AI INTERNSHIP FOR YOUNG ACHIEVERS (AIYA ON CAMPUS)

Start Date: December 2023 @ NUS School of Computing, Singapore

Accepting Grade 8-12 Students

Book Consultation

What is AIYA?

There are innumerable ways in which AI is changing our lives – from improving the way medical science treats diseases to creating stronger and smarter buildings to driverless cars.

There are innumerable ways in which AI is changing our lives – from improving the way medical science treats diseases to creating stronger and smarter buildings to self-driving cars.

 

The AI Internship for Young Achievers (AIYA) is a hands-on learning experience designed for high school students from Grade 8 to 12. It is an open academic internship with participants from multiple countries across Asia.

The AI Internship for Young Achievers (AIYA) - LIVE Online is a hands-on learning experience designed for high school students from Grade 8 to 12. It is an open academic internship with participants from multiple countries across Asia.

 

It will enable you to discover how you can use the power of AI in any discipline and field of study and how machine learning and artificial intelligence can make peoples’ lives better. Through our Lab experience you will put your new skills to practical hands-on learning.

It will enable you to discover how you can use the power of AI in any discipline and field of study, also how machine learning and artificial intelligence can make peoples’ lives better. Through our hands-on sessions, you will put your new skills to practical hands-on learning.

 

At a Glance
Duration : 2 weeks
Grades : Grades 8 - 12
Academic Fee : SGD 3499
Programme Outcome : Transcript from NUS
Application Deadline : 30th November, 2020
Duration : On Campus – 15 Days
Learner Profile : Grades 8 - 12
Internship Fee : USD 2499
Start Date : December 2023
Duration : 12 weeks
Learner Profile : Grades 8 - 12
Internship Fee :

SGD 2379*
Application Deadline : June 21, 2021
Mode of Delivery : LIVE Online

Download Factsheet

Download Brochure

Learning Intervention

INDICATIVE SESSION PLAN FOR AIYA EXPERIENTIAL ON CAMPUS – JUNE/JULY’2023

Conceptual Learning with NUS, On Campus at NUS, Singapore
Sessions Concepts Hands-On Assessment
Session - 1 Introduction to Artificial Intelligence
  • What is Artificial Intelligence?
  • History and State-of-Art Applications
  • Machine Learning Tools & Applications
  • Principles of problem solving and the search for solution
  • Introduction to google collab
  • Running the code and loading assets
  • Learn Python basics
  • Basics of python and syntax
  • Control statements in python
  • Quiz after each session
  • End Term Quiz
Session - 2 Understanding data and lifecycle
  • Types of data, data formats
  • How to process data and find information
  • Introduction to basic stats and its uses
  • ML lifecycle, models and training
  • Train, test and validation splits. K-folds
  • Loading datasets on google collab and mounting data
  • Introduction to pandas and data frames
  • Data Frame operations and splicing
  • Numpy basics and understanding
Session 3 Machine Learning Fundamentals
  • Supervised, Unsupervised and Reinforcement Learning
  • Prediction and Classification
  • Components of the performance evaluation
  • Linear Regression example
  • Building their own model from scratch
  • Understanding regression and propagation
  • Calculation of error and loss function in python
  • Plotting results using matplotlib
Session 4 Unsupervised Learning and other concepts
  • Clustering
  • Association - theory, not maths
  • Clustering example
  • Decision Tree’s Learning Algorithms {only Hunt's}
  • Optimal Attribute and Error types
  • Overfitting and Error Performance
  • Ensemble model construction(optional)
  • Clustering in python
  • Decision tree code overview
  • Project Guidance & Feedback
Session 5 Neural Networks and Deep Learning
  • Learning Inspired by the Brain
  • Notation
  • Network structures
  • Perceptrons
  • Multilayer Feed-Forward Networks
  • Back-propagation intro
  • Understanding MLPs in code
  • Neural network model in python
  • Calculating model statistics and performance.
  • Project Guidance and feedback.

PRACTICAL LEARNING SESSION - Hands - On Application with CG

Sessions Concepts Hands-On Project Assessment
Session - 1
  • Introduction to google collab
  • Running the code and loading assets
  • Learn Python basics
  • Basics of python and syntax
  • Control statements in python
  • All Hands-On
  • Project Progress Update and Review in every session
  • None
Session - 2
  • Loading datasets on google collab and mounting data
  • Introduction to pandas and data frames
  • DataFrame operations and splicing
  • Numpy basics and understanding
  • All Hands-On
Session 3 Building their own model from scratch
  • Understanding regression and propagation
  • Calculation of error and loss function in python
  • Plotting results using matplotlib
  • All Hands-On
Session 4
  • Ensemble model construction(optional)
  • Clustering in python
  • Decision tree code overview
  • All Hands-On
Session 5
  • Understanding MLPs in code
  • Neural network model in python
  • Calculating model statistics and performance.
  • All Hands-On

INDICATIVE SESSION PLAN - Hands - On Application with Amazon (AWS)

Sessions: 3 hours x 5 session = 15 hours. On Campus: Weekdays only
Sessions Concepts Hands-On Project Assessment
1 Introduction to Artificial Intelligence
  • Understanding patterns, training and learning
  • Introduction to intelligence and Artificial Intelligence (AI)
  • Applications of AI
  • AI testing (Turing test, Chinese room argument testing, etc)
  • AI ethics
  • Project Briefing & Group Formation
  • Introduction and briefing on Amazon tools (SageMaker & Lex)
  • Student account sign-up
  • Project Progress Update and Review in every session
  • Quiz after every session
2 Introduction to Natural Language Processing (NLP)
  • Importance of data and introduction to BigData
  • Introduction to probability and Bayesian Classifier
  • Understanding the natural language, grammars (POS tagging), etc.
  • Applications of Natural Language Processing
  • Chatbot concepts like intent, utterance, actions, slot, etc.
  • Demo of Chatbot via Amazon Lex and deploying on Slack
  • Setting up SageMaker and Jupyter Notebook instance
3 Introduction to Deep Learning and Artificial Neural Networks (ANN)
  • Introduction to Perceptron
  • Build first image classifier
  • Introduction to Multilevel Perceptron (MLP) classifier
  • Architecture of Neural Network
  • Introduction to Convolution Neural Network (CNN)
  • Object detection via Amazon studio maker
  • Chatbot project review from the previous session
4 Image Classification
  • Basic concepts on image classification
  • Preparing and pre-processing with MNIST (Modified National Institute of Standards and Technology database) data set
  • Handwritten Digit Classification using MNIST dataset
  • Image Classification
5 Deployment and Testing
  • Importance of model deployment and testing
  • Techniques for deploying models using SageMaker
  • Testing models for accuracy and performance
  • Deploying and testing models using SageMaker

Week 1

DAY 9:00 AM – 12:00 PM          2:00 PM – 5:00 PM  6:00 PM – 8:00 PM
Day 1 (Sunday) Arrival in Singapore
and Check-in (after 2:00 PM)		 City Tour (4:00 PM – 6:00 PM)
   (Esplanade, Merlion, Marina Bay   
    Sands, China Town, Little India)		 Dinner at Little India Free and Easy
 
Day 2  NUS Coursework and Sessions Session with Technical Assistants
 		 Self-Directed Teamwork
Day 3  NUS Coursework and Sessions Session with Technical Assistants Self-Directed Teamwork
Day 4  NUS Coursework and Sessions

Session with Technical Assistants

 Self-Directed Teamwork
Day 5  NUS Coursework and Sessions

Session with Technical Assistants

 Self-Directed Teamwork
Day 6 

NUS Coursework and Sessions

Session with Technical Assistants

 Self-Directed Teamwork
 
Day 7
​​​​​​​(Saturday)

--------------------------

Visit to Universal Studio 
Entry Fee not included
 

  -----------------------------
Day 8
(Sunday)		 --------------------------- Visit to Sentosa and shopping at Mustafa Centre
 		 ------------------------------

Week 2

Date 9:00 AM – 12:00 PM          2:00 PM – 5:00 PM  6:00 PM –8:00 PM
Day 9 AMAZON Coursework and Hands-on Sessions Sessions with Technical Assistants Self-Directed Teamwork
Day 10 AMAZON Coursework and Hands-on Sessions Sessions with Technical Assistants Free and Easy Singapore Tour
Day 11 AMAZON Coursework and Hands-on Sessions Sessions with Technical Assistants Self-Directed Teamwork
Day 12  AMAZON Coursework and Hands-on Sessions Sessions with Technical Assistants Student Project & Mock Presentations 
Day 13 AMAZON Coursework and Hands-on Sessions Sessions with Technical Assistants Work on Presentation Feedback
Day 14
(Saturday)		 Assessment by NUS and AMAZON Faculty
Final Student Project Presentation & AI Guru Contest

Valedictory Ceremony

 Night Safari
Day 15
(Sunday)		 -------------------------------------------

Check-out before 2 pm SGT

 ------------------------------------

Assessment Criteria

Assessment Component Weightage
Weekly Group Assignments/Quiz 20%
End Term Quiz 40%
Project Presentation 40%

1. Certificate of Completion by National University of Singapore (NUS)

2. Certificate of Completion by Amazon (AWS)

3. Individual Letter of Recommendations for top project group from NUS

 

 

testimonial
testimonial

DISCLAIMER: ABOVE DOCUMENT IS INDICATIVE AND SUBJECT TO MINOR CHANGES BASED ON PARTNER DISCRETION.

 

Pedagogy
Learning Goals

INDICATIVE SESSION PLAN FOR AIYA EXPERIENTIAL ON CAMPUS – JUNE/JULY’2023

Conceptual Learning with NUS, On Campus at NUS, Singapore
Sessions Concepts Hands-On Assessment
Session - 1 Introduction to Artificial Intelligence
  • What is Artificial Intelligence?
  • History and State-of-Art Applications
  • Machine Learning Tools & Applications
  • Principles of problem solving and the search for solution
  • Introduction to google collab
  • Running the code and loading assets
  • Learn Python basics
  • Basics of python and syntax
  • Control statements in python
  • Quiz after each session
  • End Term Quiz
Session - 2 Understanding data and lifecycle
  • Types of data, data formats
  • How to process data and find information
  • Introduction to basic stats and its uses
  • ML lifecycle, models and training
  • Train, test and validation splits. K-folds
  • Loading datasets on google collab and mounting data
  • Introduction to pandas and data frames
  • Data Frame operations and splicing
  • Numpy basics and understanding
Session 3 Machine Learning Fundamentals
  • Supervised, Unsupervised and Reinforcement Learning
  • Prediction and Classification
  • Components of the performance evaluation
  • Linear Regression example
  • Building their own model from scratch
  • Understanding regression and propagation
  • Calculation of error and loss function in python
  • Plotting results using matplotlib
Session 4 Unsupervised Learning and other concepts
  • Clustering
  • Association - theory, not maths
  • Clustering example
  • Decision Tree’s Learning Algorithms {only Hunt's}
  • Optimal Attribute and Error types
  • Overfitting and Error Performance
  • Ensemble model construction(optional)
  • Clustering in python
  • Decision tree code overview
  • Project Guidance & Feedback
Session 5 Neural Networks and Deep Learning
  • Learning Inspired by the Brain
  • Notation
  • Network structures
  • Perceptrons
  • Multilayer Feed-Forward Networks
  • Back-propagation intro
  • Understanding MLPs in code
  • Neural network model in python
  • Calculating model statistics and performance.
  • Project Guidance and feedback.

PRACTICAL LEARNING SESSION - Hands - On Application with CG

Sessions Concepts Hands-On Project Assessment
Session - 1
  • Introduction to google collab
  • Running the code and loading assets
  • Learn Python basics
  • Basics of python and syntax
  • Control statements in python
  • All Hands-On
  • Project Progress Update and Review in every session
  • None
Session - 2
  • Loading datasets on google collab and mounting data
  • Introduction to pandas and data frames
  • DataFrame operations and splicing
  • Numpy basics and understanding
  • All Hands-On
Session 3 Building their own model from scratch
  • Understanding regression and propagation
  • Calculation of error and loss function in python
  • Plotting results using matplotlib
  • All Hands-On
Session 4
  • Ensemble model construction(optional)
  • Clustering in python
  • Decision tree code overview
  • All Hands-On
Session 5
  • Understanding MLPs in code
  • Neural network model in python
  • Calculating model statistics and performance.
  • All Hands-On

INDICATIVE SESSION PLAN - Hands - On Application with Amazon (AWS)

Sessions: 3 hours x 5 session = 15 hours. On Campus: Weekdays only
Sessions Concepts Hands-On Project Assessment
1 Introduction to Artificial Intelligence
  • Understanding patterns, training and learning
  • Introduction to intelligence and Artificial Intelligence (AI)
  • Applications of AI
  • AI testing (Turing test, Chinese room argument testing, etc)
  • AI ethics
  • Project Briefing & Group Formation
  • Introduction and briefing on Amazon tools (SageMaker & Lex)
  • Student account sign-up
  • Project Progress Update and Review in every session
  • Quiz after every session
2 Introduction to Natural Language Processing (NLP)
  • Importance of data and introduction to BigData
  • Introduction to probability and Bayesian Classifier
  • Understanding the natural language, grammars (POS tagging), etc.
  • Applications of Natural Language Processing
  • Chatbot concepts like intent, utterance, actions, slot, etc.
  • Demo of Chatbot via Amazon Lex and deploying on Slack
  • Setting up SageMaker and Jupyter Notebook instance
3 Introduction to Deep Learning and Artificial Neural Networks (ANN)
  • Introduction to Perceptron
  • Build first image classifier
  • Introduction to Multilevel Perceptron (MLP) classifier
  • Architecture of Neural Network
  • Introduction to Convolution Neural Network (CNN)
  • Object detection via Amazon studio maker
  • Chatbot project review from the previous session
4 Image Classification
  • Basic concepts on image classification
  • Preparing and pre-processing with MNIST (Modified National Institute of Standards and Technology database) data set
  • Handwritten Digit Classification using MNIST dataset
  • Image Classification
5 Deployment and Testing
  • Importance of model deployment and testing
  • Techniques for deploying models using SageMaker
  • Testing models for accuracy and performance
  • Deploying and testing models using SageMaker
Schedule

Week 1

DAY 9:00 AM – 12:00 PM          2:00 PM – 5:00 PM  6:00 PM – 8:00 PM
Day 1 (Sunday) Arrival in Singapore
and Check-in (after 2:00 PM)		 City Tour (4:00 PM – 6:00 PM)
   (Esplanade, Merlion, Marina Bay   
    Sands, China Town, Little India)		 Dinner at Little India Free and Easy
 
Day 2  NUS Coursework and Sessions Session with Technical Assistants
 		 Self-Directed Teamwork
Day 3  NUS Coursework and Sessions Session with Technical Assistants Self-Directed Teamwork
Day 4  NUS Coursework and Sessions

Session with Technical Assistants

 Self-Directed Teamwork
Day 5  NUS Coursework and Sessions

Session with Technical Assistants

 Self-Directed Teamwork
Day 6 

NUS Coursework and Sessions

Session with Technical Assistants

 Self-Directed Teamwork
 
Day 7
​​​​​​​(Saturday)

--------------------------

Visit to Universal Studio 
Entry Fee not included
 

  -----------------------------
Day 8
(Sunday)		 --------------------------- Visit to Sentosa and shopping at Mustafa Centre
 		 ------------------------------

Week 2

Date 9:00 AM – 12:00 PM          2:00 PM – 5:00 PM  6:00 PM –8:00 PM
Day 9 AMAZON Coursework and Hands-on Sessions Sessions with Technical Assistants Self-Directed Teamwork
Day 10 AMAZON Coursework and Hands-on Sessions Sessions with Technical Assistants Free and Easy Singapore Tour
Day 11 AMAZON Coursework and Hands-on Sessions Sessions with Technical Assistants Self-Directed Teamwork
Day 12  AMAZON Coursework and Hands-on Sessions Sessions with Technical Assistants Student Project & Mock Presentations 
Day 13 AMAZON Coursework and Hands-on Sessions Sessions with Technical Assistants Work on Presentation Feedback
Day 14
(Saturday)		 Assessment by NUS and AMAZON Faculty
Final Student Project Presentation & AI Guru Contest

Valedictory Ceremony

 Night Safari
Day 15
(Sunday)		 -------------------------------------------

Check-out before 2 pm SGT

 ------------------------------------
Assessment

Assessment Criteria

Assessment Component Weightage
Weekly Group Assignments/Quiz 20%
End Term Quiz 40%
Project Presentation 40%
Programme Completion Documents

1. Certificate of Completion by National University of Singapore (NUS)

2. Certificate of Completion by Amazon (AWS)

3. Individual Letter of Recommendations for top project group from NUS

 

 

testimonial
testimonial

DISCLAIMER: ABOVE DOCUMENT IS INDICATIVE AND SUBJECT TO MINOR CHANGES BASED ON PARTNER DISCRETION.

 

Admissions

Certificates

AIYA HIGH ACHIEVERS CERTIFICATE

AIYA High Achiever Certificate recognizes participants who demonstrate academic excellence, good teamwork, sound character, strong leadership, and a passion for creativity and innovation.

Associates

National University of Singapore

The NUS School of Computing traces its roots back to the Nanyang University Department of Computer Science that was established in 1975 – the first of its kind in Singapore. Since then, it has developed into one of the leading computing schools in the world, with faculty members who are both internationally recognised researchers and inspiring teachers. The school offers undergraduate and graduate degree programmes across the full spectrum of the field of computing, including Computer Science, Information Systems, Computer Engineering, Business Analytics and Information Security, as well as specialisations in emerging areas of importance such as artificial intelligence, fintech, blockchain, analytics and security.

Amazon

 

Amazon - World leader in e-commerce, cloud computing, digital streaming and AI.
 

Amazon Web Services, Inc. (AWS) is a subsidiary of Amazon that provides on-demand cloud computing platforms and APIs to individuals, companies, and governments, on a metered pay-as-you-go basis. These cloud computing web services provide distributed computing processing capacity and software tools via AWS server farms

Amazon SageMaker is built on Amazon’s two decades of experience developing real-world ML applications, including product recommendations, personalization, intelligent shopping, robotics, and 
voice-assisted devices.
 

Amazon SageMaker is a fully managed machine learning service. With SageMaker, data scientists and developers can quickly and easily build and train machine learning models, and then directly deploy them into a production-ready hosted environment.

National University of Singapore

The NUS School of Computing traces its roots back to the Nanyang University Department of Computer Science that was established in 1975 – the first of its kind in Singapore. Since then, it has developed into one of the leading computing schools in the world, with faculty members who are both internationally recognised researchers and inspiring teachers. The school offers undergraduate and graduate degree programmes across the full spectrum of the field of computing, including Computer Science, Information Systems, Computer Engineering, Business Analytics and Information Security, as well as specialisations in emerging areas of importance such as artificial intelligence, fintech, blockchain, analytics and security.

Amazon

 

Amazon - World leader in e-commerce, cloud computing, digital streaming and AI.
 

Amazon Web Services, Inc. (AWS) is a subsidiary of Amazon that provides on-demand cloud computing platforms and APIs to individuals, companies, and governments, on a metered pay-as-you-go basis. These cloud computing web services provide distributed computing processing capacity and software tools via AWS server farms

Amazon SageMaker is built on Amazon’s two decades of experience developing real-world ML applications, including product recommendations, personalization, intelligent shopping, robotics, and 
voice-assisted devices.
 

Amazon SageMaker is a fully managed machine learning service. With SageMaker, data scientists and developers can quickly and easily build and train machine learning models, and then directly deploy them into a production-ready hosted environment.

Featured Review

Success Stories

Our Alumni Network

Frequently Asked Questions

What is the AIYA?

The A.I. Internship is an On Campus – 15 Days full of learning, It is conducted by National University of Singapore (NUS) & Amazon (AWS).

It is conducted by:

  • National University of Singapore (NUS) School of Computing Singapore
  • Amazon (AWS)

It is 15 days On Campus - internship programme, conducted at National University of Singapore, (NUS) School of Computing, Singapore.

It is an academic internship, which is a hands-on guided experience in an academic environment to hone industry-relevant skills and knowledge in a chosen domain with mentorship and training by university professor(s) and industry professional(s).

  • They will understand, experience and apply fundamental AI concepts.
  • They will appreciate the workings behind real life AI research and applications.
  • They will conceptualise, design and implement a social/ technological innovation project with expert inputs from faculty from NUS and professionals from Amazon.
  • They will get insights on higher education and the international university admission process and applications in industry.
  • They will develop a strong profile for international university admissions.

Our project managers will be able to guide you to the admissions department. You will need to explore opportunities on your own with the admissions department based on your area of passion and interest for higher studies.

How do I apply?

You may download the Factsheet below or fill in the interest form. One of our counsellors will be in touch with you to take it forward and assist you with the enrollment. You may also enroll through our website and make the payment via a Debit/Credit card or Online Banking.

This program is open to all students from middle school and high school . This is an open programme that focuses on providing a better understanding of Artificial Intelligence, how it is changing our world, its benefits and usage in our everyday lives.

No, our course is specially designed to ensure that students from all streams and areas of study can easily understand the concepts taught at this internship.

Yes, students studying the ICSE, CBSE, IB MYP, IB DP, IGCSE curriculum can apply for the programme. Students can be of any nationality, ethnicity and belong to any country!

This is a fully-residential program. All students and visiting faculty will stay at the Hostel/ Hotel Accommodation in Singapore. NUS also has a large food court which serves food from 16 countries. Vegetarian and non-vegetarian both options are available.

Please refer the programme fee on the website. In addition to that, you should factor in the cost of flights, insurance and visa applications . Also, food expenses are an additional cost of approximately S$ 20 per day.

The academic internship schedule, date and time are subject to change based on the availability of professor(s) from NUS and professionals from Amazon (AWS). Prior notice will be given to all concerned parties on the change of date and the best efforts will be made by Corporate Gurukul to accommodate all parties when deciding the revised schedule, date and time.

Is it a selection-based programme?

Yes

The selection criteria are as follows:

  1. Overall academic performance (grades) in current year or previous year
  2. Resume and Essays in Application Form

What is the last date to pay for the registration fees?

Please refer the Offer Letter issued to you.

  • Certificate of Completion from National University of Singapore, School of Computing (NUS)
  • Certificate of Completion from Amazon (AWS)
  • Individual Letter of Recommendations for top project group by NUS
  • Flights/Visa/Travel Insurance
  • Local Transport in India
  • International SIM Card
  • Local Transport in Singapore for personal visits/sightseeing
  • Entrance Fee to various tourist attractions in Singapore
  • Medical expenses in Singapore
  • Gym, laundry or any other hostel facility charges
  • Stay in Singapore before or after academic internship dates

Which certificate(s) will I get after completion of this academic internship?
  • Certificate of Completion by National University of Singapore (NUS)
  • Certificate of Completion from Amazon (AWS)
  • Individual Letter of Recommendations for top project group from NUS

Issuance of all certificates and the LoR will be at Corporate Gurukul’s discretion subject to:

  1. the participant’s performance
  2. completion of assignments and
  3. 90% attendance during the academic internship

The certificates will be awarded during the Valedictory Ceremony at the end of the programme.

The LOR(s) will be posted to your respective institutes 60 days post the programme completion.

The hands-on sessions are conducted in the Lecture Theatre/Seminar Rooms. You will not visit any laboratories for the same unless requested by the professor(s).

Laptop with the specifications mentioned in ACADEMIC INTERNSHIP PREREQUISITES is MANDATORY for all participants.

No. The entire academic internship is delivered at NUS, Singapore.

Yes, you will be assigned teams for project work and assignments. These teams typically consist of 4-5 members.

No, the team members are assigned by Corporate Gurukul team in consultation with the professor(s). They are created keeping in mind that the prerequisite readiness and a proper mix of students from various institutions. Any request for choice of team member will not be entertained.

All assignments and projects will be submitted on the Learning Management System, Acadly.

Assignments will be given daily and need to be submitted as per specified deadline. You may be required to work on the assignments in teams or individually as per the nature of assignment.

You are required to complete one project during the duration of the programme. This will be done in teams.

The project presentations will be conducted post the NUS and Amazon sessions.

Yes, both NUS and Amazon (AWS) sessions are graded.

The MCQ Quiz will be conducted every day during the afternoon session.

Any late submissions of project, assignments or quizzes beyond specified deadline will carry negative marks.

About AIYA

What is the AIYA?

The A.I. Internship is an On Campus – 15 Days full of learning, It is conducted by National University of Singapore (NUS) & Amazon (AWS).

It is conducted by:

  • National University of Singapore (NUS) School of Computing Singapore
  • Amazon (AWS)

It is 15 days On Campus - internship programme, conducted at National University of Singapore, (NUS) School of Computing, Singapore.

It is an academic internship, which is a hands-on guided experience in an academic environment to hone industry-relevant skills and knowledge in a chosen domain with mentorship and training by university professor(s) and industry professional(s).

  • They will understand, experience and apply fundamental AI concepts.
  • They will appreciate the workings behind real life AI research and applications.
  • They will conceptualise, design and implement a social/ technological innovation project with expert inputs from faculty from NUS and professionals from Amazon.
  • They will get insights on higher education and the international university admission process and applications in industry.
  • They will develop a strong profile for international university admissions.

Our project managers will be able to guide you to the admissions department. You will need to explore opportunities on your own with the admissions department based on your area of passion and interest for higher studies.

Applying for AIYA

How do I apply?

You may download the Factsheet below or fill in the interest form. One of our counsellors will be in touch with you to take it forward and assist you with the enrollment. You may also enroll through our website and make the payment via a Debit/Credit card or Online Banking.

This program is open to all students from middle school and high school . This is an open programme that focuses on providing a better understanding of Artificial Intelligence, how it is changing our world, its benefits and usage in our everyday lives.

No, our course is specially designed to ensure that students from all streams and areas of study can easily understand the concepts taught at this internship.

Yes, students studying the ICSE, CBSE, IB MYP, IB DP, IGCSE curriculum can apply for the programme. Students can be of any nationality, ethnicity and belong to any country!

This is a fully-residential program. All students and visiting faculty will stay at the Hostel/ Hotel Accommodation in Singapore. NUS also has a large food court which serves food from 16 countries. Vegetarian and non-vegetarian both options are available.

Please refer the programme fee on the website. In addition to that, you should factor in the cost of flights, insurance and visa applications . Also, food expenses are an additional cost of approximately S$ 20 per day.

The academic internship schedule, date and time are subject to change based on the availability of professor(s) from NUS and professionals from Amazon (AWS). Prior notice will be given to all concerned parties on the change of date and the best efforts will be made by Corporate Gurukul to accommodate all parties when deciding the revised schedule, date and time.

Academics

Is it a selection-based programme?

Yes

The selection criteria are as follows:

  1. Overall academic performance (grades) in current year or previous year
  2. Resume and Essays in Application Form

Payment

What is the last date to pay for the registration fees?

Please refer the Offer Letter issued to you.

  • Certificate of Completion from National University of Singapore, School of Computing (NUS)
  • Certificate of Completion from Amazon (AWS)
  • Individual Letter of Recommendations for top project group by NUS
  • Flights/Visa/Travel Insurance
  • Local Transport in India
  • International SIM Card
  • Local Transport in Singapore for personal visits/sightseeing
  • Entrance Fee to various tourist attractions in Singapore
  • Medical expenses in Singapore
  • Gym, laundry or any other hostel facility charges
  • Stay in Singapore before or after academic internship dates

Programme Completion Documents

Which certificate(s) will I get after completion of this academic internship?
  • Certificate of Completion by National University of Singapore (NUS)
  • Certificate of Completion from Amazon (AWS)
  • Individual Letter of Recommendations for top project group from NUS

Issuance of all certificates and the LoR will be at Corporate Gurukul’s discretion subject to:

  1. the participant’s performance
  2. completion of assignments and
  3. 90% attendance during the academic internship

The certificates will be awarded during the Valedictory Ceremony at the end of the programme.

The LOR(s) will be posted to your respective institutes 60 days post the programme completion.

The hands-on sessions are conducted in the Lecture Theatre/Seminar Rooms. You will not visit any laboratories for the same unless requested by the professor(s).

Laptop with the specifications mentioned in ACADEMIC INTERNSHIP PREREQUISITES is MANDATORY for all participants.

No. The entire academic internship is delivered at NUS, Singapore.

Yes, you will be assigned teams for project work and assignments. These teams typically consist of 4-5 members.

No, the team members are assigned by Corporate Gurukul team in consultation with the professor(s). They are created keeping in mind that the prerequisite readiness and a proper mix of students from various institutions. Any request for choice of team member will not be entertained.

All assignments and projects will be submitted on the Learning Management System, Acadly.

Assignments will be given daily and need to be submitted as per specified deadline. You may be required to work on the assignments in teams or individually as per the nature of assignment.

You are required to complete one project during the duration of the programme. This will be done in teams.

The project presentations will be conducted post the NUS and Amazon sessions.

Yes, both NUS and Amazon (AWS) sessions are graded.

The MCQ Quiz will be conducted every day during the afternoon session.

Any late submissions of project, assignments or quizzes beyond specified deadline will carry negative marks.