared with both Governments and key stakeholders, including funding agencies.
Your participation in the survey is completely voluntary and all individual responses will be kept confidential: only summaries based on aggregated data will be made public. The responses will be shared only with IUSSTF and itihaasa staff. The list of participating institutions and responses to open-ended questions (unattributed) may be shared in reports.
IUSSTF is partnering with itihaasa Research and Digital (https://itihaasa.com/), ACM India (https://india.acm.org/) and NPTEL (https://nptel.ac.in/) on this initiative.
We hope you will participate in the survey - your feedback is very important to this process.
Thank you very much for your time and effort.
Sincerely,
The IUSSTF-USIAI
itihaasa, ACM India, and
NPTEL Teams
Definitions
In this Survey, ‘Artificial Intelligence’ and ‘Data Science’ are broadly defined as follows:
[1] Artificial Intelligence: A program that focuses on the symbolic inference, representation, and simulation by computers and software of human learning and reasoning processes and capabilities, and the computer modelling of human motor control and motion. Includes instruction in computing theory, cybernetics, human factors, natural language processing, and applicable aspects of engineering, technology, and specific end-use applications.1
Artificial intelligence (AI) systems are software (and possibly also hardware) systems designed by humans that, given a complex goal, act in the physical or digital dimension by perceiving their environment through data acquisition, interpreting the collected structured or unstructured data, reasoning on the knowledge, or processing the information, derived from this data, and deciding the best action(s) to take to achieve the given goal. AI systems can either use symbolic rules or learn a numeric model, and they can also adapt their behaviour by analysing how the environment is affected by their previous actions.2
[2] Data science: A program that focuses on the analysis of large-scale data sources from the interdisciplinary perspectives of applied statistics, computer science, data storage, data representation, data modelling, mathematics, and statistics. Includes instruction in computer algorithms, computer programming, data management, data mining, information policy, information retrieval, mathematical modelling, quantitative analysis, statistics, trend spotting, and visual analytics.1
[3] Data Analytics: A program that prepares individuals to apply data science to generate insights from data and identify and predict trends. Includes instruction in computer databases, computer programming, inference, machine learning, optimization, probability and stochastic models, statistics, strategy, uncertainty quantification, and visual analytics.
These definitions are in no way meant to be prescriptive. Please use the definition that is most appropriate for your program/ degree.
Instructions
Please read the following instructions before completing the survey form:
• In the Survey, the term ‘Academic Unit’ refers to a Department, Center, College, Division, School or similar entity at your institution.
• The survey focuses only on programs in AI, Data Science/ Analytics or related fields.
• We recommend the Academic Unit Head complete the survey or oversee the completion of the survey. Please only provide information related to your specific Academic Unit.
• The survey has been divided into three sections. Section A: Program Offerings, Section B: Curriculum and Instruction, and Section C: Faculty, Infrastructure, Resources, and Collaborations.
• While the Survey includes both compulsory and optional questions, we would very much appreciate if you could provide detailed responses to all the questions to help us better understand the current state of AI education in India and the underlying challenges.
• The survey will take approximately 15-20 minutes to complete.
• If there are other Academic Units within your Institution that offer AI and Data Science Programs/ Degrees, we ask that you share the link with the appropriate individual(s).
Information about the Respondent:
Name of the Institution*
|
<Free Text Field> |
Institution website*
|
<Free Text Field> |
Name of the person responding to the survey*
|
<Free Text Field> |
Academic Unit*
|
<Free Text Field> |
Position/Title*
|
<Free Text Field> |
Email address*
|
<Free Text Field> |
__________________________________________________________________________________________________________________________________________________
Does your Academic Unit offer Programs/Degrees in AI or Data Science? *
|
Option |
Response |
|
1 |
Yes, our Academic Unit offers Programs/Degrees in AI or Data Science |
|
2 |
No, but our Academic Unit plans to offer Programs/Degrees in AI or Data Science in the near future |
|
3 |
No, we do not have any plans to offer Programs/Degrees in AI or Data Science |
PART A: PROGRAM OFFERINGS
A1*. Which of the following types of Bachelor’s Level AI or Data Science Programs/ Degrees are offered by your Academic Unit? Please use the drop-down menus to indicate the Academic Unit that houses the program and the number of students enrolled in the program per year. Select all applicable programs.
If the type of program is not offered, please select the “N/A” option for both columns.
|
Bachelor’s Program |
In which Academic Unit is the Program housed? Select from the dropdown menu |
Number of students enrolled in the Program per year: Select from the dropdown menu |
|
Stand-alone AI program |
• Artificial Intelligence • Computer Science • Electrical / Electronic Engineering • Engineering (others) • Business / Management • Mathematics/ Statistics • Joint / Inter-disciplinary/ Center • Biological Sciences • Atmospheric/ Earth Sciences • Medicine • Social Sciences • Agricultural Sciences • N/A • Others (please specify) |
• 1 - 25 • 26- 50 • 51 – 100 • 100+ • N/A |
|
Stand-alone Data Science or Analytics program |
||
|
Computer Science program with a specialization in AI or Data Science |
||
|
Other program with a specialization in AI or Data Science |
A2*. Which of the following types of Master’s Level AI or Data Science Programs/ Degrees are offered by your Academic Unit? Please use the drop-down menus to indicate the Academic Unit that houses the program and the number of students enrolled in the program per year. Select all applicable programs.
If the type of program is not offered, please select the “N/A” option for both columns.
|
Master’s Program |
In which Academic Unit is the Program housed? Select from the dropdown menu |
Number of students enrolled in the Program per year: Select from the dropdown menu |
|
Stand-alone AI program |
• Artificial Intelligence • Computer Science • Electrical / Electronic Engineering • Engineering (others) • Business / Management • Mathematics/ Statistics • Joint / Inter-disciplinary/ Center • Biological Sciences • Atmospheric/ Earth Sciences • Medicine • Social Sciences • Agricultural Sciences • N/A • Others (please specify) |
• 1 - 25 • 26- 50 • 51 – 100 • 100+ • N/A |
|
Stand-alone Data Science or Analytics program |
||
|
Computer Science program with a specialization in AI or Data Science |
||
|
Other program with a specialization in AI or Data Science |
A3*. Which of the following types of Ph.D. AI or Data Science Programs/ Degrees are offered by your Academic Unit? Please use the drop-down menus to indicate the Academic Unit that houses the program and the number of students enrolled in the program per year. Select all applicable programs.
If the type of program is not offered, please select the “N/A” option for both columns.
|
Ph.D. Program |
In which Academic Unit is the Program housed? Select from the dropdown menu |
Number of students enrolled in the Program per year: Select from the dropdown menu |
|
Stand-alone AI program |
• Artificial Intelligence • Computer Science • Electrical / Electronic Engineering • Engineering (others) • Business / Management • Mathematics/ Statistics • Joint / Inter-disciplinary/ Center • Biological Sciences • Atmospheric/ Earth Sciences • Medicine • Social Sciences • Agricultural Sciences • N/A • Others (please specify) |
• 1 - 25 • 26- 50 • 51 – 100 • 100+ • N/A |
|
Stand-alone Data Science or Analytics program |
||
|
Computer Science program with a specialization in AI or Data Science |
||
|
Other program with a specialization in AI or Data Science |
A4*. Which of the following types of “Other” AI or Data Science Programs/ Degrees are offered by your Academic Unit? Please use the drop-down menus to indicate the Academic Unit that houses the program and the number of students enrolled in the program per year. Select all applicable programs.*
If the type of program is not offered, please select the “N/A” option for both columns.
|
Program |
In which Academic Unit is the Program housed? Select from the dropdown menu |
Number of students enrolled in the Program per year: Select from the dropdown menu |
|
Online program/degree in AI, Data Science/Analytics at the Bachelor’s level |
• Artificial Intelligence • Computer Science • Electrical / Electronic Engineering • Engineering (others) • Business / Management • Mathematics/ Statistics • Joint / Inter-disciplinary/ Center • Biological Sciences • Atmospheric/ Earth Sciences • Medicine • Social Sciences • Agricultural Sciences • N/A • Others (please specify) |
• 1 - 25 • 26- 50 • 51 – 100 • 100+ • N/A |
|
Online program/degree in AI, Data Science/Analytics at the Master’s level |
||
|
Training Programs in AI and Data Science (Examples: certificate programs, summer / winter school, workshops) |
||
|
Online Training Courses/ Workshops in AI and Data Science |
||
|
Other – Please Specify |
PART B: CURRICULUM AND INSTRUCTION
B1. For the Bachelor’s level AI or Data Science Program / Degree offered by your Academic Unit, please select all that apply and indicate whether the course is (a) Required or (b) Elective or (c) Course not offered.
If your Academic Unit does not offer a Bachelor’s level Program / Degree, please move to the next question.
|
Bachelor’s Level Courses |
Required/Elective/ Not offered (Radio button, respondent needs to choose any one) |
|
Programming |
|
|
Mathematics |
|
|
Probability |
|
|
Statistical Methods |
|
|
Data Structures and Algorithms |
|
|
Introduction to AI |
|
|
Knowledge Representation and Reasoning |
|
|
Optimization |
|
|
Machine Learning |
|
|
Natural Language Processing |
|
|
Deep Learning, ANN, Reinforcement Learning, Generative Models |
|
|
Multi-Agent Systems |
|
|
Data visualization, data mining |
|
|
Robotics & Automation |
|
|
Human-Computer Interaction |
|
|
Computer Vision |
|
|
Text Mining |
|
|
Speech Processing |
|
|
Applications (the internet of things, virtual reality, healthcare, social sciences, cybersecurity, etc.) |
|
|
Ethics (privacy, fairness, explainability) |
|
|
AI & Brain sciences (Neuromorphic Computing) |
|
|
Philosophy of AI |
B2. For the Master’s / Ph.D. level AI or Data Science Program / Degree offered by your Academic Unit, please select all that apply and indicate whether the course is (a) Required or (b) Elective or (c) Course not offered.
If your Academic Unit does not offer a Master’s / Ph.D. level Program / Degree, please move to the next question.
|
Master’s / Ph.D. Level Courses |
Required/Elective/ Not offered (Radio button, respondent need to choose any one) |
|
Programming |
|
|
Mathematics |
|
|
Probability |
|
|
Statistical Methods |
|
|
Data Structures and Algorithms |
|
|
Introduction to AI |
|
|
Knowledge Representation and Reasoning |
|
|
Optimization |
|
|
Machine Learning |
|
|
Natural Language Processing |
|
|
Deep Learning, ANN, Reinforcement Learning, Generative Models |
|
|
Multi-Agent Systems |
|
|
Data visualization, data mining |
|
|
Robotics & Automation |
|
|
Human-Computer Interaction |
|
|
Computer Vision |
|
|
Text Mining |
|
|
Speech Processing |
|
|
Applications (the internet of things, virtual reality, healthcare, social sciences, cybersecurity, etc.) |
|
|
Ethics (privacy, fairness, explainability) |
|
|
AI & Brain sciences (Neuromorphic Computing) |
|
|
Philosophy of AI |
B3. Please list any other AI or Data Science-related courses offered by your Academic Unit. (Optional)
|
<Free Text Field> |
B4*. Which of the following modes of training and learning are available to students in the AI or Data Science Programs/ Degrees offered by your Academic Unit? *
|
Required/ Optional/ Not Offered (Radio button for each option, select any one) |
|
|
Research in AI / Data science |
|
|
Interdisciplinary research in AI/ Data Science +X, where X is another research domain) |
|
|
Courses from other application domains |
|
|
Hands-on project with real-life data (Capstone project, course project, mini project) |
|
|
Online Courses including MOOCs |
|
|
Project with industry (internships etc.) |
|
|
Thesis |
|
|
Other (please specify) |
PART C: FACULTY, INFRASTRUCTURE AND RESOURCES, COLLABORATION
C1*. Please indicate the total number of faculty members in your Academic Unit.
|
Total number of faculty in the Academic Unit |
Range 1-10 11-20 21 -30 31 and above |
C2*. Please indicate the percentage of faculty members in your Academic Unit with core experience/ expertise and training in AI or Data Science.
|
Percentage of faculty with core experience/ training in AI / Data Science |
% age Range 1-10% 11-20% 21-30% 31-40% 41-50% 51% and above |
C3*. Do faculty members from other Academic Units participate in your AI or Data Science Program/ Degree? If Yes, please indicate the Academic Units that participate in your program. If ‘No’, please check N/A. *
|
Discipline |
Please check all applicable |
|
Artificial Intelligence |
|
|
Computer Science |
|
|
Electrical / Electronic Engineering |
|
|
Engineering (others) |
|
|
Business / Management |
|
|
Mathematics/ Statistics |
|
|
Joint / Inter-disciplinary/ Center |
|
|
Biological Sciences |
|
|
Atmospheric/ Earth Sciences |
|
|
Medicine |
|
|
Social Sciences |
|
|
Agricultural Science |
|
|
Others (please specify) |
|
|
N/A |
C4*. To what extent do the following factors affect/ pose a challenge to the AI or Data Science programs/ degrees offered by your Academic Unit?
Please rate each of the factors
|
Factors |
|
|
Quantity and quality of students interested in pursuing research |
• Not at All • To some extent • Greatly |
|
Quantity and quality of faculty for teaching and research supervision |
|
|
Availability of/ access to high-end computing infrastructure and software |
|
|
Availability of quality datasets |
|
|
Resources and administrative bottlenecks |
|
|
Collaboration with Industry |
|
|
Collaboration with other Academic Units for interdisciplinary research |
|
|
Collaboration with international educational / research organizations |
|
|
Availability of Internship opportunities |
|
|
Student Placement and employment opportunities |
C5*. How would you rate the demand in the past 1-5 years for AI or Data Science courses offered by your Academic Unit from the following groups? *
Please select ‘Not Applicable’ if it is not applicable for your Academic Unit
|
Please select from the dropdown menu • Significantly increased • Increased • Unchanged • Decreased • Significantly Decreased • Not applicable |
|
|
Bachelor’s Students from your own Academic Unit |
|
|
Bachelor’s Students from other Academic Units |
|
|
Master’s /Ph.D Students from your own Academic Unit |
|
|
Master’s/ Ph.D. Students from other Academic Units |
C6*. Which of the following best describes the career paths/ aspirations of students in your AI and Data Science Program/ Degree? *
Please rank each of the following career choices from 1 to 4, where 1 is ‹Most preferred› and 4 is ‹Least preferred›
|
Challenges |
1 (Most preferred) to 4 (Least preferred) |
|
Industry (Tech) |
|
|
Industry (Other i.e. manufacturing, finance, healthcare etc.) |
|
|
Academic/ Research Positions (Doctoral Programs, Faculty Positions) |
|
|
Start-up/Entrepreneurial Activities |
C7. Please describe any existing partnerships your Academic Unit has with (a) global institutions/ research laboratories; (b) Industry in support of the AI and Data Science Program/ Degree. Please specify the country, institution/ organization, and type of collaboration (student/ faculty exchange, joint research collaborations, internships). (Optional)
|
<Free Text Field> |
C8. Please provide a detailed description of one of the undergraduate or post-graduate programs in AI and Data Science offered by your Academic Unit, including the list of courses, modes of training, and other degree requirements. You may send this information via email to usindia.ai@gmail.com. (Optional)
C9. If you are willing to participate in a follow-up discussion with the IUSSTF-USIAI team to answer questions about your program, please provide a phone number where we may reach you. (Optional)
|
<Free Text Field> |
I give my consent to use the Name of the Institution, Name of the Academic Unit, the Program/Degree offered by the Academic Unit and the URL of the Institution website to be used for future use/publication.
1) Yes 2) No
Thank you for your participation in the survey.
Please visit the USIAI website to learn more about the initiative.
D. FUTURE PLANS
D1. Please share more details of the program that your Academic Unit plans to offer and a tentative start date. You may also paste the URL of your program web page. (Optional)
D2*. To what extent do the following factors limit your ability to offer a program/ degree in the future?
|
Factors |
|
|
Quantity and quality of students interested in pursuing research |
• Not at All • To some extent • Greatly |
|
Quantity and quality of faculty for teaching and research supervision |
|
|
Availability of/ access to high-end computing infrastructure and software |
|
|
Availability of quality datasets |
|
|
Resources and administrative bottlenecks |
|
|
Collaboration with Industry |
|
|
Collaboration with other Academic Units for interdisciplinary research |
|
|
Collaboration with international educational / research organizations |
|
|
Availability of Internship opportunities |
|
|
Student Placement and employment opportunities |
I give my consent to use the Name of the Institution, Name of the Academic Unit, the Program/Degree offered by the Academic Unit and the URL of the Institution website to be used for future use/publication.
1) Yes 2) No
Thank you for your participation in the survey.
Please visit the USIAI website to learn more about the initiative.