- Get access to the complete digital library of LJMU to research & write your dissertation
- Complete all courses to achieve this prestigious M.Sc. Degree from LJMU, UK to jump-start your career in Data Science
- Earn a Master's degree which is recognized by WES, at 1/10th the cost of an offline program
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- Data Science and Analytics
- Master of Science in Data Science
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About LJMU's Masters In Data Science Program
Course Snapshot
-
5
Unique Specializations
-
14+
Tools & Languages
-
25+
Industry Case Studies & Capstone Project
- Complimentary Python Programming Bootcamp
- WES recognised Masters Degree in Data Science
- Fortnightly Group Mentorship Sessions with Industry Experts
- IIIT Bangalore & LJMU Alumni Status
- World Class Faculty from IIITB and LJMU
Key Highlights Of LJMU's MS In Data Science
What is this course about?
-
Key Highlights
-
Specializations
-
Top Subjects You Will Learn
-
Career Paths
-
Student Support
Key Highlights
- 6 Months - Masters Project / Thesis
- Career Essential Soft Skills
- World Class Faculty from IIITB and LJMU
- 85% Recorded + 15% Live Sessions
- Weekly Live Sessions with Industry Experts & Faculty
- Dual Alumni Status - IIITB and LJMU
- Career Coaching & Mentoring Sessions
- Global Networking Opportunities
- 1 week LJMU on campus visit**
5 Unique Specializations to choose from
- Data Analytics
- Business Analytics
- Deep Learning
- Natural Language Processing
- Data Engineering
Top Subjects You Will Learn
- Statistics, Predictive Analytics, Exploratory Data Analysis
- Machine Learning, Deep Learning
- Data Visualization, Big Data Analytics, Data Engineering
- Python, Tableau, MySQL, Advanced Excel etc.
The program prepares you for several in-demand data roles
- Data Analyst, Sr. Data Analyst, Data Scientist, Sr. Data Scientist
- Product Analyst, Business Analyst, Finance Analyst, Operations Analyst, Marketing Analyst, Risk Analyst, HR Analyst, Data Driven Managers
- Data Engineer, Machine Learning Engineer
Student Support
- A dedicated program coordinator
- 24/7 support to answer all your queries! intstudentsupport@upgrad.com
- Centralised WhatsApp channels for queries
Programming Languages and Tools Covered
About LJMU's Master's In Data Science Program
The New Learning Experience
About the programme
5 Unique Specializations
Choose any one of 5 in-demand specialisations to pursue as per your career aspirations in this Master of Science in Data Science Program form Liverpool John Moores University.
Choose any one of 5 in-demand specialisations to pursue as per your career aspirations in this Master of Science in Data Science Program form Liverpool John Moores University.
Read MoreDedicated Career Assistance
Be one step ahead with access to 1:1 career counseling sessions and mock interviews with hiring managers.
Be one step ahead with access to 1:1 career counseling sessions and mock interviews with hiring managers.
Read MoreStudent Support
Get access to dedicated student support by writing to us at studentsupport@upgrad.com or by using the "talk to us" option on our learning platform for urgent queries.
Get access to dedicated student support by writing to us at studentsupport@upgrad.com or by using the "talk to us" option on our learning platform for urgent queries.
Read MoreMaster's Degree Certificate In Data Science, LJMU
Earn valuable Credentials & Recognition
Finish your course to obtain a WES recognised MS in Data Science degree from Liverpool John Moores University
Master of Science in Data Science
- Get access to the complete digital library of LJMU to research & write your dissertation
- Complete all courses to achieve this prestigious M.Sc. Degree from LJMU, UK to jump-start your career in Data Science
- Earn a Master's degree which is recognized by WES, at 1/10th the cost of an offline program
Explore Our Learning Platform
Learn on an AI-powered & personalised platform with best-in-class
content, live sessions & mentoring from leading industry experts.
LJMU's MS In Data Science Course Syllabus
What will you learn?
Best-in-class content by leading faculty and industry leaders in the form of videos, cases and projects, assignments and live sessions
Course 1 - Data Toolkit
- 13 weeks
Topics (11)
- Introduction to Python
- Programming in Python
- Python for Data Science
- Data Visualization in Python
- Exploratory Data Analysis
- Credit EDA Case Study
- Inferential Statistics
- Hypothesis Testing
- Data Analysis using SQL
- Advaced SQL & Best Practices
- SQL Assignment: RSVP Movies
Course 2: Machine Learning - I
- 10 Weeks
Topics (11)
- Linear Regression - I
- Linear Regression - II + Gradient Descent for SLR
- Linear Regression Assignment
- Logistic Regression - I
- Logistic Regression - II
- Classification using Decision Trees
- Unsupervised Learning: Clustering
- Basics of NLP and Lexical Processing
- Business Problem Solving + Intro to GIT and GITHUB
- Case Study: Lead Scoring
- Buffer
Specialisation - Data Analytics
- 29 Weeks
Topics (18)
- Data Modelling
- Advanced SQL Programming
- Introduction to Cloud and AWS
- Analytics at Large Scale in Spark - I
- Analytics at Large Scale in Spark - II
- Big Data Case Study
- Basic Viz. using Tableau
- Advanced Excel
- Data Analysis and Visualisation in PowerBI
- Analytical Thinking and Structured Problem Solving using Frameworks
- Data Storytelling
- Airbnb Case Study
- Data Structures and Algorithms
- Searching & Sorting
- Algorithm Analysis and Recursion
- Advanced Database Programming using Pandas
- SQL & Python Lab
- Capstone
Specialisation - Business Analytics
- 29 Weeks
Topics (16)
- Bagging & Random Forests
- Model Selection - I
- Model Selection - II
- Time Series Forecasting - I
- Time Series Forecasting - II
- Model Selection Case Study
- Basic Viz. using Tableau
- Advanced Excel
- Data Analysis and Visualisation in PowerBI
- Analytical Thinking and Structured Problem Solving using Frameworks
- Data Storytelling
- Airbnb Case Study
- Product Development using OpenAI APIs, Fine Tuning using STaR technique in Python
- Integrating speech using Whisper API and application deployment using Flask
- Interview Gynie AI: Chatbot Development Project
- Capstone
Specialisation - Natural Language Processing
- 29 Weeks
Topics (16)
- Bagging & Random Forests
- Model Selection - I
- Model Selection - II
- Time Series Forecasting - I
- Time Series Forecasting - II
- Model Selection Case Study
- Basic Viz. using Tableau
- Advanced Excel
- Data Analysis and Visualisation in PowerBI
- Analytical Thinking and Structured Problem Solving using Frameworks
- Data Storytelling
- Airbnb Case Study
- Product Development using OpenAI APIs, Fine Tuning using STaR technique in Python
- Integrating speech using Whisper API and application deployment using Flask
- Interview Gynie AI: Chatbot Development Project
- Capstone
Specialization- Deep Learning
- 29 Weeks
Topics (16)
- Bagging & Random Forest
- Boosting
- Model Selection
- Principal Component Analysis
- Advanced Regression + Time Series Forecasting (Optional)
- Advanced ML case Stuy
- Introduction to Neural Networks and ANN
- Backpropogation & Hyperparameter Tuning in Neural Networks
- Introduction to Convolutional Neural Networks
- CNN Architectures and Industry Applications + Recurrent Neural Networks (Optional)
- Applications of DL in CV: Object Detection Image Segmentation (Optional)
- Gesture Recognition Case Study
- Product Development using OpenAI APIs, Fine Tuning using STaR technique in Python
- Integrating speech using Whisper API and application deployment using Flask
- Interview Gynie AI: Chatbot Development Project
- Capstone
Specialisation - Data Engineering
- 29 Weeks
Topics (16)
- Data Management and Relational Database Modelling
- Introduction to Cloud and AWS Setup
- Introduction to Hadoop and MapReduce Programming
- NoSQL Databases and Apache HBase
- Data Ingestion with Apache Sqoop and Apache Flume
- Map reduce Programming Assignment
- Hive and Quering + Optional Assignment
- Introduction to Apache Spark+ Optional Assignment
- Amazon Redshift
- ETL Project
- Optimizing Spark for Large scale processing
- Real-Time Data Streaming with Apache Kafka
- Building Automated Data Pipelines with Airflow
- Analytics using PySpark+ Optional Assignment
- Retail Project
- Capstone
Research Methodologies
- 10 Weeks
Topics (6)
- Introduction to Research and Research Process
- Research Design
- Literature Reviewing
- Research Project Management
- Report Writing and Presentation Skills
- Scientific Ethics
Master's Dissertation
- 14 Weeks
Topics (6)
- Investigate a diagnosis of eye diseases using imaging ophthalmic data
- Structure medical images with information geometry
- Using Social media feed to place tweets regarding natural disasters on a map
- Preventing credit card fraud through pattern recognition
- Developing a recommender system for a Media giant
- Risk modelling for Financial activities and Investment Banking
MS In Data Science Specialisations
Customize your Learning
Select a specialisation that aligns with your interests and career goals
Data Analytics
- 29 Weeks
Topics (18)
- Data Modelling
- Advanced SQL Programming
- Introduction to Cloud and AWS
- Analytics at Large Scale in Spark - I
- Analytics at Large Scale in Spark - II
- Big Data Case Study
- Basic Viz. using Tableau
- Advanced Excel
- Data Analysis and Visualisation in PowerBI
- Analytical Thinking and Structured Problem Solving using Frameworks
- Data Storytelling
- Airbnb Case Study
- Data Structures and Algorithms
- Searching & Sorting
- Algorithm Analysis and Recursion
- Advanced Database Programming using Pandas
- SQL & Python Lab
- Capstone
Business Analytics
- 29 Weeks
Topics (16)
- Bagging & Random Forests
- Model Selection - I
- Model Selection - II
- Time Series Forecasting - I
- Time Series Forecasting - II
- Model Selection Case Study
- Basic Viz. using Tableau
- Advanced Excel
- Data Analysis and Visualisation in PowerBI
- Analytical Thinking and Structured Problem Solving using Frameworks
- Data Storytelling
- Airbnb Case Study
- Product Development using OpenAI APIs, Fine Tuning using STaR technique in Python
- Integrating speech using Whisper API and application deployment using Flask
- Interview Gynie AI: Chatbot Development Project
- Capstone
Deep Learning
- 29 Weeks
Topics (16)
- Bagging & Random Forest
- Boosting
- Model Selection
- PCA
- Advanced Regression + Time Series Forecasting (Optional)
- Advanced ML Case Study
- Introduction to Neural Networks and ANN
- Backpropogation & Hyperparameter Tuning in Neural Networks
- Introduction to Convolutional Neural Networks
- CNN Architectures and Industry Applications + Recurrent Neural Networks (Optional)
- Applications of DL in CV: Object Detection Image Segmentation (Optional)
- Gesture Recognition Case Study
- Product Development using OpenAI APIs, Fine Tuning using STaR technique in Python
- Integrating speech using Whisper API and application deployment using Flask
- Interview Gynie AI: Chatbot Development Project
- Capstone
Natural Language Processing
- 29 Weeks
Topics (16)
- Bagging & Random Forests
- Model Selection - I
- Model Selection - II
- Time Series Forecasting - I
- Time Series Forecasting - II
- Model Selection Case Study
- Basic Viz. using Tableau
- Advanced Excel
- Data Analysis and Visualisation in PowerBI
- Analytical Thinking and Structured Problem Solving using Frameworks
- Data Storytelling
- Airbnb Case Study
- Product Development using OpenAI APIs, Fine Tuning using STaR technique in Python
- Integrating speech using Whisper API and application deployment using Flask
- Interview Gynie AI: Chatbot Development Project
- Capstone
Data Engineering
- 29 Weeks
Topics (16)
- Data Management and Relational Database Modelling
- Introduction to Cloud and AWS Setup
- Introduction to Hadoop and MapReduce Programming
- NoSQL Databases and Apache HBase
- Data Ingestion with Apache Sqoop and Apache Flume
- MapReduce Programming Assignment
- Hive and Quering + Optional Assignment
- Introduction to Apache Spark+ Optional Assignment
- Amazon Redshift
- ETL Project
- Optimizing Spark for Large scale processing
- Real-Time Data Streaming with Apache Kafka
- Building Automated Data Pipelines with Airflow
- Analytics using PySpark+ Optional Assignment
- Retail Project
- Capstone
Masters In Science In Data Science Instructors
Whom will you learn from?
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6 Instructors
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10 Industry Experts
Dr. Gabriela Czanner
- Faculty - Engineering and Technology
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A Senior lecturer in Statistics and Data Science at Department of Applied Mathematics at LJMU. Her research focus is advanced statistics for decision support
A Senior lecturer in Statistics and Data Science at Department of Applied Mathematics at LJMU. Her research focus is advanced statistics for decision support
Read More
Prof. Dhiya Al-Jumeily
- Professor - Artificial Intelligence
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A gold medallist from IIM Bangalore, an alumnus of IIT Madras and London Business School, Anand is among the top 10 data scientists in India.
A gold medallist from IIM Bangalore, an alumnus of IIT Madras and London Business School, Anand is among the top 10 data scientists in India.
Read More
Chandrashekar Ramanathan
- Dean - Academics
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Prof. Chandrashekar has a Ph.D. from Mississippi State University and experience of over 10 years in several multinational organizations.
Prof. Chandrashekar has a Ph.D. from Mississippi State University and experience of over 10 years in several multinational organizations.
Read More
Tricha Anjali
- Ex-associate Dean
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Prof. Anjali has a Ph.D. from Georgia Tech as well as an integrated M.Tech. (EE) from IIT Bombay.
Prof. Anjali has a Ph.D. from Georgia Tech as well as an integrated M.Tech. (EE) from IIT Bombay.
Read More
Dr. Debabrata Das
- Director, IIITB
-
Dr. Debabrata Das is the Director of IIITB. He has received his Ph.D. from IIT-KGP. His main areas of research are IoT and Wireless Access Network.
Dr. Debabrata Das is the Director of IIITB. He has received his Ph.D. from IIT-KGP. His main areas of research are IoT and Wireless Access Network.
Read More
Prof. G. Srinivasaraghavan
- Professor
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Prof. Srinivasaraghavan has a Ph.D. in Computer Science from IIT Kanpur and 18 years of experience with Infosys Technologies.
Prof. Srinivasaraghavan has a Ph.D. in Computer Science from IIT Kanpur and 18 years of experience with Infosys Technologies.
Read More
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.
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.
Read More
Mirza Rahim Baig
- Lead Analyst
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Advanced analytics professional with 8+ years of experience as a consultant in the e-commerce and healthcare domains.
Advanced analytics professional with 8+ years of experience as a consultant in the e-commerce and healthcare domains.
Read More
Sajan Kedia
- Ex-Data Science Lead
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Sajan graduated from IIT, BHU and has tons of experience in Data Science, Big Data, Spark, Machine Learning and Natural Language Processing
Sajan graduated from IIT, BHU and has tons of experience in Data Science, Big Data, Spark, Machine Learning and Natural Language Processing
Read More
Rajesh Sabapathy
- Sr Director, Data Science
-
Rajesh has 10+ years of experience leading Data Science teams in various domains solving complex problems using Deep Learning & ML technique
Rajesh has 10+ years of experience leading Data Science teams in various domains solving complex problems using Deep Learning & ML technique
Read More
Lead Data Engineer
- Lead Data Engineer
-
Kautuk has 10+ years of experience working in Data Science. He is a seasoned professional in Big Data, AWS, Pyspark and other technologies
Kautuk has 10+ years of experience working in Data Science. He is a seasoned professional in Big Data, AWS, Pyspark and other technologies
Read More
Data Science Projects
Learn by Doing
Learn from leading Data Science faculty and industry leaders in this Masters (MS) in Data Science
-
10+ Industry projects to choose from
Credit EDA Assignment
In this assignment, you will work for a consumer finance company which specialises in lending various types of loans to urban customers and use EDA to analyse the patterns present in the data. This will ensure that the applicants are capable of repaying the loan and are not rejected.
In this assignment, you will work for a consumer finance company which specialises in lending various types of loans to urban customers and use EDA to analyse the patterns present in the data. This will ensure that the applicants are capable of repaying the loan and are not rejected.
Skills learned
- Data Cleaning
- Data Visualisation
- Data Analysis
- Data Interpretation
RSVP Case Study
In this assignment, you will work on a movies dataset using SQL to extract exciting insights about popular films and the factors that drive a film.
In this assignment, you will work on a movies dataset using SQL to extract exciting insights about popular films and the factors that drive a film.
Skills learned
- MySQL
- MySQL Queries
- Data Manipulation
- Data Analysis
Bike Sharing Assignment
Build a regression model to understand the factors on which the demand for bike sharing systems vary on and help a company optimise its revenue.
Build a regression model to understand the factors on which the demand for bike sharing systems vary on and help a company optimise its revenue.
Skills learned
- Linear Regression
- ML Modelling
- Model Evaluation
Lead Scoring Case Study
In this case study, the company requires you to build a machine learning classification model which will be able to use demographical and behavioural data of potential buyers, to identify the ones most likely to convert.
In this case study, the company requires you to build a machine learning classification model which will be able to use demographical and behavioural data of potential buyers, to identify the ones most likely to convert.
Skills learned
- Logistic Regression
- Decision Trees
- Classification
- ML Modelling
- Model Evaluation
- Business Problem Solving
Model Selection Case Study -Telecom Churn
Telecom companies often face the problem of churning customers due to the competitive nature of the industry. Help a telecom company identify customers that are likely to churn and make data-driven strategies to retain them from the perspective of a business analyst.
Telecom companies often face the problem of churning customers due to the competitive nature of the industry. Help a telecom company identify customers that are likely to churn and make data-driven strategies to retain them from the perspective of a business analyst.
Skills learned
- Logistic Regression
- Tree Models
- Model Selection
- Feature Engineering
- Classification
- ML Modelling
- Model Evaluation
- Business Problem Solving
Advanced ML Case Study - Telecom Churn
Telecom companies often face the problem of churning customers due to the competitive nature of the industry. Help a telecom company identify customers that are likely to churn and make data-driven strategies to retain them from the perspective of a data scientist.
Telecom companies often face the problem of churning customers due to the competitive nature of the industry. Help a telecom company identify customers that are likely to churn and make data-driven strategies to retain them from the perspective of a data scientist.
Skills learned
- Logistic Regression
- Tree Models
- Boosting
- Model Selection
- Regularization
- Feature Engineering
- Classification
- ML Modelling
- Model Evaluation
- Business Problem Solving
Syntactic Processing Assignment
Use the techniques such as POS tagging and Dependency parsing to extract information from unstructured text data.
Use the techniques such as POS tagging and Dependency parsing to extract information from unstructured text data.
Skills learned
- Natural Language Processing
- Lexical Processing, Regex
- POS Tagging
- Dependency Parsing
ETL Project
Make use of Sqoop, Redshift & Spark to design an ETL data pipeline.
Make use of Sqoop, Redshift & Spark to design an ETL data pipeline.
Skills learned
- AWS
- Sqoop
- Sqoop
- Spark
- ETL Pipeline
IPL Visualization Assignment
Analyse movie data from the past 100 years and find out various insights to determine what makes a movie do well. Use data manipulation, slicing, and various other dataframe operations to successfully find usable insights from the movies.
Analyse movie data from the past 100 years and find out various insights to determine what makes a movie do well. Use data manipulation, slicing, and various other dataframe operations to successfully find usable insights from the movies.
Skills learned
- Tableau/Power BI
- Data Processing
- Data Visualisation
- Data Analysis
- Dashboarding
- Data Storytelling
Advanced Regression
Build a regularized regression model to understand the most important variables to predict
Build a regularized regression model to understand the most important variables to predict
Skills learned
- ML Modeling
- Linear Regression
- ML Model Evaluation
MapReduce Programming Assignment
Practice MapReduce Programming on a Big Dataset.
Practice MapReduce Programming on a Big Dataset.
Skills learned
- AWS
- Hadoop
- MapReduce
- Mrjob
- Apache HBase
- SQL
Data Science Program Class Profile
Master of Science in Data Science
Our program caters to professionals from diverse backgrounds, creating a vibrant classroom environment with enriching discussions and interactions.
By Industry
By Work Experience
By Highest Qualification
By Degree Type
By Age
By Gender
GGU DBA Alumni Careers
upGrad Alumni Work At
How will upGrad support you?
Access the various career development support services offered by
upGrad to help you achieve your professional goals.
- Dedicated upGrad Buddy as your single POC for all queries
- In addition, Student Support Team is available 7 days a week, 24*7
- Email us on studentsupport@upgrad.com
- OR use the "Talk to Us" option on the Learn platform
- Live Discussion forum for peer to peer doubt resolution monitored by technical experts
- 1-1 Doubt solving sessions with Teaching Experts
- Informal peer groups on Whatsapp or Telegram for doubt solving
- Global batchmates & alumni: Our learners are from 85+ countries
- Networking webinars to interact with batchmates and alumni
- Online discussion forums for peer to peer interaction
- Learn & network with our industry experts, career coaches
- Informal peer groups: Our Learners form groups on Whatsapp for interaction & networking purpose
- High Performance Coaching (1:1) with a dedicated career coach to build your career path
- Career Webinars, where the industry leaders would guide you on job opportunities, career path in the field of Data Science
- Resume and Linkedin Profile Building to enhance your career
- Interview Preparation, with the help of industry experts and prep material
- Career Essential Soft Skills sessions to do well in interview, meetings, presentations
- Job Readiness Assessments to ensure our learners get job ready
- Interactive Live Sessions with leading industry experts covering curriculum + advanced topics
- Lab walkthroughs of industry-driven projects and case studies
- Live Sessions on Complimentary Python Boot Camp
Program Fees: AED 34,900
*(Optional) 1-week LJMU campus visit at an additional USD 2000 or equivalent local currency.
Data Science Course Eligibility And Admissions
How To Apply
The admissions process for Liverpool John Moore University's MS in Data Science is very easy, and can be done completely online
Bachelor’s Degree with minimum 50% or equivalent passing marks. No coding experience required.
Submit Your Application
Fill out an application giving your basic profile details
Fill out an application giving your basic profile details
Read MoreGive a selection test
Give a short 17 minutes aptitude test and get shortlisted
Give a short 17 minutes aptitude test and get shortlisted
Read MoreReserve your Seat & Begin the Prep Course
Reserve your seat by paying the deposit amount to enroll in the program. Begin with your Prep course and start your Data Science journey!
Reserve your seat by paying the deposit amount to enroll in the program. Begin with your Prep course and start your Data Science journey!
Read More
Refer someone you know and receive cash reimbursements of up to
!*
*More details under the referral policy under Support Section
Data Science Program Success Stories
What Our Learners Say
I am in love with upGrad
I wanted a course that would complement my existing skills and I’ve always loved programming, linear regression, predictive analysis etc. Additionally, I needed a low-cost master’s degree that was 100% online and of a high level. UpGrad met all of my requirements.
I wanted a course that would complement my existing skills and I’ve always loved programming, linear regression, predictive analysis etc. Additionally, I needed a low-cost master’s degree that was 100% online and of a high level. UpGrad met all of my requirements.
Read MoreMarcelo Gonçalves Silva
- Material Process Specialist, Apollo Tyres Ltd, United Kingdom
Choosing UpGrad has been a pivotal decision in my academic journey
The level of expertise, in-depth knowledge of the lectures, hands on practice session, the wider communication and interpersonal skills makes upGrad the number one choice.
The level of expertise, in-depth knowledge of the lectures, hands on practice session, the wider communication and interpersonal skills makes upGrad the number one choice.
Read MoreSheel Dwivedi
- Business Intelligence & Informatica Specialist, Ampega, Germany
You are provided with live interaction sessions on topics covered every week.
The course has helped me to understand the underlying theories of Machine and Deep Learning algorithms and made me capable of applying them effectively in my area of specialization by considering the respective algorithms' inner working principles.
The course has helped me to understand the underlying theories of Machine and Deep Learning algorithms and made me capable of applying them effectively in my area of specialization by considering the respective algorithms' inner working principles.
Read MoreAbdul Sathar
- Head - Product Development & Delivery, Computer & Systems Engineering Company, United Kingdom
You are provided with live interaction sessions on topics covered every week.
Learning experience was amazing because the course contents are more practical rather than just theoretical. upGrad is particularly good at Student support and motivation. You get a classroom learning experience in a completely virtual environment.
Learning experience was amazing because the course contents are more practical rather than just theoretical. upGrad is particularly good at Student support and motivation. You get a classroom learning experience in a completely virtual environment.
Read MoreSrinivasan CR
- Vice President - Data Science & Analytics at Redington Gulf FZE, United Arab Emirates
You are provided with live interaction sessions on topics covered every week.
We get a lot of support by mentors and module deadlines is something that will push us to complete the program in the given time. I am working on my masters at LJMU currently and hope I will get a transition within my organisation.
We get a lot of support by mentors and module deadlines is something that will push us to complete the program in the given time. I am working on my masters at LJMU currently and hope I will get a transition within my organisation.
Read MorePrasad Chandrakant Chandra Zende
- Data Scientist, Voestalpine BÖHLER Edelstahl GmbH & Co KG, Austria
You are provided with live interaction sessions on topics covered every week.
Thanks to upGrad, I was able to achieve my dream of completing my Masters in Data Science 20 years after completing my graduation.
Thanks to upGrad, I was able to achieve my dream of completing my Masters in Data Science 20 years after completing my graduation.
Read MoreVanishri Murali
- Project Manager, IBM India Private Limited, United States
You are provided with live interaction sessions on topics covered every week.
I was not very much convinced with the quality of learning imparted through the various part-time online courses. But the need for up-skilling was inevitable for me to sustain and grow in my career. Due to my professional as well as personal commitments, the only option was to make my learning and profession go hand in hand. With the support of upGrad, I have witnessed an exciting journey for the past 2 years upskilling myself with the latest technology and gaining my Masters in Data Science.
I was not very much convinced with the quality of learning imparted through the various part-time online courses. But the need for up-skilling was inevitable for me to sustain and grow in my career. Due to my professional as well as personal commitments, the only option was to make my learning and profession go hand in hand. With the support of upGrad, I have witnessed an exciting journey for the past 2 years upskilling myself with the latest technology and gaining my Masters in Data Science.
Read MoreGreenu Sharma
- Director, ImageVision
16 years experience
You are provided with live interaction sessions on topics covered every week.
Upgrad as expected was always there to support- From the Student mentor to the Thesis supervisor, both were having discussion with me at the oddest of hour ensuring I was never at a standstill. The SME sessions and the sessions with professors from LJMU always helped with new perspectives. As I look back, the otherwise hectic journey of upskilling was a smooth one.
Upgrad as expected was always there to support- From the Student mentor to the Thesis supervisor, both were having discussion with me at the oddest of hour ensuring I was never at a standstill. The SME sessions and the sessions with professors from LJMU always helped with new perspectives. As I look back, the otherwise hectic journey of upskilling was a smooth one.
Read MoreMaxim Rohit
- Data Scientist, Radamatic Solutions Pvt Ltd
12 years experience
You are provided with live interaction sessions on topics covered every week.
With a career spanning over 25 years, I took the plunge to become future ready with the Master’s degree program in Data Science from LJMU and upGrad. Since I have worked in the IT industry for most of my career but did my graduation in Mechanical Engineering, I was unable to find the right fit for a Master's program till I discovered upGrad. upGrad made my dream of pursuing a Master's come true.
With a career spanning over 25 years, I took the plunge to become future ready with the Master’s degree program in Data Science from LJMU and upGrad. Since I have worked in the IT industry for most of my career but did my graduation in Mechanical Engineering, I was unable to find the right fit for a Master's program till I discovered upGrad. upGrad made my dream of pursuing a Master's come true.
Read MorePradnya Paithankar
- Freelance Trainer and Consultant
27 years experience
You are provided with live interaction sessions on topics covered every week.
As a working professional, upGrad felt like a convenient option. I like that it's full-time and rigorous even though it’s online. The beginning of my course was super fun, exciting and challenging. It felt like taking a walk back to my school days. The program also offers a lot of hands-on experience.
As a working professional, upGrad felt like a convenient option. I like that it's full-time and rigorous even though it’s online. The beginning of my course was super fun, exciting and challenging. It felt like taking a walk back to my school days. The program also offers a lot of hands-on experience.
Read MoreSundara Rajan Jeyaraj
- Software Engineer, Cognizant, United States
Frequently Asked Questions
1. What is the Master's in Data Science with upGrad?
The Master's degree is an engaging yet rigorous 18-20 months blended 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 LJMU.
The Master's degree is an engaging yet rigorous 18-20 months blended 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 LJMU.
2. 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.
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.
3. 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 15 hours of time commitment per week, applying new concepts and executing industry relevant projects.
The program is NOT going to be easy. It will be requiring at least 15 hours of time commitment per week, applying new concepts and executing industry relevant projects.
4. Which topics are going to be covered as part of the program?
The program is designed for working professionals looking for a transition or growth into the data domain. Considering the requirements of different data roles in the industry, the curriculum is divided into 3 specializations. These three specializations will have a common curriculum running for approximately 5-6 months that everyone will go through after which they have to do two specialization courses and a capstone project in the remaining 6-7 months. The topics that are going to be covered as a part of the common curriculum and each of the five specializations are as follows:
Common Curriculum: Basics of SQL, Python, Statistics and EDA, Basic Machine Learning Models Deep Learning Specialization: Advanced Machine Learning, Neural Networks
Natural Language Processing Specialization: Advanced Machine Learning, Natural Language Processing
Business Analytics Specialization: Advanced Machine Learning, Storytelling and Advanced Business Problem Solving
Business Intelligence/Data Analytics: Advanced SQL and NoSQL Databases, Storytelling with Advanced Visualization
Deep Learning Specialization: Advanced Machine Learning, Natural Language Processing
Data Engineering: Data Modelling and Data Warehousing, Building Data Pipelines, Data Streaming, and Processing
This would be followed by 6 months Masters articulation from LJMU which would consist of Research Methodology and Masters Thesis under the supervision of subject matter expert.
The program is designed for working professionals looking for a transition or growth into the data domain. Considering the requirements of different data roles in the industry, the curriculum is divided into 3 specializations. These three specializations will have a common curriculum running for approximately 5-6 months that everyone will go through after which they have to do two specialization courses and a capstone project in the remaining 6-7 months. The topics that are going to be covered as a part of the common curriculum and each of the five specializations are as follows:
Common Curriculum: Basics of SQL, Python, Statistics and EDA, Basic Machine Learning Models Deep Learning Specialization: Advanced Machine Learning, Neural Networks
Natural Language Processing Specialization: Advanced Machine Learning, Natural Language Processing
Business Analytics Specialization: Advanced Machine Learning, Storytelling and Advanced Business Problem Solving
Business Intelligence/Data Analytics: Advanced SQL and NoSQL Databases, Storytelling with Advanced Visualization
Deep Learning Specialization: Advanced Machine Learning, Natural Language Processing
Data Engineering: Data Modelling and Data Warehousing, Building Data Pipelines, Data Streaming, and Processing
This would be followed by 6 months Masters articulation from LJMU which would consist of Research Methodology and Masters Thesis under the supervision of subject matter expert.
5. What type of learning experience should I expect?
6. Is any certification granted at the end of the program?
7. When will I have to choose my specialization track?
8. How do I know which specialization is best for me?
When you’re nearing the end of your common curriculum, upGrad will provide you with a recommendation best suited for you based on your background. The following mapping should give you an idea about the specialization best suited for you although the final upGrad recommendation would come from a much more exhaustive rule engine.
Deep Learning: Engineers, Software and IT Professionals
Natural Language Processing: Engineers, Software and IT Professionals
Business Intelligence/ Data Analytics: Engineers, Marketing and Sales Professionals, Freshers
Business Analytics: Engineers, Managers, Marketing and Sales Professionals, Domain Expert
Data Engineering: Software and IT Professionals
When you’re nearing the end of your common curriculum, upGrad will provide you with a recommendation best suited for you based on your background. The following mapping should give you an idea about the specialization best suited for you although the final upGrad recommendation would come from a much more exhaustive rule engine.
Deep Learning: Engineers, Software and IT Professionals
Natural Language Processing: Engineers, Software and IT Professionals
Business Intelligence/ Data Analytics: Engineers, Marketing and Sales Professionals, Freshers
Business Analytics: Engineers, Managers, Marketing and Sales Professionals, Domain Expert
Data Engineering: Software and IT Professionals
9. Do I have to choose the specialization recommended by upGrad?
10. What online resource does LJMU provide for students to confirm the validation of awards and what information can be found there regarding their collaborative partnerships?
11. Where can one access comprehensive details about the MSDS program at LJMU, including its structure and specific program requirements?
1. What is the time commitment expected for the program?
At least 15 hours per week of time commitment is expected to be able to graduate from the program.
At least 15 hours per week of time commitment is expected to be able to graduate from the program.
2. Will the five specialisations require different time commitments?
Each of the fice specialisations will have a common ~29-week curriculum in which the time commitment will be exactly the same.
Each of the fice specialisations will have a common ~29-week curriculum in which the time commitment will be exactly the same.
1. 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.
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.
2. My current role does not include exposure to data. Does it make sense for me to opt for this program?
3. What is the application process for the program and what are the timelines?
There are 3 simple steps in the Admission Process which is detailed below:
Step 1: Submit Your Application
Fill out an application giving your basic profile details
Step 2: Give a selection test
Give a short 17 minutes aptitude test and get shortlisted
Step 3: Block your Seat & Begin the Prep Course
Reserve your seat by paying the deposit amount to enroll in the program. Begin with your Prep course and start your Data Science journey!
There are 3 simple steps in the Admission Process which is detailed below:
Step 1: Submit Your Application
Fill out an application giving your basic profile details
Step 2: Give a selection test
Give a short 17 minutes aptitude test and get shortlisted
Step 3: Block your Seat & Begin the Prep Course
Reserve your seat by paying the deposit amount to enroll in the program. Begin with your Prep course and start your Data Science journey!
4. What is the selection process for this program?
upGrad, IIITB, LJMU, world-renowned faculty, and many industry leaders have committed a lot of time in conceptualising and creating this program to make sure that the learners can receive the best possible learning experience in data analytics. Hence, we want to make sure that the participants of this program also show a very high level of commitment and passion for Data Science.
The applicants will have to take a selection test designed to check their aptitude and quantitative abilities. The applicants can skip the test if they meet one of the following criteria:
- GRE score is greater than 300
- GMAT score is greater than 650
- CAT score is greater than 90 percentile
- GATE score is greater than 500
upGrad, IIITB, LJMU, world-renowned faculty, and many industry leaders have committed a lot of time in conceptualising and creating this program to make sure that the learners can receive the best possible learning experience in data analytics. Hence, we want to make sure that the participants of this program also show a very high level of commitment and passion for Data Science.
The applicants will have to take a selection test designed to check their aptitude and quantitative abilities. The applicants can skip the test if they meet one of the following criteria:
- GRE score is greater than 300
- GMAT score is greater than 650
- CAT score is greater than 90 percentile
- GATE score is greater than 500
5. Is there any minimum educational qualification required to take this program?
Bachelor’s Degree with minimum 50% or equivalent passing marks.
No coding experience required.
Bachelor’s Degree with minimum 50% or equivalent passing marks.
No coding experience required.
1. Is there any deferral or refund policy for this program?
Refund Policy:
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 Counsellor to help you in applying and withdrawing for a refund by sending them an email with reasons listed. There shall be no refund applicable once the program has started. This is applicable even for those students who could not complete their payment, and could not be enrolled in the batch opted for. However, the student can avail pre-deferral as per the policy defined below for the same.
2. Student must pay the full fee within seven (7) days of payment of the deposit amount or Batch Start Date, whichever is earlier; otherwise, the admission letter will be rescinded.
3. Request for refund as per point no. 1 of the refund policy must be sent via email in the prescribed refund request form. The refund will be processed within 30 working days of submitting the duly signed refund form, after being duly approved by the Academic Committee.
Refund Policy:
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 Counsellor to help you in applying and withdrawing for a refund by sending them an email with reasons listed. There shall be no refund applicable once the program has started. This is applicable even for those students who could not complete their payment, and could not be enrolled in the batch opted for. However, the student can avail pre-deferral as per the policy defined below for the same.
2. Student must pay the full fee within seven (7) days of payment of the deposit amount or Batch Start Date, whichever is earlier; otherwise, the admission letter will be rescinded.
3. Request for refund as per point no. 1 of the refund policy must be sent via email in the prescribed refund request form. The refund will be processed within 30 working days of submitting the duly signed refund form, after being duly approved by the Academic Committee.
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