GAIP: BIG DATA ANALYTICS USING DEEP LEARNING

Starts: December 2024

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About the Internship

Our "secret sauce” is that we’re with you at every step of the GAIP Journey

 

The Global Academic Internship Programme (GAIP) with the NUS School of Computing and Amazon Web Services (AWS) brings the rigorous, collaborative, action-learning experience of our in-person internship in the NUS Singapore campus. Over 3 weeks, you will learn and work with a global team of curious learners and tech innovators carefully selected by Corporate Gurukul to build and deliver value through innovation.

 

GAIP is a hands-on, short-term academic internship conducted by Corporate Gurukul at National University of Singapore (NUS), in association with and certified by the NUS School of Computing. GAIP enables engineering undergraduates/graduates from universities and institutes of higher learning in Asia to level up by pursuing their passion and interest through internships and project-based learning in Artificial Intelligence, Data Analytics, Big Data, Machine Learning, & Deep Learning.

 

Internship on ‘Big Data Analytics Using Deep Learning’ as part of GAIP focuses on and is focused on hands-on real-world projects. 90% of our alumni have polled that 80% of the curriculum is new and aligned to MS abroad or research careers in Data Science and AI.

 

GAIP is a key component in CG’s Global Strategy which focuses on shaping the future of education, learning and creating global empathetic leaders.

At a Glance
Duration : 3 Weeks
Learner Profile : University UG and PG students
Academic Fee : SGD 3899
Application Deadline : 15th April, 2021
Duration : 3 Weeks
Learner Profile : University UG and PG students
Academic Internship Fee : USD 3899
Start Date : December 2024

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Download Brochure

Learning Intervention

Sessions with NUS

Session

Duration  

(hours)

Session Agenda

Assessment

1

3

  • IntroductiontoData Analytics

  • WhatisDataAnalytics

    • Types of Data Analytics

    • Data in Data Analytics + Decision Models – Data Mining Process

  • ExploratoryDataAnalysis

    • Data Visualization

    • Data Querying

    • Statistical Methods for Summarizing Data

  • Exploring data using Pivot Tables

2

3

  • DescriptiveStatistical Measures

  • WhatisDescriptiveAnalytics?

    • Populations and Samples

    • Measures of Location

    • Measures of Dispersion

    • Measures of Shape

    • Measures of Association

  • ProjectBriefingandGroupFormation

Quiz 1

3

3

  • Regression

    • Introduction to Regression Analysis

    • Simple Linear Regression

    • Multi Linear Regression

    • Stepwise Regression

    • Coding Scheme for Categorical Variables

    • Problems with Linear Regression

 

4

3

  • Introduction to Classification

    • Decision Trees

    • Bayesian Classifier

    • Logistic Regression

    • Support Vector

  • Machine Separating

  • Hyperplane

  • Maximal Margin Classifier Support

  • Vector Classifier

    • Resampling Methods

5

3

  • Introduction to Clustering

    • Affinity Measures and Partition Methods

    • K-means

    • K-medoids

    • Hierarchical Methods

  • Introduction to Association

    • Structure and Representation of Association Rules

    • Strong Association Rules and the Concept of Frequent

  • Item sets – Apriori Algorithm

    • FP Growth

  • Time Series Analysis

 

6

3

  • Introduction to Text Mining

    • Text Mining Terminologies

    • Text Mining Concepts

    • Text Mining Process

  • Knowledge Extraction Methods for Text Mining

    • Classification

    • Clustering

  • Association

Quiz 3

7

3

Artificial Neural Networks(ANN)

  • Introduction

  • Perceptrons and Activation Functions

  • Building Blocks of Neural Networks (Input, Hidden, Output layers)

  • Hands-On Exercise: Building a Simple Neural Network (XOR Problem)

    • How to develop ANN using Tensorflow

  • Back-Propagation

    • Gradient Descent, Momentum, Learning Rate, Overfitting

 

8

3

  • Convolutional Neural Networks (CNN)

    • Convolution, pooling operations

    • Popular CNN architectures

    • Applications of CNN in Python

Quiz 4

9

3

  • Recurrent Neural Networks (RNN)

    • Vanilla RNN

    • LSTM and GRU

    • Applications of RNN in Python

 

9

3

GenerativeAI

  • Part 1: Introduction to Generative Models:

    • What are generative models?

    • Overview of model types: GANs, VAEs, and transformers.

  • Part 2: GANs (Generative Adversarial Networks)

    • Basic architecture: Generator and Discriminator.

    • Simple applications: Image generation,music generation (hands-on)

    • VAEs (Variational Autoencoders)

    • Encoder-decoder architecture.

    • Use cases: Image denoising.

    • Transformers in Generative AI

    • Overview of transformer architecture.

    • Applications: Text generation with GPT models.

  • Part 3: Applications and Ethical Considerations

    • Highlighting practical applications of each model type.

    • Brief discussion on ethical implications like deepfakes and bias.

ReinforcementLearning (RL)

  • Introduction

  • RL Algorithms

    • Dynamic Programming (DP)

    • Monte Carlo Methods

    • Temporal-Difference Learning (TD)

  • Implementing RL algorithm using Python

Final Quiz

 

 

CG Mock Presentations (CG with TAs)

 

 

 

Final Project Presentation and Assessment - NUS

 

Sessions with NUS

Session

Session  By 

Session Agenda

Duration  

(hours)

1

 NUS

Introduction to Data Analytics

What is Data Analytics

- Types of Data Analytics

- Data in Data Analytics + Decision Models – Data Mining Process

Exploratory Data Analysis

- Data Visualization

- Data Querying

- Statistical Methods for Summarizing Data – Exploring Data using Pivot Tables

 

3

2

  NUS

Descriptive Statistical Measures 

What is Descriptive Analytics? 

- Populations and Samples 

- Measures of Location 

- Measures of Dispersion 

- Measures of Shape 

- Measures of Association 

Project Briefing and Group Formation  

QUIZ 

 

3

3 

 NUS

Regression 

-Introduction to Regression Analysis 

- Simple Linear Regression 

 

- Multi Linear Regression 

- Stepwise Regression 

- Coding Scheme for Categorical Variables

- Problems with Linear Regression

 

3

4

  NUS

Introduction to Classification 

Classification 

- Decision Trees 

- Bayesian Classifier 

- Logistic Regression  

- Support Vector Machine 

Separating Hyperplane 

Maximal Margin Classifier

 

Support Vector Classifier 

Resampling Methods 

 

3

5

  NUS

ntroduction to Clustering 

- Affinity Measures and Partition Methods 

- K-means 

- K-medoids 

- Hierarchical Methods

  

Introduction to Association 

- Structure and Representation of Association Rules 

- Strong Association Rules and the Concept of Frequent Item sets – Apriori Algorithm 

- FP Growth 

- Time Series Analysis

 

3

6

  NUS

Introduction to Text Mining 

- Text Mining Terminologies 

- Text Mining Concepts 

- Text Mining Process 

Knowledge Extraction Methods for Text Mining 

- Classification 

- Clustering 

- Association  

QUIZ 

 

3

7 

  NUS

Artificial Neural Networks (ANN) 

Overview of ANN 

Why ANN? 

Back-propagation 

 

3

8

 NUS

Artificial Neural Networks (ANN) 

- Gradient descent algorithm (GD) 

- Difficulties of training ANN 

- Advanced GD algorithm 

- Other training techniques of ANN 

QUIZ 

 

3

9 

 NUS

Convolutional Neural Networks (CNN) 

- Convolution, pooling operations 

- Popular CNN architectures 

 

3

10

 NUS

- Applications of CNN in Python 

Recurrent Neural Networks (RNN) 

- Vanilla RNN 

- LSTM and GRU 

- Applications of RNN in Python 

NUS Final Quiz 

 

3

 

 

Sessions with AWS

Session

Tools

Session Agenda

Hands on Exercise

Duration  

(hours)

1 

AWS Console

IAM

EMR

• What is BigData, Machine Learning, Deep Learning

• Need of BigData

• Why Cloud? IaaS, PaaS, SaaS

• 5V of BigData

• BigData Pipeline

• Amazon EMR

Use cases - Batch Data Processing VS Data Warehousing VS Data Lake VS Streaming Data

 

Demo & Lab - Launching EMR Cluster

4

2 

Amazon S3, Glue, Lake Formation, RDS, Kinesis, DMS, APIs & SDK

Ingestion & Collection of Data

QUIZ - 1

 

Demo & Lab - Launching EMR Cluster

4

3 

 

• Storages on AWS for BigData & Machine Learning

• Data Lakes

 

 

4

4 

Glue, Data Brew, SageMaker Notebook, Hive, PySpark

• Processing BigData Cleaning, Transformation, Cataloging & governing

• Hive, PySpark, AWS Glue, AWS Data Brew

Best Practices: Partitioning, Formatting, Compressing, Sizing

QUIZ - 2

 

Demo: Transforming batch data using AWS Glue.

Demo & Lab: Complete transformation of Raw data to Processed data in Parquet

Demo: Launching SageMaker Notebook

4

5 

Athena, Redshift, Quick sight, SageMaker

- Analytics & Visualization

- Data Warehousing

 

Demo: Launching Redshift Cluster

4

6 

Ground Truth, SageMaker Inference, Notebook

• Machine Learning

• Machine Learning Pipeline

• Supervised, Unsupervised, Reinforcement Algorithms

• SageMaker

• SageMaker Ground Truth, Notebook

• Splitting Data & Cross Validation

• Model Training with SageMaker

QUIZ - 3

 

Demo: Image processing using SageMaker Ground truth

4

7 

 

• Model Evaluation: Underfitting & Overfitting

• Metrics: Accuracy, Precision, Recall

• Feature Engineering

Model Deployment & Monitoring

QUIZ - 4

 

Demo: Creating Amazon SageMaker Training Job

4

 

CG Mock Presentations

 

3

 

Final Project Presentation and Assessment – NUS and Amazon (AWS)

 

3 

Assessment Criteria

Assessment Component Weightage
Continuous Quiz (Weekly Group Assignments/Quiz) 30%
Final Quiz (End Term Quiz) 20%
Project Presentation 50%
testimonial

Certificate of Achievement
from Corporate Gurukul

testimonial

Certificate of Completion
by Amazon

testimonial

Certificate of Completion
by NUS Advanced Computing for Executives

LETTER OF EVALUATION (LOE) FROM NUS School of Computing
Pedagogy
Curriculum

Sessions with NUS

Session

Duration  

(hours)

Session Agenda

Assessment

1

3

  • IntroductiontoData Analytics

  • WhatisDataAnalytics

    • Types of Data Analytics

    • Data in Data Analytics + Decision Models – Data Mining Process

  • ExploratoryDataAnalysis

    • Data Visualization

    • Data Querying

    • Statistical Methods for Summarizing Data

  • Exploring data using Pivot Tables

2

3

  • DescriptiveStatistical Measures

  • WhatisDescriptiveAnalytics?

    • Populations and Samples

    • Measures of Location

    • Measures of Dispersion

    • Measures of Shape

    • Measures of Association

  • ProjectBriefingandGroupFormation

Quiz 1

3

3

  • Regression

    • Introduction to Regression Analysis

    • Simple Linear Regression

    • Multi Linear Regression

    • Stepwise Regression

    • Coding Scheme for Categorical Variables

    • Problems with Linear Regression

 

4

3

  • Introduction to Classification

    • Decision Trees

    • Bayesian Classifier

    • Logistic Regression

    • Support Vector

  • Machine Separating

  • Hyperplane

  • Maximal Margin Classifier Support

  • Vector Classifier

    • Resampling Methods

5

3

  • Introduction to Clustering

    • Affinity Measures and Partition Methods

    • K-means

    • K-medoids

    • Hierarchical Methods

  • Introduction to Association

    • Structure and Representation of Association Rules

    • Strong Association Rules and the Concept of Frequent

  • Item sets – Apriori Algorithm

    • FP Growth

  • Time Series Analysis

 

6

3

  • Introduction to Text Mining

    • Text Mining Terminologies

    • Text Mining Concepts

    • Text Mining Process

  • Knowledge Extraction Methods for Text Mining

    • Classification

    • Clustering

  • Association

Quiz 3

7

3

Artificial Neural Networks(ANN)

  • Introduction

  • Perceptrons and Activation Functions

  • Building Blocks of Neural Networks (Input, Hidden, Output layers)

  • Hands-On Exercise: Building a Simple Neural Network (XOR Problem)

    • How to develop ANN using Tensorflow

  • Back-Propagation

    • Gradient Descent, Momentum, Learning Rate, Overfitting

 

8

3

  • Convolutional Neural Networks (CNN)

    • Convolution, pooling operations

    • Popular CNN architectures

    • Applications of CNN in Python

Quiz 4

9

3

  • Recurrent Neural Networks (RNN)

    • Vanilla RNN

    • LSTM and GRU

    • Applications of RNN in Python

 

9

3

GenerativeAI

  • Part 1: Introduction to Generative Models:

    • What are generative models?

    • Overview of model types: GANs, VAEs, and transformers.

  • Part 2: GANs (Generative Adversarial Networks)

    • Basic architecture: Generator and Discriminator.

    • Simple applications: Image generation,music generation (hands-on)

    • VAEs (Variational Autoencoders)

    • Encoder-decoder architecture.

    • Use cases: Image denoising.

    • Transformers in Generative AI

    • Overview of transformer architecture.

    • Applications: Text generation with GPT models.

  • Part 3: Applications and Ethical Considerations

    • Highlighting practical applications of each model type.

    • Brief discussion on ethical implications like deepfakes and bias.

ReinforcementLearning (RL)

  • Introduction

  • RL Algorithms

    • Dynamic Programming (DP)

    • Monte Carlo Methods

    • Temporal-Difference Learning (TD)

  • Implementing RL algorithm using Python

Final Quiz

 

 

CG Mock Presentations (CG with TAs)

 

 

 

Final Project Presentation and Assessment - NUS

 
Schedule

Sessions with NUS

Session

Session  By 

Session Agenda

Duration  

(hours)

1

 NUS

Introduction to Data Analytics

What is Data Analytics

- Types of Data Analytics

- Data in Data Analytics + Decision Models – Data Mining Process

Exploratory Data Analysis

- Data Visualization

- Data Querying

- Statistical Methods for Summarizing Data – Exploring Data using Pivot Tables

 

3

2

  NUS

Descriptive Statistical Measures 

What is Descriptive Analytics? 

- Populations and Samples 

- Measures of Location 

- Measures of Dispersion 

- Measures of Shape 

- Measures of Association 

Project Briefing and Group Formation  

QUIZ 

 

3

3 

 NUS

Regression 

-Introduction to Regression Analysis 

- Simple Linear Regression 

 

- Multi Linear Regression 

- Stepwise Regression 

- Coding Scheme for Categorical Variables

- Problems with Linear Regression

 

3

4

  NUS

Introduction to Classification 

Classification 

- Decision Trees 

- Bayesian Classifier 

- Logistic Regression  

- Support Vector Machine 

Separating Hyperplane 

Maximal Margin Classifier

 

Support Vector Classifier 

Resampling Methods 

 

3

5

  NUS

ntroduction to Clustering 

- Affinity Measures and Partition Methods 

- K-means 

- K-medoids 

- Hierarchical Methods

  

Introduction to Association 

- Structure and Representation of Association Rules 

- Strong Association Rules and the Concept of Frequent Item sets – Apriori Algorithm 

- FP Growth 

- Time Series Analysis

 

3

6

  NUS

Introduction to Text Mining 

- Text Mining Terminologies 

- Text Mining Concepts 

- Text Mining Process 

Knowledge Extraction Methods for Text Mining 

- Classification 

- Clustering 

- Association  

QUIZ 

 

3

7 

  NUS

Artificial Neural Networks (ANN) 

Overview of ANN 

Why ANN? 

Back-propagation 

 

3

8

 NUS

Artificial Neural Networks (ANN) 

- Gradient descent algorithm (GD) 

- Difficulties of training ANN 

- Advanced GD algorithm 

- Other training techniques of ANN 

QUIZ 

 

3

9 

 NUS

Convolutional Neural Networks (CNN) 

- Convolution, pooling operations 

- Popular CNN architectures 

 

3

10

 NUS

- Applications of CNN in Python 

Recurrent Neural Networks (RNN) 

- Vanilla RNN 

- LSTM and GRU 

- Applications of RNN in Python 

NUS Final Quiz 

 

3

 

 

Sessions with AWS

Session

Tools

Session Agenda

Hands on Exercise

Duration  

(hours)

1 

AWS Console

IAM

EMR

• What is BigData, Machine Learning, Deep Learning

• Need of BigData

• Why Cloud? IaaS, PaaS, SaaS

• 5V of BigData

• BigData Pipeline

• Amazon EMR

Use cases - Batch Data Processing VS Data Warehousing VS Data Lake VS Streaming Data

 

Demo & Lab - Launching EMR Cluster

4

2 

Amazon S3, Glue, Lake Formation, RDS, Kinesis, DMS, APIs & SDK

Ingestion & Collection of Data

QUIZ - 1

 

Demo & Lab - Launching EMR Cluster

4

3 

 

• Storages on AWS for BigData & Machine Learning

• Data Lakes

 

 

4

4 

Glue, Data Brew, SageMaker Notebook, Hive, PySpark

• Processing BigData Cleaning, Transformation, Cataloging & governing

• Hive, PySpark, AWS Glue, AWS Data Brew

Best Practices: Partitioning, Formatting, Compressing, Sizing

QUIZ - 2

 

Demo: Transforming batch data using AWS Glue.

Demo & Lab: Complete transformation of Raw data to Processed data in Parquet

Demo: Launching SageMaker Notebook

4

5 

Athena, Redshift, Quick sight, SageMaker

- Analytics & Visualization

- Data Warehousing

 

Demo: Launching Redshift Cluster

4

6 

Ground Truth, SageMaker Inference, Notebook

• Machine Learning

• Machine Learning Pipeline

• Supervised, Unsupervised, Reinforcement Algorithms

• SageMaker

• SageMaker Ground Truth, Notebook

• Splitting Data & Cross Validation

• Model Training with SageMaker

QUIZ - 3

 

Demo: Image processing using SageMaker Ground truth

4

7 

 

• Model Evaluation: Underfitting & Overfitting

• Metrics: Accuracy, Precision, Recall

• Feature Engineering

Model Deployment & Monitoring

QUIZ - 4

 

Demo: Creating Amazon SageMaker Training Job

4

 

CG Mock Presentations

 

3

 

Final Project Presentation and Assessment – NUS and Amazon (AWS)

 

3 
Assessment

Assessment Criteria

Assessment Component Weightage
Continuous Quiz (Weekly Group Assignments/Quiz) 30%
Final Quiz (End Term Quiz) 20%
Project Presentation 50%
Programme Completion Documents
testimonial

Certificate of Achievement
from Corporate Gurukul

testimonial

Certificate of Completion
by Amazon

testimonial

Certificate of Completion
by NUS Advanced Computing for Executives

LETTER OF EVALUATION (LOE) FROM NUS School of Computing

Admissions

Admissions to GAIP is highly selective, and has evolved over the last 15 years to reflect characteristics such as compassion, pursuit of excellence, curiosity, etc. embodied by our most successful interns. When you apply, be prepared to talk about your accomplishments and what are your career goals and aspirations.

GAIP HIGH ACHIEVER CERTIFICATES

This is awarded to the top 3 participants of each module. It 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.

Dr. TAN Wee Kek

Dr. TAN Wee Kek

Associate Professor

Department of Information Systems & Analytics
School of Computing
National University of Singapore

Dr. TAN Wee Kek is currently an Associate Professor in the Department of Information Systems & Analytics at the School of Computing, National University of Singapore. He is also a Fellow of the prestigious NUS Teaching Academy. He graduated with a Doctor of Philosophy in Information Systems in July 2013 and a Bachelor of Computing in Information Systems (1st Class Honours) in July 2007, both from the National University of Singapore. Prior to this, he attended Singapore Polytechnic and graduated with a Diploma in Computer Information Systems with Merit in July 2001.

 

His current primary research interests focus on consumer-based information technology (e.g., online decision aids, social computing, virtual worlds and consumer cloud services). Most of his research is based on design science, a well-established problem-solving paradigm that has been widely adopted in information systems research. His current secondary research interests focus on information systems education.

 

His work has been published or is forthcoming in journals such as Journal of the American Society for Information Science and Technology (JASIST), Decision Support Systems (DSS), Communications of the Association for Information Systems (CAIS), and Journal of Information Systems Education (JISE). His work has also been presented or is forthcoming in conferences such as ACM SIGMIS Computer Personnel Research Conference (SIGMIS-CPR), IFIP Working Group 8.2 Working Conference (IFIP WG8.2), European Conference on Information Systems (ECIS), Americas Conference on Information Systems (AMCIS), and International Conference on Human-Computer Interaction (ICHCI).

Prof. Samantha Sow Jin Sze

Senior Lecturer

Department of Information Systems and Analytics at NUS Computing

Samantha Sow is a Senior Lecturer in the Department of Information Systems and Analytics at the National University of Singapore (NUS). She has over 8+ years of experience in Business Analytics and Data Science and she conducts training for both government agencies and corporate clients. Before joining NUS, she lectures at Temasek Polytechnic, teaching Business Analytics and Data Science to professionals, managers and executives (PMEs).

Samantha completed her Master of Education from the University of Sheffield and graduated from the National University of Singapore with a Bachelor’s in Engineering, First Class Honours.

She works on enterprise transformation projects with clients. Her passion lies in engaging and inspiring participants to enhance their workplace analytics capabilities and business intelligence quotient within their organisations.

Dr. Amirhassan Monajemi

Senior Lecturer

School of Computing
National University of Singapore

Dr Amirhassan Monajemi is a Senior Lecturer in AI and Machine Learning with the School of Computing (SoC) at the National University of Singapore (NUS). Prior to SoC, he was a Senior Lecturer in NUS School of Continuing and Lifelong Education (SCALE) teaching AI and Data Science to adult learners. Before joining NUS, he was with the Faculty of Computer Engineering, University of Isfahan, Iran, where he was serving as a professor of AI, Machine Learning, and Data Science.

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.

Dr. TAN Wee Kek

Dr. TAN Wee Kek

Associate Professor

Department of Information Systems & Analytics
School of Computing
National University of Singapore

Dr. TAN Wee Kek is currently an Associate Professor in the Department of Information Systems & Analytics at the School of Computing, National University of Singapore. He is also a Fellow of the prestigious NUS Teaching Academy. He graduated with a Doctor of Philosophy in Information Systems in July 2013 and a Bachelor of Computing in Information Systems (1st Class Honours) in July 2007, both from the National University of Singapore. Prior to this, he attended Singapore Polytechnic and graduated with a Diploma in Computer Information Systems with Merit in July 2001.

 

His current primary research interests focus on consumer-based information technology (e.g., online decision aids, social computing, virtual worlds and consumer cloud services). Most of his research is based on design science, a well-established problem-solving paradigm that has been widely adopted in information systems research. His current secondary research interests focus on information systems education.

 

His work has been published or is forthcoming in journals such as Journal of the American Society for Information Science and Technology (JASIST), Decision Support Systems (DSS), Communications of the Association for Information Systems (CAIS), and Journal of Information Systems Education (JISE). His work has also been presented or is forthcoming in conferences such as ACM SIGMIS Computer Personnel Research Conference (SIGMIS-CPR), IFIP Working Group 8.2 Working Conference (IFIP WG8.2), European Conference on Information Systems (ECIS), Americas Conference on Information Systems (AMCIS), and International Conference on Human-Computer Interaction (ICHCI).

Prof. Samantha Sow Jin Sze

Senior Lecturer

Department of Information Systems and Analytics at NUS Computing

Samantha Sow is a Senior Lecturer in the Department of Information Systems and Analytics at the National University of Singapore (NUS). She has over 8+ years of experience in Business Analytics and Data Science and she conducts training for both government agencies and corporate clients. Before joining NUS, she lectures at Temasek Polytechnic, teaching Business Analytics and Data Science to professionals, managers and executives (PMEs).

Samantha completed her Master of Education from the University of Sheffield and graduated from the National University of Singapore with a Bachelor’s in Engineering, First Class Honours.

She works on enterprise transformation projects with clients. Her passion lies in engaging and inspiring participants to enhance their workplace analytics capabilities and business intelligence quotient within their organisations.

Dr. Amirhassan Monajemi

Senior Lecturer

School of Computing
National University of Singapore

Dr Amirhassan Monajemi is a Senior Lecturer in AI and Machine Learning with the School of Computing (SoC) at the National University of Singapore (NUS). Prior to SoC, he was a Senior Lecturer in NUS School of Continuing and Lifelong Education (SCALE) teaching AI and Data Science to adult learners. Before joining NUS, he was with the Faculty of Computer Engineering, University of Isfahan, Iran, where he was serving as a professor of AI, Machine Learning, and Data Science.

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

Frequently Asked Questions

Who is organizing the academic internship?

Corporate Gurukul is organizing the academic internship in association with professor(s) from NUS School of Computing and professional(s) from Amazon Web Services (AWS).

GAIP will be conducted on-campus at the NUS School of Computing.

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

In order to know about the programme and cost involved please refer to the programme details above.

Previous academic internship updates are available on our Facebook page. Check out the link here.

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

The admissions are purely on merit. And GAIP serves as a very strong platform for strengthening your application. However, we do not guarantee any admissions at NUS. You can explore admission requirements and financial aids by visiting the admissions department at NUS in your free time.

What is the deadline to submit the application form?

The application deadline is Closing Soon.

You are required to apply online using the Enroll Now button. Follow the steps of the application process available on your dashboard.

The selection criteria are as follows:

  1. Aggregate CGPA of all semesters till date
  2. Pre-requisite Test Scores
  3. Projects/Courses taken up in the relevant module chosen
  4. Essays - Relevant career goals, interest areas and learning experiences

For Data Analytics using Deep Learning you will be assessed on the following:

  1. Python
  2. Probability and Statistics

 

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

The payment deadlines will be mentioned in your ‘Offer Letter’. You are eligible for the ‘Offer Letter’ only if you are selected.

Your application is automatically cancelled due to non payment of fees by the specified deadline. Any extension requests are at the sole discretion of the admissions department and availability of seats. You will be required to send an email to contact@corporategurukul.com requesting for an extension* and the reason for delay in payment. *Extension requests should be made at least 24 hours prior to your payment deadline

Yes, accommodation is mandatory as all participants are required to be at the same place for project work / assignments to ensure that the team or the project don't get impacted.

  1. Curriculum design, training, assignments and evaluation by professor(s) from NUS School of Computing
  2. Curriculum design, training and assignments by certified professional(s) from Amazon Web Services (AWS)
  3. Certificate of Completion by NUS Advanced Computing for Executives
  4. Certificate of Completion by Amazon Web Services (AWS)
  5. Letter of Evaluation by faculty from NUS School of Computing
  6. Certificate of Achievement by Corporate Gurukul, Singapore co-signed by NUS Advanced Computing for Executives and Amazon Web Services (AWS)
  7. Accommodation
  1. Flights/Visa/Travel Insurance
  2. Local Transport in India
  3. Breakfast, Lunch and Dinner
  4. International SIM Card
  5. Local Transport in Singapore for personal visits/sightseeing
  6. Entrance Fee to various tourist attractions in Singapore
  7. Medical expenses in Singapore
  8. Gym, laundry or any other hostel facility charges
  9. Stay in Singapore before or after academic internship dates
  10. INR 600 for Prerequisite test
  1. The certificates will be awarded during the Valedictory Ceremony at the end of the programme.
  2. The LOE(s) will be posted to your respective institutes 60 days post the programme completion.

Which certificate(s) and letter(s) will I get after completion of this academic internship?
  1. Certificate of Completion by NUS Advanced Computing for Executives
  2. Certificate of Completion by Amazon Web Services (AWS)
  3. Letter of Evaluation by faculty from NUS School of Computing
  4. Certificate of Achievement by Corporate Gurukul, Singapore co-signed by NUS Advanced Computing for Executives and Amazon Web Services (AWS)

Issuance of all certificates and the LoE will be at Corporate Gurukul’s discretion subject to:
a. the participant’s performance
b. completion of assignments and
c. 90% attendance during the academic internship

Yes

Where are the hands-on sessions conducted?
  1. 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).
  2. Laptop with the specifications mentioned in OFFER LETTER is MANDATORY for all participants.

 

  1. Microsoft Excel
  2. VMware workstation or latest Vmplayer installed (Win) or VMware fusion with License (Mac)

In the past batches, about 10% of students have secured grade O or A+.

The cohort size per batch is a maximum of 85 participants. The number of batches during the programme will be subject to the number of enrollments.

Yes, incase of multiple batches in a particular programme the faculty profiles will be different. The same will be shared post your batch is confirmed.

No. The entire academic internship is delivered at NUS School of Computing.

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 the pre requisite 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.

  1. Assignments will be given daily and need to be submitted as per specified deadline.
  2. 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 NUS School of Computing and Amazon sessions.

Participants will be assessed based on the following components:

  • Continuous Quiz (Weekly Group Assignments/Quiz) - 30% weightage
  • Final Quiz (End Term Quiz) - 20% weightage
  • Project Presentation - 50% weightage

Yes, both NUS School of Computing and Amazon sessions will be graded. They are graded individually.

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.

Participants may independently, on their own initiative meet Professor(s) with prior appointment. Corporate Gurukul’s participation or GAIP should nowhere be mentioned for such interactions are outside the scope of GAIP.

Where do we stay in Singapore?

You will stay in a hostel/ hotel in Singapore. The exact hostel/ hotel address and facilities will be informed to you during academic internship orientation.

Coach services will be provided for transfer from hostel/ hotel to university and back.

Reach the airport at least three hours prior to the departure.

The exact dates and timing will be issued to you formally upon successful admission for GAIP. Kindly hold your ticket booking till that time.

The exact dates and timing will be issued to you formally upon successful admission for GAIP. Kindly hold your ticket booking till that time.

Airport Transfers are not covered as a part of programme deliverables. However, Corporate Gurukul may arrange for coach services for pick up from Airport and drop at hostel/ hotel if there are a lot of students travelling during the same time slot.

Please note that there is no drop facility from hostel/ hotel to airport during the return journey.

  1. Please approach Authorized Visa Agents (AVA) only for Visa processing. You may check the list of AVAs for Singapore here.
  2. The Visa processing fee is S$ 30 (INR 1500). The agent will charge you additional fee of INR 300-500.
  3. You need to apply for TOURIST VISA only.
  4. You will be granted 30 days of stay from the day you enter Singapore.

The immigration process takes typically 2-3 minutes per individual.
Refer below links for the arrival and departure immigration process:

a. On Arrival Immigration Process - https://youtu.be/yvL8nPEuQIE
b. Departure Immigration Process - https://youtu.be/xgTHVn5y4Cs

You will be required to show your passport, boarding pass and E-Visa to the immigration officer. They might ask for additional supporting documents as below. Please carry the following documents along with one set of photocopy (mandatory):

  1. Passport
  2. Offer Letter
  3. Admission Letter
  4. Visa Invite Letter
  5. E-Visa
  6. Personal Travel Insurance (if applied)
  7. 2 nos. of passport size photograph
  1. Laptop (and charger) with mentioned specs:
  2. SIN $1000 Card/International Credit Card for personal expenses
  3. SIN $30-SIN $50 for SIM Card and international Calling
  4. Travel adapter for Singapore. Buy here.
  5. Mobile phone with charger
  6. Bathing Towel with preferred soap and shampoo
  7. Bedsheet (2 Nos.)
  8. Digital Camera
  9. Foldable Umbrella (it rains anytime/ any day in Singapore)
  10. Hair and personal grooming (it costs 5 times that of India)
  11. Water Bottle
  12. Medical Kit (if applicable).Prescription is required for drugs administered for specific illness. You do not require a prescription for Over the Counter (OTC) drugs.
  13. Indian/ Western formals for trainings sessions and meetings
  14. One pair of black formal shoes
  15. Jacket/ Blazer/Suit for formal occasion/ photo-shoot
  16. Swim wear/ shorts/ slippers for the beach (though you can buy in Singapore, its costly)
  17. Carry a pair of sun-glasses for outdoors and beach (remember Singapore is on the equator)
  18. Flight Check-in baggage with locking facility (as per your luggage allowance)
  19. Refer carefully the list of objects that CANNOT be carried in hand-carry baggage for flight

The hostel/ hotel booking will be done by Corporate Gurukul as per the following schedule:

Hostel/ Hotel Check-in

Time: 2:00 PM SGT onwards
Early check-in (same day) may be available at a fee if there is a vacancy.

Hostel/ Hotel Check-out

Time: Before 12:00 PM
Late check-out is not available.

No, the hostels/hotels are booked only for the programme duration. Should you wish to extend your stay, you will need to arrange for accommodation on your own.

They will be confirmed one month prior to the programme commencement. Typical facilities include:
 

In Room

a. Non-Air-conditioned Room
b. Single Bed
c. One set of linen (Bedspread. Pillow cover, Thin Blanket)
d. Study table and chair
e. Wardrobe (with locking facility)
f. Mobile pedestal
g. Ceiling Fan
h. Window curtains
i. Wi-Fi


Common Facilities

a. Shower and Toilet Facilities
b. Food court/restaurant near hostel (Veg and Non-veg)
Please note Sports and Gym facilities may not be accessible.

  1. Please carry at least two sets of formals for introductory session, formal photo shoot and Valedictory ceremony.
  2. You can refer here for formal dressing guidelines
  3. You can wear smart casuals during sessions unless specifically asked to wear formals.
  4. Smart casuals include jeans, t-shirts, shirts, trousers, kurtis (for girls).
  5. Please do not wear shorts and slippers to class.
  1. Shorts are allowed in the hostel for both boys and girls.
  2. Attire such as skimpy or revealing clothes or clothes printed with vulgar or offensive words or pictures should be avoided.

Your travel insurance policy should cover all charges incurred for medical expenses. Please read all scheme related documents carefully for inclusions and exclusions. Corporate Gurukul will not be responsible for any personal expenses made which are covered or not covered by your insurance policy. Also, make sure you travel with enough money for emergency.

Corporate Gurukul Programme Manager(s) typically stay in the same hostel as you. You can approach them for any help. Their details will be shared with you during orientation.

Vegetarian, as well as non-vegetarian food is easily available inside and outside university campus. There is wide range of choice amongst Indian, Chinese, European, Malay, Thai, Vietnamese and Indonesian cuisines. Typically, 3 meals in a day should cost you between S$18 - S$25. However, the estimate may vary as per your dining choices.

About GAIP

Who is organizing the academic internship?

Corporate Gurukul is organizing the academic internship in association with professor(s) from NUS School of Computing and professional(s) from Amazon Web Services (AWS).

GAIP will be conducted on-campus at the NUS School of Computing.

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

In order to know about the programme and cost involved please refer to the programme details above.

Previous academic internship updates are available on our Facebook page. Check out the link here.

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

The admissions are purely on merit. And GAIP serves as a very strong platform for strengthening your application. However, we do not guarantee any admissions at NUS. You can explore admission requirements and financial aids by visiting the admissions department at NUS in your free time.

Applying for GAIP

What is the deadline to submit the application form?

The application deadline is Closing Soon.

You are required to apply online using the Enroll Now button. Follow the steps of the application process available on your dashboard.

The selection criteria are as follows:

  1. Aggregate CGPA of all semesters till date
  2. Pre-requisite Test Scores
  3. Projects/Courses taken up in the relevant module chosen
  4. Essays - Relevant career goals, interest areas and learning experiences

For Data Analytics using Deep Learning you will be assessed on the following:

  1. Python
  2. Probability and Statistics

 

Payment

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

The payment deadlines will be mentioned in your ‘Offer Letter’. You are eligible for the ‘Offer Letter’ only if you are selected.

Your application is automatically cancelled due to non payment of fees by the specified deadline. Any extension requests are at the sole discretion of the admissions department and availability of seats. You will be required to send an email to contact@corporategurukul.com requesting for an extension* and the reason for delay in payment. *Extension requests should be made at least 24 hours prior to your payment deadline

Yes, accommodation is mandatory as all participants are required to be at the same place for project work / assignments to ensure that the team or the project don't get impacted.

  1. Curriculum design, training, assignments and evaluation by professor(s) from NUS School of Computing
  2. Curriculum design, training and assignments by certified professional(s) from Amazon Web Services (AWS)
  3. Certificate of Completion by NUS Advanced Computing for Executives
  4. Certificate of Completion by Amazon Web Services (AWS)
  5. Letter of Evaluation by faculty from NUS School of Computing
  6. Certificate of Achievement by Corporate Gurukul, Singapore co-signed by NUS Advanced Computing for Executives and Amazon Web Services (AWS)
  7. Accommodation
  1. Flights/Visa/Travel Insurance
  2. Local Transport in India
  3. Breakfast, Lunch and Dinner
  4. International SIM Card
  5. Local Transport in Singapore for personal visits/sightseeing
  6. Entrance Fee to various tourist attractions in Singapore
  7. Medical expenses in Singapore
  8. Gym, laundry or any other hostel facility charges
  9. Stay in Singapore before or after academic internship dates
  10. INR 600 for Prerequisite test
  1. The certificates will be awarded during the Valedictory Ceremony at the end of the programme.
  2. The LOE(s) will be posted to your respective institutes 60 days post the programme completion.

Programme Completion Documents

Which certificate(s) and letter(s) will I get after completion of this academic internship?
  1. Certificate of Completion by NUS Advanced Computing for Executives
  2. Certificate of Completion by Amazon Web Services (AWS)
  3. Letter of Evaluation by faculty from NUS School of Computing
  4. Certificate of Achievement by Corporate Gurukul, Singapore co-signed by NUS Advanced Computing for Executives and Amazon Web Services (AWS)

Issuance of all certificates and the LoE will be at Corporate Gurukul’s discretion subject to:
a. the participant’s performance
b. completion of assignments and
c. 90% attendance during the academic internship

Yes

Academics

Where are the hands-on sessions conducted?
  1. 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).
  2. Laptop with the specifications mentioned in OFFER LETTER is MANDATORY for all participants.

 

  1. Microsoft Excel
  2. VMware workstation or latest Vmplayer installed (Win) or VMware fusion with License (Mac)

In the past batches, about 10% of students have secured grade O or A+.

The cohort size per batch is a maximum of 85 participants. The number of batches during the programme will be subject to the number of enrollments.

Yes, incase of multiple batches in a particular programme the faculty profiles will be different. The same will be shared post your batch is confirmed.

No. The entire academic internship is delivered at NUS School of Computing.

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 the pre requisite 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.

  1. Assignments will be given daily and need to be submitted as per specified deadline.
  2. 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 NUS School of Computing and Amazon sessions.

Participants will be assessed based on the following components:

  • Continuous Quiz (Weekly Group Assignments/Quiz) - 30% weightage
  • Final Quiz (End Term Quiz) - 20% weightage
  • Project Presentation - 50% weightage

Yes, both NUS School of Computing and Amazon sessions will be graded. They are graded individually.

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.

Participants may independently, on their own initiative meet Professor(s) with prior appointment. Corporate Gurukul’s participation or GAIP should nowhere be mentioned for such interactions are outside the scope of GAIP.

Travel and Accomodation

Where do we stay in Singapore?

You will stay in a hostel/ hotel in Singapore. The exact hostel/ hotel address and facilities will be informed to you during academic internship orientation.

Coach services will be provided for transfer from hostel/ hotel to university and back.

Reach the airport at least three hours prior to the departure.

The exact dates and timing will be issued to you formally upon successful admission for GAIP. Kindly hold your ticket booking till that time.

The exact dates and timing will be issued to you formally upon successful admission for GAIP. Kindly hold your ticket booking till that time.

Airport Transfers are not covered as a part of programme deliverables. However, Corporate Gurukul may arrange for coach services for pick up from Airport and drop at hostel/ hotel if there are a lot of students travelling during the same time slot.

Please note that there is no drop facility from hostel/ hotel to airport during the return journey.

  1. Please approach Authorized Visa Agents (AVA) only for Visa processing. You may check the list of AVAs for Singapore here.
  2. The Visa processing fee is S$ 30 (INR 1500). The agent will charge you additional fee of INR 300-500.
  3. You need to apply for TOURIST VISA only.
  4. You will be granted 30 days of stay from the day you enter Singapore.

The immigration process takes typically 2-3 minutes per individual.
Refer below links for the arrival and departure immigration process:

a. On Arrival Immigration Process - https://youtu.be/yvL8nPEuQIE
b. Departure Immigration Process - https://youtu.be/xgTHVn5y4Cs

You will be required to show your passport, boarding pass and E-Visa to the immigration officer. They might ask for additional supporting documents as below. Please carry the following documents along with one set of photocopy (mandatory):

  1. Passport
  2. Offer Letter
  3. Admission Letter
  4. Visa Invite Letter
  5. E-Visa
  6. Personal Travel Insurance (if applied)
  7. 2 nos. of passport size photograph
  1. Laptop (and charger) with mentioned specs:
  2. SIN $1000 Card/International Credit Card for personal expenses
  3. SIN $30-SIN $50 for SIM Card and international Calling
  4. Travel adapter for Singapore. Buy here.
  5. Mobile phone with charger
  6. Bathing Towel with preferred soap and shampoo
  7. Bedsheet (2 Nos.)
  8. Digital Camera
  9. Foldable Umbrella (it rains anytime/ any day in Singapore)
  10. Hair and personal grooming (it costs 5 times that of India)
  11. Water Bottle
  12. Medical Kit (if applicable).Prescription is required for drugs administered for specific illness. You do not require a prescription for Over the Counter (OTC) drugs.
  13. Indian/ Western formals for trainings sessions and meetings
  14. One pair of black formal shoes
  15. Jacket/ Blazer/Suit for formal occasion/ photo-shoot
  16. Swim wear/ shorts/ slippers for the beach (though you can buy in Singapore, its costly)
  17. Carry a pair of sun-glasses for outdoors and beach (remember Singapore is on the equator)
  18. Flight Check-in baggage with locking facility (as per your luggage allowance)
  19. Refer carefully the list of objects that CANNOT be carried in hand-carry baggage for flight

The hostel/ hotel booking will be done by Corporate Gurukul as per the following schedule:

Hostel/ Hotel Check-in

Time: 2:00 PM SGT onwards
Early check-in (same day) may be available at a fee if there is a vacancy.

Hostel/ Hotel Check-out

Time: Before 12:00 PM
Late check-out is not available.

No, the hostels/hotels are booked only for the programme duration. Should you wish to extend your stay, you will need to arrange for accommodation on your own.

They will be confirmed one month prior to the programme commencement. Typical facilities include:
 

In Room

a. Non-Air-conditioned Room
b. Single Bed
c. One set of linen (Bedspread. Pillow cover, Thin Blanket)
d. Study table and chair
e. Wardrobe (with locking facility)
f. Mobile pedestal
g. Ceiling Fan
h. Window curtains
i. Wi-Fi


Common Facilities

a. Shower and Toilet Facilities
b. Food court/restaurant near hostel (Veg and Non-veg)
Please note Sports and Gym facilities may not be accessible.

  1. Please carry at least two sets of formals for introductory session, formal photo shoot and Valedictory ceremony.
  2. You can refer here for formal dressing guidelines
  3. You can wear smart casuals during sessions unless specifically asked to wear formals.
  4. Smart casuals include jeans, t-shirts, shirts, trousers, kurtis (for girls).
  5. Please do not wear shorts and slippers to class.
  1. Shorts are allowed in the hostel for both boys and girls.
  2. Attire such as skimpy or revealing clothes or clothes printed with vulgar or offensive words or pictures should be avoided.

Your travel insurance policy should cover all charges incurred for medical expenses. Please read all scheme related documents carefully for inclusions and exclusions. Corporate Gurukul will not be responsible for any personal expenses made which are covered or not covered by your insurance policy. Also, make sure you travel with enough money for emergency.

Corporate Gurukul Programme Manager(s) typically stay in the same hostel as you. You can approach them for any help. Their details will be shared with you during orientation.

Vegetarian, as well as non-vegetarian food is easily available inside and outside university campus. There is wide range of choice amongst Indian, Chinese, European, Malay, Thai, Vietnamese and Indonesian cuisines. Typically, 3 meals in a day should cost you between S$18 - S$25. However, the estimate may vary as per your dining choices.

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