Master of Science in Data Science
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INTRO VIDEO
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Accredited from Institute of Analytics
Program Overview
Key Highlights
Choose from 3 specializations
-Deep Learning
- Business Intelligence/Data Analytics
- Data Engineering
Syllabus
Experience 500+ hours of best-in-class content by leading faculty and industry leaders in the form of videos, cases and projects
Programming Languages and Tools Covered
- 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
Instructors
Learn from leading Data Science faculty and industry leaders.
Dr. Gabriela Czanner
Prof. Paulo Lisboa
Dr. Atif Waraich
Prof. Dhiya Al-Jumeily
Chandrashekar Ramanathan
Tricha Anjali
Debabrat Das
Anshuman Gupta
Ujjyaini Mitra
Ankit Jain
Mirza Rahim Baig
Sajan Kedia
Prof. G. Srinivasaraghavan
Colin Hagemeyer
Behzad Almadi
S. Anand
Bijoy Kumar Khandelwal
Syllabus
Pre-Program Preparatory Content
- Data Analysis in Excel
- Analytics Problem Solving
Data Toolkit
- 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
Machine Learning
- Linear Regression
- Linear Regression Assignment
- Logistic Regression
- Classification using Decision Trees
- Unsupervised learning: Clustering
- Basics of NLP and Text Mining
- Business Problem Solving
- Case Study: Lead Scoring
Specialization- Deep Learning
- Bagging & Random Forest
- Boosting
- Model Selection & General ML Techniques
- Principal Component Analysis
- Advanced Regression
- Advanced ML case Stuy
- Time Series Analysis
- Introduction to Neural Networks and ANN
- Neural Network Assignment
- Convolutional Neural Networks
- Convolutional Neural Networks -Industry Applications
- Object Detection & Image Segmentation (Optional)
- Recurrent Neural Networks
- Gesture Recognition
- Capstone Project
Specialisation - Business Intelligence/Data Analytics
- Visualisation using Tableau
- Advanced Excel
- Visualisation using PowerBI
- Structured Problem Solving using Frameworks
- Data Storytelling
- AirBnB Case Study
- Data Modelling
- Advanced SQL and Best Practices
- Introduction to Big Data and Cloud
- Analytics using Spark
- Big Data Case Study
- Data Structures - Sets, Dictionaries, Stacks, Queues
- Searching and Sorting
- Algorithm Analysis + Recursion
- Advanced Database Programming using Pandas
- Python & SQL Lab
- Capstone Project
Specialisation - Data Engineering
- Data Management and Relational Database Modelling
- Introduction to Big Data(Optional)
- Introduction to Cloud and AWS Setup
- Introduction to Hadoop and MapReduce Programming
- Assignment (Optional)
- NoSQL Databases and Apache HBase and NoSQL Databases and MongoDB(Optional)
- Data Warehousing (Optional)
- Data Ingestion with Apache Sqoop and Apache Flume
- Map reduce Programming Assignment
- Hive & Querying
- Assignment (Optional)
- Amazon Redshift
- Introduction to Apache Spark
- Project: ETL Data Pipline
- AWS Cloud Infrastructure (Optional)
- Optimising Spark for Large Scale Data Processing
- Apache Flink(Optional)
- Real-Time Data Streaming with Apache Kafka
- Real-Time Data Processing using Spark Streaming
- Assignment (Optional)
- Building Automated Data Pipelines with Airflow
- Analytics using PySpark
- Project: Real Time data processing
- Capstone Project
Research Methodologies
- Introduction to Research and Research Process
- Research Design
- Literature Reviewing
- Research Project Management
- Report Writing and Presentation Skills
- Scientific Ethics
Master's Dissertation
- Investigate dietary patterns and metabolite fingerprints of takeaway (fast) food consumers using PCA and Clustering methods
- 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
Specializations
Topics Covered
Deep Learning
Industry Projects
- Engage in collaborative projects with student-mentor interaction
- Benefit by learning in-person with expert mentors
- Personalized subjective feedback on your submissions to facilitate improvement
IMDb Movie Analysis
Analyze movie data from the past hundred years and find out various insights to determine what makes a movie do well.
Uber Supply-Demand Gap
Use analytics to identify why Uber sometimes faces a supply-demand challenge and what can be done to overcome it
Lead Scoring
Learn how the knowledge of basic machine learning algorithms can be used to determine leads that are potentially convertible and save your Sales team time, money, and resources.
Fraud Detection
Decline fraud transactions on a credit card in real-time to minimize the losses so that customers are not charged for items that they did not purchase.
Creditworthiness of Customers
Learn how Predictive Analytics can be used to decide the creditworthiness of customers and whether they are issued a credit card or not
Speech Recognition
Learn how Google speech-to-text works and make your own model.
Image Captioning
Build a model which will caption a given image and describe it in sentences in a detailed way like objects present, the actions they are doing, etc.
Social Media Listening
What if you could predict the popularity of a brand like upGrad in India?
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.
Retail-Giant Sales Forecasting
Help a retail-giant to have a clear idea of how their sales will look like in the future.
Interactive Marketing Campaign Analysis
Research and analyse data from a marketing campaign to gain valuable insights and determine the ‘yays’ and ‘nays’ of the campaign.
The upGrad Advantage
High ROI
- Upgrade your career at 1/10 the cost of the same on campus program
- Get world class credentials without leaving your job from the comfort of your home
Unique Learning Experience
- Learn through curriculum created by the industry for the industry
- Learn and get coached by leading industry experts from around the globe
- Experience world class education on-demand through our proprietary app and website
- Work with a dedicated upGrad buddy who will handhold you throughout the program
- Get expert verified resolutions for all your doubts within hours
- Weekly live sessions with industry experts on doubts, career & communication
Career Outcomes
- Rigorous career preparation with resume feedback, personal branding on LinkedIn
- Career booster content to help understand how to search for jobs, prepare for interviews, negotiate your salary etc.
- Industry mentorship : Receive mentorship from industry leaders of the domain to help you reach your desired career goal
- Opportunity to network with accomplished professionals, faculty and industry experts from 50+ countries
- Part of 50K+ alumni base who are working in top companies like Amazon, ESPN, Visa, Microsoft, E&Y, Accenture
Admission Process
There are 3 simple steps in the Admission Process which is detailed below:
Step 1
Take the Online Eligibility Test
Complete your application to take the 17 minute online eligibility test to kick-start the admission process. The test is designed to assess your quantitative & logical aptitude ensuring you're ready for the program.
Step 2
Get Shortlisted & Receive your Offer Letter
Our Admissions Committee will review your test score & profile. Upon qualifying, an Offer Letter will be sent to you confirming your admission to the Executive PGP in Data Science and Master in Data Science from L.J.M.U
Step 3
Block your Seat & Begin the Prep Course
Confirm your seat by enrolling into the program and making the initial block payment. Begin your preparatory course & start your career in Data Science.
Program Fees
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Refer someone you know and receive cash reimbursements of up to $500!*
*More details under the referral policy under Support Section
Empowering learners of tomorrow
Over 2,300 students have completed this course and started working at their dream job, whats stopping you?
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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 20-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 LJMU.
What should I expect from the Master's Degree in Data Science?
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.
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 six tracks. These six tracks 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 six specializations are as follows:
Common Curriculum: Basics of SQL, Python, Statistics and EDA, Basic Machine Learning Models
Data Science Generalist: Advanced Machine learning & Storytelling, Advanced Programming & Databases
Deep Learning Specialization: Advanced Machine Learning, Neural Networks
NLP Specialization: Advanced Machine Learning, Natural Language Processing
Business Intelligence: Advanced SQL and NoSQL Databases, Storytelling with Advanced Visualization
Business Analytics: Advanced Machine Learning, Storytelling and Advanced Business Problem Solving
Data Engineering: Data Modelling and Data Warehousing, Building Data Pipelines, Data Streaming and Processing
What type of learning experience should I expect?
Is any certification granted at the end of the program?
Post successful completion of the program, a certificate in Master's degree from LJMU would be granted.
When will I have to choose my specialization track?
The program has ~23 weeks of common curriculum and ~29 weeks of the specialization and capstone project. Once you’re through the 23 weeks of curriculum common to all the 3 tracks, you will be prompted to choose your specialization.
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
Business Intelligence/ Data Analytics: Engineers, Marketing and Sales Professionals, Freshers
Data Engineering: Software and IT Professionals
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.
Time Commitment
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.
Will the three specializations require different time commitments?
Each of the three specializations will have a common ~23-week curriculum in which the time commitment will be exactly the same.
When you move onto a specialization, it might be that some weeks are heavier in a particular track but lighter for the others. But, overall the total time commitment required will be 12-15 hours/week on average
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?
What is the application process for the program and what are the timelines?
You can start the application process by submitting the application. Applications have already started for the next cohort.
What is the selection process for this program?
upGrad, 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
Is there any minimum educational qualification required to take this program?
To be eligible for the program, the following criteria need to be fulfilled:
- College Degree: The applicant should have a bachelor’s degree in science/engineering/business administration/commerce/mathematics or masters in mathematics/statistics with 50% or equivalent passing marks.
- Work experience: The applicant should preferably have at least 1-2 year of professional experience.
Refund Policy/Financials
Is there any deferral or refund policy for this program?
Refund Policy: (Programs with/without prep-session component)
- The student must pay applicable caution money for the enrollment of the course. This will be adjustable against the total course fee payable by the student.
- 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.
- Refund shall be processed to an eligible student within 30 working days from the date of receipt of refund form subject to submission of the right documents from him/her in this regard.
- Refund shall be subject to deduction of USD 150 or local currency equivalent processing charges.
Deferral Policy: (Post Program Commencement)
- If a student is facing severe issues in dedicating time to the course, we provide the opportunity for the student to defer to another batch. This deferral will be subjected to a 10% deferral fee of the total course amount + taxes if any along with the differential program fees between the two cohorts.
- This deferral request shall be granted only once and to either of the scheduled cohorts to start in the next 1 year from the start date of the initial batch for which the student was originally enrolled for.
- The deferral request will be approved once the deferral fee is paid. Until the process is completed, the student will be assumed to be continuing in the same cohort.
- The student has 7 days (including holidays and weekends) from the date of deferral request to make the payment of the deferral fee post which the deferral request shall be deemed as expired, and the student shall continue as part of the current cohort.
- If the student completes the deferral payment, the student’s login will be disabled, the student will leave the deferred cohort and the student will start learning on the new cohort from the point of the last assignment that was graded in the deferred cohort. All grades and progress till that point will be carried forward as it is to the new cohort. For clarification, the grades of the graded assignments will be carried forward, whether or not the student had submitted these grading during the initial stage.
- The deferral can only be requested during the batch for which the student has enrolled is ongoing. Once the batch has been completed, deferral requests shall not be entertained. For clarification, the batch completion here shall mean the “last grace deadline” as communicated by upGrad.
Deferral Policy: (Pre- Program Commencement)
- If a student, due to unavoidable circumstances is unable to commence with the cohort and requests for a deferral before the cohort starts, we provide the opportunity for the student to defer to another batch.
- However, the student will be required to pay 50% of the total course fee amount (inclusive of taxes) before the deferral can be approved. Till this is completed, the student will be assumed to be continuing in the same cohort.
- A student can request for deferral only once and to either of the scheduled cohorts to start in the next 1 year from the start date of the initial batch in which the student was originally enrolled for.
- The student shall have time till the current cohort launch date to make the payment of the 50% program fee, post which the deferral request will expire. In the event the student raises a refund request after the deferral window expires, the above-mentioned applicable refund policy shall apply.
- The fee applicable to the deferred student will be as per the prevailing fee for the batch student has opted to defer to (No additional deferral fee is required to be paid). The student shall be liable to pay the differential program fees between the two cohorts if any.