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Glimpse Glimpse

Career Accelerator Programme in
Data Science & AI

A 6-month programme designed for early-to-mid professionals to master AI from foundations to deployment.

Apply Now
image
Glimpse

Career Accelerator Programme in
Data Science & AI

Format

Offline
(Weekend-only)

Cohort-based certificate program

Cohort Starting

Jan '26

Applications starting soon

Eligibility

2+ Years

Professional experience required

Duration

6 months

Plus 1-week orientation

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Designed For Future AI Engineers, Data Scientists, ML Engineers,
Product Managers, and CTOs

Build a Customer Churn Prediction Model

Python | Scikit-learn | Pandas | Feature Engineering | A/B Testing | Regression | Classification

Create a Production-Ready OCR API

Deep Learning | PyTorch | CNNs | Vision Transformers | Model Deployment | Flask | Computer Vision

Develop a RAG System for Knowledge Retrieval

GPT-4 | LLM Fine-Tuning | LangChain | Pinecone | Retrieval-Augmented Generation | Vector Databases

Design Automated ML Pipeline

Docker | MLflow | GitHub Actions | Airflow | Model Monitoring | CI/CD | A/B Testing

Optimise a Time Series Forecasting Model

XGBoost | LightGBM | Prophet | Time Series Analysis | Regression | Forecasting

Build Optimisation Model for Business Structure

Q-Learning | Reinforcement Learning | TensorFlow | Keras | Optimization | Model Evaluation

Build a Customer Churn Prediction Model

Python | Scikit-learn | Pandas | Feature Engineering | A/B Testing | Regression | Classification

Create a Production-Ready OCR API

Deep Learning | PyTorch | CNNs | Vision Transformers | Model Deployment | Flask | Computer Vision

Develop a RAG System for Knowledge Retrieval

GPT-4 | LLM Fine-Tuning | LangChain | Pinecone | Retrieval-Augmented Generation | Vector Databases

Design Automated ML Pipeline

Docker | MLflow | GitHub Actions | Airflow | Model Monitoring | CI/CD | A/B Testing

Optimise a Time Series Forecasting Model

XGBoost | LightGBM | Prophet | Time Series Analysis | Regression | Forecasting

Build Optimisation Model for Business Structure

Q-Learning | Reinforcement Learning | TensorFlow | Keras | Optimization | Model Evaluation

Build a Customer Churn Prediction Model

Python | Scikit-learn | Pandas | Feature Engineering | A/B Testing | Regression | Classification

Create a Production-Ready OCR API

Deep Learning | PyTorch | CNNs | Vision Transformers | Model Deployment | Flask | Computer Vision

Develop a RAG System for Knowledge Retrieval

GPT-4 | LLM Fine-Tuning | LangChain | Pinecone | Retrieval-Augmented Generation | Vector Databases

Design Automated ML Pipeline

Docker | MLflow | GitHub Actions | Airflow | Model Monitoring | CI/CD | A/B Testing

Optimise a Time Series Forecasting Model

XGBoost | LightGBM | Prophet | Time Series Analysis | Regression | Forecasting

Build Optimisation Model for Business Structure

Q-Learning | Reinforcement Learning | TensorFlow | Keras | Optimization | Model Evaluation

Learn to
Build Cutting-Edge AI Models

Statistical Foundations & Classical ML

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How to Build Predictive Models with Data?

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LLMs & Generative AI

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MLOps & Production Systems

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Specialisation Track

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Model Evaluation

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Statistical Foundations & Classical ML

Deep Learning & Computer Vision

LLMs & Generative AI

MLOps & Production Systems

Specialisation Track

Industry Capstone

How to Build Predictive Models with Data?

What You Will Learn

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Master advanced statistics and A/B testing techniques

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Learn regression, classification, and tree-based models

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Build expertise in feature engineering and interpretability

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Understand real-world applications of ML algorithms

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Hands-on Project: Develop a customer churn prediction system

How to Teach Machines to See and Understand?

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Master neural networks using the PyTorch framework

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Explore Vision Transformers for advanced image tasks

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Understand object detection and OCR techniques

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Optimise and deploy deep learning models effectively

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Hands-on Project: Build a production-ready OCR API

How to Create Intelligent Language Models?

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Fine-tune large language models like GPT-4 and Claude

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Master prompt engineering and retrieval-augmented generation (RAG)

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Work with vector databases and information retrieval techniques

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Evaluate and monitor performance of LLMs effectively

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Hands-on project: Build an enterprise-level RAG system

How to Build Scalable AI Systems?

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Build robust data pipelines and feature stores efficiently

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Deploy and monitor machine learning models at scale

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Implement CI/CD pipelines for machine learning workflows

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Detect model drift and automate retraining processes

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Hands-on project: Develop an automated ML pipeline

How to Become an Expert in AI Specialisations?

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Choose a specialisation to deepen expertise:

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S1: Explore Agentic AI and multi-modal system design

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S2: Dive into time series forecasting and predictive analytics

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S3: Focus on finance, risk analysis, and quantitative modeling

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Hands-on project: Apply specialisation to real-world scenarios

How to Deliver Real-World AI Solutions?

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Design and develop a complete end-to-end production system

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Analyse the business impact of your AI solution

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Prepare a comprehensive technical defense and presentation

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Collaborate with mentors to refine your project for industry standards

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Deliverables: Design documentation, code repository, and evaluation report

The Masters' Union Edge in
Data Science & Applied AI

Experience a world-class curriculum, unparalleled mentorship, and real-world impact that will
accelerate your journey to becoming an AI leader.

Learn from Leading
AI Experts and CTOs

Courses taught by executives from Microsoft, Google, and top tech companies, along with exclusive mentorship.

1

1:1 mentorship from AI leaders at tech giants

2

Masterclasses by global AI experts and influencers

3

1:10 mentor-to-student ratio ensures personalised guidance

AI & Data Science Currciulum

Real-World Application of
AI & Data Science

Co-built with Garage Labs Tech our curriculum emphasises application and impact.

1

Develop real-world AI solutions for industries

2

Hands-on projects using industry-standard tools

3

Real-time case studies and interactive workshops

Establish Your
Presence in the AI Community

Learn how to build a strong online presence and showcase your expertise in AI through industry-specific platforms.

1

Publish your models and research on GitHub

2

Start an expert series on LinkedIn or YouTube

3

Attract employers with high-value AI insights

Enhance Communication and
Leadership Skills

Develop critical soft skills that will set you apart in the fast-paced AI industry.

1

Sharpen leadership and decision-making abilities

2

Learn how to communicate complex AI concepts clearly

3

Build confidence in executive-level presentations

Faculty & Mentorship
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Learn from Leading
AI Experts and CTOs

Courses taught by executives from Microsoft, Google, and top tech companies, along with exclusive mentorship.

1

1:1 mentorship from AI leaders at tech giants

2

Masterclasses by global AI experts and influencers

3

1:10 mentor-to-student ratio ensures personalised guidance

Icon

Real-World Application of
AI & Data Science

Co-built with Garage Labs Tech, , our curriculum emphasises application and impact.

1

Develop real-world AI solutions for industries

2

Hands-on projects using industry-standard tools

3

Real-time case studies and interactive workshops

Icon

Establish Your
Presence in the AI Community

Learn how to build a strong online presence and showcase your expertise in AI through industry-specific platforms.

1

Publish your models and research on GitHub

2

Start an expert series on LinkedIn or YouTube

3

Attract employers with high-value AI insights

Icon

Enhance Communication and
Leadership Skills

Develop critical soft skills that will set you apart in the fast-paced AI industry.

1

Sharpen leadership and decision-making abilities

2

Learn how to communicate complex AI concepts clearly

3

Build confidence in executive-level presentations

Trade with Our Expert Community

Surround yourself with AI engineers, researchers, founders, and practitioners who ship real systems. You’ll learn in public, get feedback that actually moves your work forward, and grow inside a community that builds together.

1

Publish on GitHub & HuggingFace and build a portfolio.

2

Work in small squads with weekly code & model reviews.

3

Ship 6 deployable AI agents across real industry use cases.

4

Get guidance from practicing AI engineers every term.

5

Present your work at community demos & OSS showcases.

What are derivatives?

“I've sent the Push Request”

How to select stocks?

“Merge with main branch”

How do hedge risks

“Ship via PRs into live repos”

Flexible and Immersive Learning Experience

A balanced blend of live sessions and independent work to develop real-world AI skills.

Live Sessions (Weekends)

Hands-on Learning with Expert Guidance

  • Saturday sessions focus on theory, architectures and real-world AI (4 hours)
  • Sunday sessions focus on live coding, labs and hands-on project work (4 hours)
  • 8 hours of guided, in-person, project-based sessions each weekend

Mid-Week Work (Flexible)

Flexible Self-paced Learning

  • Research papers and technical reading for 2–3 hours on modern AI systems
  • Coding assignments for 2–3 hours implementing models and core techniques
  • Case studies, peer reviews and short quizzes to reinforce applied learning

Enrollment Checklist
Admissions Criteria

01.
Academic Background

01.
Academic Background

A undergraduate degree is required, with preference for STEM disciplines. Strong analytical aptitude from any background will be considered.

02.
Professional Experience

02.
Professional Experience

At least 2 years of experience in tech, data, or product roles, showing ownership, problem-solving ability, and sound decision-making.

03.
Technical Aptitude

03.
Technical Aptitude

A basic understanding of programming, particularly in Python, and familiarity with data structures or analytics tools are essential to succeed in the program.

04.
Critical Thinking

04.
Critical Thinking

The ability to approach complex problems logically, interpret data patterns, and make informed, high-impact decisions is crucial.

01.

Online
Application

01.

Online
Application

Essential Details:

  • Basic personal details

  • Academic history and work experience

  • A short motivation statement

  • Documents like CV/ résumé, and degree details

  • LinkedIn and/or GitHub links

Since each cohort is limited to 50 seats, the application helps us understand your journey, intent, and fit for a fast-paced, hands-on programme.

02.

Technical
Screening

02.

Technical Screening

About the Test

Shortlisted candidates will complete a 30-minute technical screening.

This assessment checks your baseline comfort with:

  • Programming fundamentals (preferably in Python)

  • Data analysis and working with structured information

  • Logical reasoning and problem-solving

It’s not about trick questions; it’s about making sure you’re ready for the depth and pace of the curriculum.

03.

Brief
Interview

03.

Brief
Interview

About the Interview

Next, you’ll have a short conversation with the admissions team.
We’ll explore:

  • Your career goals and where you want to go with AI

  • Why you’re applying to this programme now

  • How you think, learn, and collaborate

This is also your space to clarify expectations, ask questions, and assess whether the programme matches your ambition.

04.

Admission
Decision

04.

Admission
Decision

Status of Evaluation

After the full evaluation (application, technical screening, and interview), the admissions team will share your final status. Candidates typically fall into three categories:

Accepted

  • You’re offered admission into the upcoming cohort. Your offer will include programme details and fee structure, along with a window of time to confirm your seat by paying the admission fee.

Waitlisted

  • You’re a strong fit, but the cohort is near capacity. Your admission will depend on seats opening up. The committee periodically reviews the waitlist and promotes candidates as spots become available.

Not Selected

  • You haven’t been shortlisted for this cohort. You’re welcome to strengthen your profile and apply again in a future cycle.

Fee Structure

Fee Timelines
Due Date
Amount
 3 years in India + 1 year in US
Global Track
Admission Offer Acceptance Within 7 days of offer INR 1,00,000/- INR 1,00,000/-
Programme Commencement Before start of classes INR 7,00,000/- INR 15,95,000/-
Mid-Programme Installment After 3 months INR 4,00,000/- INR 17,85,000/-
Total

INR 12,00,000/-
 3 years in India + 1 year in US
Global Track

Scholarships

Based on your academic record, professional experience, and personal circumstances, you may be eligible for merit-based or need-based scholarships.

Merit-Based Scholarships

Scholarships awarded to learners who demonstrate exceptional academic strength, professional experience, and technical aptitude.

  • Top Performer: Awarded to the top 3 students based on performance in the first 6 weeks.
  • High Achiever: Awarded to students ranked 4-10 in the first 6 weeks.
  • Early Bird: Available to the first 15 applicants.
  • Referral: For those who bring a classmate to join the programme.

Need-Based Scholarships

Support for candidates facing financial constraints, ensuring talent is never limited by affordability.

  • Women in Tech: Supporting gender diversity in the field of AI.
  • Corporate Employer-Sponsored: For students from corporate-sponsored groups (5+ candidates).

World-Class Campus in the Heart of Gurugram

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