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Master's of Science in Data Science

Get a 2-year full time Master's in Data Science with the latest cutting edge curriculum from one of the top 100 best global universities in the world, University of Arizona.

5 out of 6 learners get positive career growth **
upGrad Results reviewed by Deloitte

Class Structure Blended mode
24 Months Recommended 12-15 hrs/week
Dec 31, 2022 Start Date
University of Arizona Alumni Status
Top 100 (Best Global Universities in the World)by U.S. News and World report

About the Program

This full-time master’s program is offered in a blended format where students will spend their time learning online over the week and attend in-classroom sessions over the weekend. We believe the level of applied knowledge is imparted better in a classroom where students get the benefit of interacting with the professors in person and also get a hands-on experience of practical scenarios.

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Weekend classroom sessions to accommodate different work commitments

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In-depth theoretical and lab sessions on various data science, AI, and ML concepts

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100% career support by upGrad

Program Overview

Key Highlights

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360 Degree Career Support
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Learn from World-class Faculty​
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1350 Hours of Learning
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Global Access to Job Opportunities
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Master Classes by Industry Experts
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Resume Tool & Review
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Career Essential Soft Skills Training
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Designed for Working Professionals
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Job Assistance with Top Firms
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30+ Live Learning Sessions
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Just-in-time Interviews
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Support Available all Days 9 AM - 9 PM IST for queries
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25+ Industry-Driven Case Studies

"Our aim is simple: We strive to create high-impact, hands-on experiences that prepare students for meaningful and productive careers.”

- Ronnie Screwvala, Co-Founder, upGrad

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Syllabus
Best-in-class content by leading faculty and industry leaders in the form of videos, cases and projects.

Top Skills You Will Learn

Python, BD processing using Spark, Deploy ML Models, Supervised & Unsupervised ML Models, Predictive Analytics & Statistics

Career Prospects

Big Data Analyst, Data Engineer, Data Scientist,
Machine Learning Engineer

Who Is This Program For?

Managers and Aspiring Managers, MBA Graduates, Engineers, Professionals in various domains

Minimum Eligibility

- Minimum 16 years education (with minimum 50% score | medium of instruction - English) from an accredited college or university.

- 4 year accredited Bachelor's OR 3 year accredited Bachelor's + Master's OR 3 year accredited Bachelor's + Post Graduate Diploma OR 3 year Bachelor’s by itself provided the degree is at least 120 credits and the degree has been earned in Division I and the institution is accredited by the National Assessment and Accreditation Council (NAAC) with an institutional score of 'A' or better

- Completed Undergraduate-Level Mathematics Coursework and be familiar with Computer Programming (Candidates without coursework in Mathematics would be considered on a case-to-case basis based on profile and entrance test scores).

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Certification

Master of Science in Data Science from University of Arizona
Complete all the courses successfully to obtain this recognition from the University of Arizona.
  • Earn a Master of Science in Data Science degree.
  • Get University of Arizona alumni status.
  • Widely recognized and valued programme in Data Science.
  • Get ID cards (chargeable) and email IDs from University of Arizona.
  • A minimum of 70% score (C grade) is required to pass each course. A minimum of 3.0 CGPA is required to pass the entire program.

Programming Languages and Tools Covered

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World-Class Faculty

Learn from leading Data Science faculty and industry leaders

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Dr. Venkatesh Sunkad

President, Professor
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With over 2 decades of experience, Dr. Venkatesh has extensive hands-on technical and management experience in IoT and Network Analytics. He managed a team of highly skilled software architects, networking architects, software engineers and project managers in multiple countries.
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Dr. Saunak Dutta

Assistant Professor
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Saunak has completed his PhD from IIT Hyderabad on Theoretical and Phenomenological Aspects of High Energy Particle Physics in the Colliders. He also holds a 10 month experience of Post Doctoral Research at the Department of Physics and Astrophysics, University of Delhi.
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Behzad Ahmadi

Data Scientist, Walmart Labs
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He has extensive experience as a Data Scientist and an ML practitioner. He has worked as an Adjunct Professor in his alma mater, which is the New Jersey Institute of Technology, as well as at North Eastern University.
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S. Anand

CEO
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A gold medalist from IIM Bangalore, an alumnus of IIT Madras and London Business School, Anand is among the top 10 data scientists in India.
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Dr. Shonraj Ballae Ganeshrao

Associate Professor
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Dr. Shonraj is an Associate Professor at INSOFE. Before joining INSOFE, he was heading the Optometry Department at Manipal Academy of Higher Education. He started his carrier as a Clinical optometrist at Sankara Nethralaya and then moved on to do his Ph.D. at The University of Melbourne. His Ph.D. work was on developing smart Bayesian-based algorithms to check the peripheral field of vision.
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Shiva Prasad Koyyada (Ph.D.)

Associate Professor, Associate Dean for Business Programs
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Having 10 + years of experience in academics and consulting together working as a data scientist in one of the topmost data science firm(INSOFE) where we apply all our learnings in AI&MachineLearning such as Supervised,(Linear, Logistic, DecisionTrees, KNN, SVM, Neural nets etc..) Unsupervised learning methods in R and python.
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Georgios Ouzounis

Professor, Deep Learning, Kauno Kolegija
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Georgios has twenty-two years of experience in scientific research, engineering, and entrepreneurship. He is currently spending his time as a Professor of Deep Learning at Kaunas University of Applied Sciences.
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Shailesh Kumar

Chief Data Scientist, CoE AI/ML
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He comes with over twenty years of experience in building and innovating AI/ML solutions across a wide range of industries with top brands like Google, Fico, and Ola
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Dr. L. Srinivasa Varadharajan

Provost- Engineering Programs, Professor
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With over 2 decades of experience in teaching and research in healthcare including human vision and related fields, Dr. Varadharajan has a track record of excellence in guiding both undergraduate and postgraduate students in research projects leading to peer-reviewed publications.
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Dr. Anand Jayaraman

Professor - Supply Chain, Machine Learning & Statistical Modeling
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Dr. Anand is an experienced Quant Trader and Portfolio Manager who has 12 years’ experience in BFSI and 6 years of teaching experience in prominent US universities like Pennsylvania State University and Duke University.
Syllabus
Best-in-class content by leading faculty and industry leaders in the form of videos, cases and projects.

25+

Industry-Driven Case Studies

30+

Live Sessions

10W

Capstone Projects

1350

Hours of Learning

  • Fundamentals of Calculus and Probability
  • Basics of R Programming
  • Basics of Python Programming
  • Tools Covered: Python and R Programming
  • Functional Programming in Python
  • Data Structures and Algorithms
  • Database Design and Introduction to MySQL
  • Tableau
  • Essential Data Science Tools: Github and Jekyll
  • Tools Covered: Python, MySQL, Tableau, Github and Jekyll
  • Libraries for Data Science: Numpy, Pandas
  • Advance Visualisation
  • Exploratory Data Analysis
  • Inferencing from Data with R
  • Hypothesis Testing with R
  • Tools Covered: R programming, Numpy, Pandas, matplotlib, seaborn and ggplot
  • Building Linear Regression Models from Scratch
  • Linear Regression practical applications
  • Logistic Regression
  • Decision Trees
  • Random Forest
  • PCA
  • Clustering
  • Bagging, Boosting and Regularization
  • Model Selection and Feature Engineering
  • Tools Covered: Python, sklearn and matplotlib
  • Advance SQL
  • Introduction to NoSQL
  • Tools Covered: MySQL, NoSQL and MongoDB
  • Introduction to Cloud
  • Elastic Provision Services of Cloud and Setting up Cloud
  • Introduction to HDFS
  • Hive Querying
  • Introduction to Spark
  • Handling Big data with Spark
  • SparkML
  • Tools Covered: AWS, Hive, Apache Spark, SparkML, Spark Streaming and Pyspark
  • Best practices for Effective Communication
  • Capstone Project
  • Introduction to Neural Networks
  • CNN
  • RNN
  • Computer Vision
  • Tools Covered: Python, OpenCV, TensorFlow, YOLO, SSD and MaskRCNN
  • Lexical Processing
  • Syntactic Processing
  • Semantic Processing
  • Introduction to Attention Mechanism
  • Advanced Language Models: BERT, GPT
  • Tools Covered: Python, NLTK, Spacy, BERT, GPT and TensorFlow
  • Structured Problem Solving
  • Data Storytelling
  • Framework to DS/ML solution building strategy
  • Building Data Architecture
  • Introduction to MLOps
  • Introduction to Data and Model Lifecycle
  • Tools Covered: REST API, Python, TensorFlow, Kubeflow, Flask, Kubernetes and Docker
  • Ethical Foundations
  • Ethics in Data
  • Ethics in Modelling
  • Capstone Project - 2
Still have questions? Get in touch with us!

Industry Projects

Learn through real-life industry projects sponsored by top companies across industries

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Credit Card Fraud Detection

Predict fraudulent credit card transactions with the help of machine learning models.

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Style transfer using GAN

Use a variant of GANs i.e. CycleGAN, to translate the style of one MRI image into another.

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Sales forecasting

Analyse the sales data for a retail giant and forecast sales using deep neural networks.

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Eye for Blind

Predict fraudulent credit card transactions with the help of machine learning models.

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Sentiment Based Product Recommendation System

Perform sentiment analysis on the reviews of the products and provide recommendations

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News Recommendation System

Recommend news articles to users based on their preferences

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Stack Overflow Case Study

Perform exploratory data analysis using cloud services on stack overflow data set.

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Uber Case Study

Analyse the Uber dataset to understand the demand and supply of cab services.

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Data Warehousing Case Study

You will work on telecom industry data and learn ETL and Data ingestion, Sqoop, Hive, Oozie.

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Real Time Twitter HashTag Analysis, using Spark Streaming

You will perform the Twitter hashtag analysis on real-time data using Spark Streaming.

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Recommendation System, using ALS (Alternating Least Squares)

Recommendation system is built using ALS algorithm in Spark.

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Market Basket Analysis, using Apriori Algorithm

You will implement market basket analysis using Spark with the help of Apriori algorithm.

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NYC Taxi Fare Prediction

Build a pricing model to predict the fare of a taxi ride using the set of attributes.

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Telecom Churn Prediction

Classification model is built to predict the churning of the customer from telecom network.

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Recommendation System using PCA and KNN

Implemented the movie recommendation system by reducing the dimensionality using PCA algorithm.

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E-Commerce Assignment

Analyse a clickstream dataset of a cosmetics store using Hive and extract valuable insights.

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Speech Recognition

Learn Google speech-to-text and make a model using deep learning.

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Gesture Recognition

Build a gesture recognition model for a Smart-TV, using a 3D convolution Network.

*Projects can change based on emerging technologies and industry needs.
The upGrad-INSOFE Advantage
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Industry Mentors

  • Receive unparalleled guidance from industry mentors, teaching assistants and graders.
  • Receive one-on-one feedback on submissions and personalised feedbacks on improvement

Student Support Team

  • Student Support is available 7 days a week, 24*7
  • You can write to us via [email protected] or for urgent queries use the" Talk to Us" option on the learn platform.
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Q&A Forum

  • Timely doubt resolution by Industry experts and peers
  • 100% Expert-verified responses to ensure quality learning

Expert Feedback

  • Personalised expert feedback on assignments and projects
  • Regular live sessions by experts to clarify concept related doubts
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Industry Networking

  • Live sessions by experts on various industry topics
  • One-on-one discussion and feedback sessions with industry mentors

Admission Process

Step 1

Score 50% on the INSOFE Entrance Exam

Step 2

Excel in the interview round

Step 3

Submit a Statement of Purpose, English Language Proficiency scores, and 2 recommendation letters

Step 4

Receive admission letter to the MS in Data Science from UoA

Over 500 Careers Transformed
Learn more about successful career transitions in this program

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Average Salary Hike

₹1.23 Cr

Highest Salary Offered

500+

Career Transitions

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Atul Agarwal

Mumbai, 2 Years experience

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Average Salary Hike

The curriculum and program is very structured and easy to consume. The mock calls and encouraging words from the CEO before my interview were extremely encouraging.

Research Assistant

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News Analyst

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Moulik Srivastava

Bengaluru, 5 Years experience

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inc. in salary

The program has been absolutely fantastic. The mentorship through industry veterans, BaseCamps, and student mentors makes the program extremely engaging. I would definitely endorse the program for its rich content and comprehensive approach to Data Science.

Business Systems Analyst

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Business Analyst

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Bhagvathi

Bengaluru, 1 Year experience

The program's content was so well structured that it helped me grasp concepts very new to me. I was able to secure a job at Kantar Analytics through upGrad's placement drive.

Fresher

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Data Analyst

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Sowjanya Vijaynagar

Bengaluru, 5 Years experience

The mock interviews at upGrad was very helpful since it was catered to the kind of role I was looking to get into. The feedback was extremely useful and also helped me gain confidence before the main interview.

Data Consultant

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Business Analyst

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Atul Agarwal

Mumbai, 2 Years experience

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Learning with upGrad was like going back to University for me. Their career support and mentorship calls really helped me switch to a career in the field of Data Science.

Software Engineer

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Data Analyst

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Personalised Industry Session

Sessions by an industry expert for a small group of 10-12 learners with similar profiles to discuss real life applications of concepts and personalised coaching

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High Performance Coaching (1:1)

Get a dedicated career coach to help you stay on track to achieve your career goals, coach you on your profile, and support you in your career journey.

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Career Mentorship Sessions (1:1)

Get personalised career landscaping from experts to chart out best opportunities

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Interview Preparation

Support in polishing your hard skills and soft skills for interview preparation

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Program Fees - Indian Residents

INR 10,00,000 (Incl. GST)*

*100% education loan assistance
The credit facility is provided by a third party credit facility provider and any arrangement with such third party is outside upGrad-Insofe purview.

How You Benefit From This Program

  • Masters in Data Science from University of Arizona
  • Get Masters in Data Science without quitting your job
  • Career Acceleration in your current role
  • Career Transition with upto average 57% salary hike
  • Stepping Stone into the field of Data Science
  • Cutting-edge curriculum designed by industry experts

Empowering learners of tomorrow

Our Learners Work At

Top companies from all around the world have recruited upGrad-Insofe
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Disclaimer

  • - *Price after exclusive upGrad discounts. Please get in touch for further details.
  • - *Exemption for students with a bachelor's degree from an institution where medium of instruction was English. Subject to verification.
  • - *Exemption for students with a bachelor's degree from an institution where medium of instruction was English. Subject to verification.
  • - Based on upGrad NPS response data obtained from ~1252 learners, between 2nd Oct'21 to 18th Oct'21 for upGrad courses*. The review was performed by Deloitte Touche Tohmatsu India LLP. upGrad is a platform to facilitate program delivery by educational institutions and is not a college or a university itself. *programs.upgrad.com/disclaimer_courselist
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Refer someone you know and receive Gift vouchers worth INR 3,000!*

*Referral offer is valid only on the Masters in Data Science Program
Frequently Asked Questions

The Master's degree is an engaging yet rigorous 24-month online program designed specifically for working professionals to develop practical knowledge and skills, establish a professional network, and accelerate entry into data science careers. The certification is awarded by University of Arizona.

Expect to carry out several industry-relevant projects simulated as per the actual workplace, making you a skilled data science professional at par with leading industry standards.

The program is NOT going to be easy. It will be requiring at least 12-15 hours of time commitment per week, applying new concepts and executing industry relevant projects.

The content will be a mix of interactive lectures from industry leaders as well as world-renowned faculty. Additionally, the program comprises live lectures or hangout sessions dedicated to solving your academic queries and reinforcing learning.

Post successful completion of the program, a Masters in Data Science would be granted from the University of Arizona.

At least 12-15 hours per week of time commitment is expected to be able to graduate from the program.

Peer-to-peer discussion forum where you can post your queries and your peers/faculty/teaching assistants answer your queries within a day. Regular Q&A sessions with faculty to get clarification on conceptual doubts.

The program is priced at INR 10, 00, 000 (including taxes).

  1. You can claim a refund for the amount paid towards the Program at any time, before the Program Start Date, by visiting www.upgrad.com and submitting your refund form via the "My Application" section under your profile. You can request your Admissions Counselor to help you in applying and withdrawing for a refund by sending them an email with reasons listed. Processing fee of INR 10,000/- will be levied. If less than INR 10,000/- have been paid in total, you will not be eligible for any refund in such a case.
  2. If the provisional admission to the University of Arizona is not confirmed by the University of Arizona, learners shall be eligible for a complete refund.
  3. Learner shall not be eligible for any refund under any circumstances if any such refund requests are raised post Batch Start Date and the learner will continue to pay the EMI for the loan (if applicable) and such loan cannot be canceled.
  4. In case of a refund, the learner will be solely responsible for any cancellation of the loan, including but not limited to applicable loan cancellation charges levied on the total canceled loan amount.

No cost EMI is available on credit cards from all major banks (American Express, Bank of Baroda, HDFC Bank, ICICI Bank, IndusInd Bank, Kotak Mahindra Bank, RBL Bank, Standard Chartered, Axis Bank, Yes Bank).

If you are availing 0% credit card EMI, upGrad will not charge any processing fees or down payment for these transactions. Your bank may levy GST or other taxes on the interest component of the EMI.

Certain banks charge nominal processing fees between INR 99 - 500 on 0% Credit Card EMI transaction. If charged will be billed in the first repayment installment.

Only the Indian bank Credit cards can be used. But you can pay the amount using the Credit card option in one shot / part payments and later you can convert into EMI from your respective bank. The tenures and interest charged will depend on your bank. upGrad will not charge any processing fees or down payment for these transactions, this will be purely between you and your bank.

Yes, there will be additional charges to the extent of interest paid by the upGrad to the bank, you will be refunded only Principal amount, i.e. the amount actually deducted/blocked from your card. This deduction will be in addition to the amount mentioned in the refund policy shared with your offer letter.

You can pay the amount using the Credit card option in one shot / part payments and later you can convert into EMI from your respective bank. The tenures and interest charged will depend on your bank. upGrad will not charge any processing fees or down payment for these transactions.

If you like finding meaningful insights from data and if you get excited by the prospect of informing business decisions through analysis and have an analytical bend of mind, then this program is meant for you. As long as you are able to clear the selection test (or are exempt) and are excited about the transition to Data Science, this program is meant for you.

Absolutely! Data Science is becoming a necessity for all industries and is no more a choice. Hence, there is a critical demand for quality data professionals and because the supply is constrained, this is one of the most lucrative career options across industries.

 The admission process is as following:

Step 1: Score 50% on the INSOFE 

Step 2: Excel in the interview round

Step 3: Submit a Statement of Purpose, English Language Proficiency scores, and recommendation letters

Step 4: Receive admission to the MS in Data Science

Minimum 16 years education (with minimum 70% score | medium of instruction - English) from an accredited college or university.

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