WES Recognised

Master of Science in Data Science

Go the extra mile to become a data-driven leader. Learn from a world-class curriculum developed by leading faculty & Industry experts to earn a globally recognized Master of Science in Data Science from Liverpool John Moores University.

Type

Masters
Start Date

December 31, 2024
Duration

18-20 Months

dWeb_550X572_DS LJMU-fd61131879c840139975fd3fdd0b3700

Liverpool John Moores University

Recognised Masters Degree by WES &
Institute of Analytics (IOA)

About LJMU's Masters In Data Science Program

Course Snapshot

5
Unique Specializations
14+
Case Studies and Projects
500+
Hours of Learning

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

Complimentary Python Programming Bootcamp
Weekly Live Sessions with Industry Experts & Faculty
Fortnightly Group Mentorship with Industry Mentors
Global Networking Opportunities
1 week LJMU on campus visit**
Career Essential Soft Skills
High Performance Coaching (1:1)

5 Unique Specializations to choose from

Deep Learning
Natural Language Processing
Business Intelligence / Data Analytics
Business Analytics
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

Target Audience

Individuals with technical backgrounds.
Software Engineers, System Analysts, Database Administrators seeking advanced analytics.
Data Analysts, Data Scientists, ML Engineers who aspire to grow in their respective professions.
Sales Professionals, IT Engineers, Product Managers, and other non-technical individuals aspiring to make a career in data science or grow in the same field.

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.

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Dedicated Career Assistance

Be one step ahead with access to 1:1 career counseling sessions and mock interviews with hiring managers.

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Student 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.

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Craft Your Path to Data Science Mastery

Practical Application

Apply data science and machine learning principles
Focus on real-life data, business analytics, and NLP situations

Research Thesis

Select a topic and dataset
Review relevant literature
Implement research methods and technical writing skills

Technical Research Writing

Learners develop skills in research methodology and technical documentation
Structured writing techniques ensure clarity and precision in reports

Final Presentation

Present the final thesis
Earn the LJMU Masters in Data Science qualification

Master'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

Earn a Master's Degree from LJMU

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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Explore Our Learning Platform

Learn on an AI-powered & personalised platform with best-in-class
content, live sessions & mentoring from leading industry experts.

Explore Now

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

500+ Hours of Learning Content.

25+ Case Studies and Projects

14+ Case Studies and Projects

1 Industry Capstone Project

6 Months Masters Project

Course 1 - Data Toolkit

13 weeks

Topics (7)

Programming in Python
Introduction to Python
Python for Data Science
Data Visualization in Python
Exploratory Data Analysis
Credit EDA Case Study
Inferential Statistics

Course 2: Machine Learning - I

10 Weeks

Topics (10)

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

Specialisation 1: 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 2: 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

Specialization 3: Deep Learning

29 Weeks

Topics (16)

Bagging & Random Forest
Boosting
Model Selection
Principal Component Analysis
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

Specialisation 4: 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

Specialisation 5: 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

5 Specializations

14+ Case Studies and Projects

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?

5 Instructors
9 Industry Experts

Prof. Dhiya Al-Jumeily

Professor - Artificial Intelligence
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.
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LJMU Profile

Chandrashekar Ramanathan

Dean - Academics
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.
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IIITB Profile

Tricha Anjali

Ex-associate Dean
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.
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IIITB Profile

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.
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IIITB Profile

Prof. G. Srinivasaraghavan

Professor
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.
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IIITB Profile

S. Anand

CEO
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

LinkedIn Profile

Mirza Rahim Baig

Lead Analyst
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.
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LinkedIn Profile

Sajan Kedia

Ex-Data Science Lead
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

LinkedIn Profile

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
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LinkedIn Profile

Kautuk Pandey

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

LinkedIn Profile

Ujjyaini Mitra

Head of Analytics
An alumnus of McKinsey and Co, Flipkart and Bharati Airtel with over 11 years of experience

An alumnus of McKinsey and Co, Flipkart and Bharati Airtel with over 11 years of experience
Read More

LinkedIn Profile

Ankit Jain

ML Engineering Manager
An alumnus of IIT Bombay, UCB, and HBS with over 9 years of experience. Ankit has been recognised as 40Under40 Data Scientist for 2022

An alumnus of IIT Bombay, UCB, and HBS with over 9 years of experience. Ankit has been recognised as 40Under40 Data Scientist for 2022
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LinkedIn Profile

Anshuman Gupta

Director, Data Science
He has a Ph.D (Dual) from Penn State University as well as a B.Tech. Degree from IIT Bombay

He has a Ph.D (Dual) from Penn State University as well as a B.Tech. Degree from IIT Bombay
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LinkedIn Profile

Bijoy Kumar Khandelwal

COO, Actify
Bijoy comes with a deep understanding of the private and cloud architectures and has helped numerous companies make the transition

Bijoy comes with a deep understanding of the private and cloud architectures and has helped numerous companies make the transition
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LinkedIn Profile

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

Logistic Regression
Tree Models
Model Selection
Feature Engineering
Classification
ML Modelling
Model Evaluation
Business Problem Solving

Advanced ML Case Study - Telecom Churn

Know More

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.

Know More

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.

Know More

Skills learned

AWS
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.

Know More

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

Know More

Skills learned

ML Modeling
Linear Regression
ML Model Evaluation

MapReduce Programming Assignment

Practice MapReduce Programming on a Big Dataset.

Know More

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

Information Technology and Services

38%

Banking and Financial Services

13%

Education

Healthcare

Others

37%

By Work Experience

Fresher 16%

0-2 Years 8%

2-5 29%

5-8 Years 18%

8+ Years 29%

By Highest Qualification

GRADUATION

54%

POST_GRADUATION

30%

Intermediate

13%

Others

By Degree Type

B.E./ B.Tech 41%

MBA 11%

B.Sc. 7%

B.com. 7%

Others 30%

By Age

34+

25%

30-34

21%

26-30

31%

22-26

19%

18-22

Others

By Gender

Male 75%

Female 25%

Data Science Course Learner Services

How will upGrad support you?

Access the various career development support services offered by
upGrad to help you achieve your professional goals.

Career Assistance
Practical Learning & Networking

Career Assistance

AI Powered Profile Builder

Obtain specific, AI powered inputs on your resume and Linkedin structure along with content on real time basis

Interview Preparation

Get access to Industry Experts and discuss any queries before your interview
Career bootcamps to refresh your technical concepts and improve your soft skills

High Performance Coaching (1:1)

Get a dedicated career coach after the program to help track your career goals, coach you on your profile, and support you during your career transition journey

Practical Learning & Networking

Networking & Learning Experience

Live Discussion forum for peer to peer doubt resolution monitored by technical experts
Peer to peer networking opportunities with 10,000+ pool of alumni
Lab walkthroughs of industry-driven projects
Weekly real-time doubt clearing sessions

Industry Expert Guidance

Interactive Live Sessions with leading industry experts covering curriculum + advanced topics

Student Support

Chatbot

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

Eligibility

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

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Give a selection test

Give a short 17 minutes aptitude test and get shortlisted

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Reserve your Seat & Begin the Prep Course

Reserve your seat by paying the deposit amount to enroll in the program. Begin 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

Start Referring *T&C Click Here

Data Science Program Success Stories

What Our Learners Say

5/5

Importance of upskilling to stay competitive in my industry.

The most noteworthy feature of UpGrad is its incredible staff. The program coordinators go above and beyond to support working professionals. They understand the unique challenges we face while balancing work and education. They were always available to help whenever I needed guidance and felt overwhelmed. Their dedication was absolutely crucial to my success, and I am deeply grateful for their tireless commitment to making this a positive and achievable learning experience.

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LinkedIn Profile

Kunalsinh Chauhan

Project Manager at Sensia Global- Schlumberger & Rockwell Automation JV
14 Years of Experience

5/5

To focus on personal and professional development, including opportunities for networking, leadership development, and career advancement.

I've been able to leverage my newfound expertise to contribute to key projects, lead teams, and drive positive outcomes in my role. During the journey of this MBA, I was promoted to my current new position. Further, I've had the opportunity to connect with like-minded professionals and industry experts. The knowledge, skills, and experiences gained through the program have not only accelerated my professional growth but have also enriched my life in profound ways

Read More

LinkedIn Profile

Hussain Abbas Ali

Senior Strategy Manager at Concept Combined Group
11 Years of Experience

5/5

Aspiration of learning business from its deep root.

It was a amazing experience. The course structure, SME guidance and explanation of theory related to real world business use case has bolstered confidence and understanding to become a great strategic leader. With online education I can continue with my job and apply the learning continuous during the course of time. They should atleast try some free courses at upgrad or take some small duration certification course with Upgrad, then see the difference it makes in professional life. Their collaboration with reputed universities, course structure and live sessions SME. Moreover their online platform is very much friendly and content are high quality. These are feedbacks I got it during my research before I joined upgrad. Best part of upgrad is their upgrad buddy. They are really like your support system to make your learning amazing. Higher management has started seeing my knowledge and business acumen. I have been involved in many strategic decision making process and got appreciation for my strategic analysis and valuable business inputs. Concept of blue Ocean strategy suggested by me to venture into new areas for business development has been greatly appreciated by leadership team. They guided me every step of my journey. If any additional mentorship, SME coaching, were needed, they provided me without any second thought.

Read More

LinkedIn Profile

Himansu Das

Solution Architect at Amdocs Inc
5 Years of Experience

5/5

Learning new business knowledge

Pleasant but time challenging. Better time management. Its worth it. Pricing. Learning a wide spectrum of knowledge.

Read More

LinkedIn Profile

Brandon Tek

Engineer Manager STA
20 Years of Experience

Frequently Asked Questions

Course Curriculum

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.

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.

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.

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 5 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 one specialization course 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

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

5. 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.

6. Is any certification granted at the end of the program?

Post successful completion of the program, a certificate in Executive PG Program in Data Science would be granted from IIIT Bangalore and a Master's degree from LJMU.

7. When will I have to choose my specialization track?

The program has ~23 weeks of common curriculum and ~29 weeks of specialization and capstone project. Once you’re through the 23 weeks of curriculum common to all five tracks, you will be prompted to choose your specialization.

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

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?

No. You can choose whatever specialization you like once you are through the common curriculum. However, we would urge you to take up the recommendation provided by us as this based on a sophisticated rule engine and is meant to give you the best outcome for your background which will, in turn, make it easier for you to switch to a data role.

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?

Please find the link to the LJMU Collaborative Provision Register, where students can verify validation of the award on the LJMU web pages.

11. Where can one access comprehensive details about the MSDS program at LJMU, including its structure and specific program requirements?

Please find the link to the Program Specifications of the MSDS program on the LJMU website.

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.

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.

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.

2. 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.

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

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:

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.

upGrad Learner Support

Available from 9 AM to 8 PM GMT (Monday - Friday).

Phone Number

+44-20-4602-3556

Email Address

info.emea@upgrad.com

*All telephone calls will be recorded for training and quality purposes.
*If we are unavailable to attend to your call, it is deemed that we have your consent to contact you on purpose.

Disclaimer

upGrad does not grant credit; credits are granted, accepted or transferred at the sole discretion of an educational institution. upGrad does not make any representations regarding the recognition or equivalence of the credits or credentials awarded, unless otherwise expressly stated. If you intend to pursue a post graduate or doctorate degree upon completion of this course or apply for employment which requires specific credits, we advise you to enquire further regarding the suitability of this degree for your academic and/or professional requirements before enrolling.