60% Online and 40% ClassroomClass structure
Recommended 12-15 hrs/week-- Months
Start DateComing Soon
Alumni StatusUniversity of Arizona
by U.S. News and World reportTop 100 (Best Global Universities in the world)

    About the Programme

    This full-time master’s program is offered in a hybrid format where students spend 50% of their time in the classroom and 50% of their time studying online. We believe the level of applied knowledge is imparted better in a classroom environment, hence the hands-on practical sessions are done in a classroom.

    Hybrid classroom sessions to accommodate different work commitments​

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

    100% career support by upGrad-INSOFE​

    Program Overview

    Key Highlights

    360 Degree Career Support
    360 Degree Career Support
    Designed for both freshers and working professionals​
    Designed for both freshers and working professionals​
    Learn from world-class faculty​
    Learn from world-class faculty​
    Job Assistance with Top Firms
    Job Assistance with Top Firms
    1350 Hours of Learning
    1350 Hours of Learning
    30+ Live Learning Sessions
    30+ Live Learning Sessions
    Global Access to Job Opportunities
    Global Access to Job Opportunities
    Just-in-time Interviews
    Just-in-time Interviews
    Masterclasses by industry experts
    Masterclasses by industry experts
    Support available all days 9 AM - 9 PM IST for queries
    Support available all days 9 AM - 9 PM IST for queries
    Resume Tool & Review
    Resume Tool & Review
    25+ industry-driven case studies
    25+ industry-driven case studies
    Soft Skills Training
    Soft Skills Training

    "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. 

    download Syllabus
    Top Skills You Will Learn
    Python, BD processing using Spark, Deploy ML Models, Superviview more
    Job Opportunities
    Big Data Analyst, Data Engineer, Data Scientist, Machine Leaview more
    Who Is This Programme For?
    Managers and Aspiring Managers, MBA Graduates, Engineers, Prview more
    Minimum Eligibility
    Minimum 16 years education (with minimum 70% score | medium view more
    Master of Science in Data Science from University of Arizona
    Complete all the courses successfully to obtain this recognition from the University of Arizona.
    Master of Science in Data Science from University of Arizona
    Click to zoom
    • 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

    Global Lecturers

    Learn from leading Data Science faculty and industry leaders

    Syllabus

    Best-in-class content by leading faculty and industry leaders in the form of videos, cases and projects, assignments and live sessions
    Download Brochure
    25+
    Industry-Driven Case Studies
    30+
    Live Sessions
    10 w
    Capstone Projects
    1350
    Hours of Learning

    Pre Course Requisites

    3 Weeks
    • Fundamentals of Calculus and Probability
    • Basics of R Programming
    • Basics of Python Programming
    • Tools Covered: Python and R Programming

    Course 1 - Data Analysis and Visualization

    10 Weeks
    • 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

    Course 2 - Data Mining and Discovery

    10 Weeks
    • 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

    Course 3 - Introduction to Machine Learning

    11 Weeks
    • 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

    Course 4 - Data Base Development and Management

    9 Weeks
    • Advance SQL
    • Introduction to NoSQL
    • Tools Covered: MySQL, NoSQL and MongoDB

    Course 5 - Data Warehousing and Analytics in the Cloud

    10 Weeks
    • 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

    Capstone Project - 1

    5 Weeks
    • Best practices for Effective Communication
    • Capstone Project

    Course 6 - Neural Networks

    10 Weeks
    • Introduction to Neural Networks
    • CNN
    • RNN
    • Computer Vision
    • Tools Covered: Python, OpenCV, TensorFlow, YOLO, SSD and MaskRCNN

    Course 7 - Applied Natural Language Processing

    10 Weeks
    • Lexical Processing
    • Syntactic Processing
    • Semantic Processing
    • Introduction to Attention Mechanism
    • Advanced Language Models: BERT, GPT
    • Tools Covered: Python, NLTK, Spacy, BERT, GPT and TensorFlow

    Course 8 - Managing the Digital Information Environment

    10 Weeks
    • 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

    Course 9 - Ethical Issues in Information

    9 Weeks
    • Ethical Foundations
    • Ethics in Data
    • Ethics in Modelling

    Capstone Project - 2

    5 Weeks
    • Capstone Project - 2

    Industry Projects

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

    The upGrad-Insofe Advantage

    benefits

    Learning Support

    Learning Support
    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 studentsupport@upgrad.com or for urgent queries use the" Talk to Us" option on the learn platform.
    benefits

    Doubt Resolution

    Doubt Resolution
    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
    benefits

    Networking

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

    Admission Process

    Over 500 Careers Transformed

    Program Fees- Indian Residents

    ₹ NaN (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's purview.

    Empowering learners of tomorrow

    Our Learners Work At

    Top companies from all around the world have recruited upGrad alumni

    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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    Frequently Asked Questions

    Course Curriculum

    What is the Master's in Data Science with upGrad?

    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.

    What should I expect from the Master's Degree in Data Science?

    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.

    What should I NOT expect from the Master's Degree in Data Science?

    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.

    What type of learning experience should I expect?

    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. 

    Is any certification granted at the end of the program?

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

    Time Commitment

    What is the time commitment expected for the program?

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

    Career Prospects and Support

    How will my doubts/questions be addressed in an online 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.

    Refund policy/Financials

    What is the program fee for the Master's Degree in Data Science?

    The program is priced at INR 8,85,000 (including taxes).

    Is there a refund policy for this program?

    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. 

    Which banks allow using 0% Credit card EMI or Credit card EMI?

    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).

    Will I have to pay any extra amount for the EMI transaction?

    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.

    Are there any fees or down payment?

    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.

    Can I use my International credit card for 0% credit EMI or Credit Card EMI?

    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.

    Are there any charges in case I opt for cancellation/refund from the course after paying balance with no cost EMI?

    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.

    How can I opt for Credit card EMI if my bank is not listed in the 0% Credit card EMI or Credit card EMI?

    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.

    Selection Criteria

    How do I know if the program is right for me?

    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.

    My current role does not include exposure to data. Does it make sense for me to opt for this program?

    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.​

    What is the application process for the program and what are the timelines?

     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

    Is there any minimum educational qualification required to take this program?

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

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