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Highlights

Medium of InstructionsMode Of Delivery
EnglishVideo and Text Based

Course Details

The “Master of Science in Data Science” online degree course is a 20 Months online course for working professionals that are awarded by dual institutes, IIIT Bangalore, and from Liverpool John Moores University LJMU, the UK. This Masters program is for both freshers, and experts irrespective of being Marketing & Sales Professionals, Freshers, Data Professionals, Domain Experts, Software & IT Professionals.

Liverpool John Moores University is among the top UK Schools for getting a “Master of Science in Data Science” degree course. The candidate enrolled in this course gets options to choose from specializations like Natural Learning Processing, Deep Learning, Data Science Generalist, Business Intelligence, Business Analytics, and Data Engineering.

The “Master of Science in Data Science” syllabus has content curated by the faculty and industry leaders in the form of videos, case studies, and assignments. Some of the most required skills learnt are Predictive Analytics using PythonMachine LearningStatisticsData VisualizationBig Data Analytics, etc.

The “Master of Science in Data Science” training program helps in knowledge acquisition and also helps in the student’s further employment opportunities. Also, adding this certificate to their professional portfolio leaves a good impression on the hiring companies, as the candidates are ready to have a competitive edge in their careers in Data Science.


Programme Offerings

  • Online Course
  • Career relevant curriculum
  • Faculty Guidance
  • 3 projects
  • Certificate by HSE University
  • Try a Course

Eligibility Criteria

Educational Qualification:

The minimum educational qualification required for candidates to apply for this Master of Science in Data Science course is a Bachelor’s Degree at least 50% marks from a recognized university 

Work Experience

The candidates need not have any prior experience in coding to apply for this course.

Certification Qualifying Details

Candidates should complete all the in-course lectures, projects, and assignments to receive the completion certification.

Admission Details

Admission to the “Master of Science in Data Science” Certification by Liverpool John Moores University just requires 3 steps to be followed:

Step 1: Visit the Site: Candidates must visit the official website.

Step 2: Online Eligibility Test - Once the application form is duly filled candidates have to sit for 17 minutes online examination to test their quantitative, and logical aptitude abilities.

Step 3: Get Shortlisted - The admission committee will then review the profile and test scores of the candidates, and shortlisted candidates will be sent an offer letter for admission acceptance.

Step 4: Block the Seat - Finally, selected candidates need to pay Rs. 25,000 for enrolling into the program, 

Step 5: After all these steps, candidates can start with the Prep Course on Data Science.

Application Details

Filling of Application forms for the Master of Science in Data Science program needs the candidate to Create an account by entering the phone number to get started. Along with this, they need to submit some other important documents to get done with the application form.

The Syllabus

  • Data Analysis in Excel

  • Analytics Problem Solving

  • Tools Covered: Excel

  • Introduction to Python - I

  • Introduction to Python - II

  • Programming in Python

  • Data Analysis using SQL

  • Python for Data Science

  • Visualization in Python

  • Exploratory Data Analysis

  • IMDb Movie Assignment

  • Maths for Data Science

  • Inferential Statistics

  • Hypothesis Testing

  • Advanced SQL

  • Credit EDA Case Study

  • Tools Covered: Python & Excel

  • Introduction to Machine Learning and Linear Regression
  • Linear Regression Assignment - Bike Sharing Systems
  • Logistic Regression
  • Unsupervised Learning: Clustering
  • Business Problem Solving
  • Clustering Assignment (Optional)
  • Case Study: Lead Scoring
  • Tools Covered:  Python & Excel

  • Tree Models + Boosting (Optional)
  • Model Selection & General ML Techniques
  • ML Lab I: Classification
  • Principal Component Analysis
  • Advanced Regression - I
  • Advanced Regression - II and ML Lab II: Regression
  • Text Analytics & Processing + Text-Based Predictive Modelling
  • Basic Visualisation using Tableau
  • Data Storytelling
  • Business Case Study
  • Data Modelling
  • SQL Weeklong Lab
  • Advanced SQL - Week II
  • Algorithm Analysis + Recursion
  • Searching and Sorting (Divide and Conquer included)
  • Data Structures - Sets, Dictionaries, Stacks, Queues
  • Python - OOPS
  • Python Weeklong Lab
  • Capstone Project
  • Tools Covered: Python, MySQL, Tableau

  • Tree Models
  • Model Selection & General ML Techniques
  • Principal Component Analysis
  • Advanced Regression
  • Advanced Regression Assignment
  • Bagging and Boosting
  • Time Series Analysis
  • Telecom Churn Case Study
  • Text Processing
  • Feature Extraction & modeling
  • Assignment - Natural Language Processing
  • Intro to DL
  • NLP Industrial Applications
  • Chatbot Case Study
  • Capstone Project
  • Tools Covered: Python

  • Data Modelling

  • SQL Best Practices

  • SQL Assignment: IMDb Movies

  • Advanced Excel

  • NoSQL Databases and Best Practices

  • Introduction to Big Data and Cloud

  • Hive and Querying

  • Hive Case Study

  • Visualisation using Tableau

  • Sports Analytics - IPL Visualisation Assignment

  • Visualisation using PowerBI

  • Visualisation using Plotly

  • Data Storytelling

  • Plotly Case Study

  • Capstone Project

  • Tools Covered: MongoDB, MySQL, AWS, Excel, Power Bl, Tableau

  • Tree Models
  • Time Series Forecasting
  • Retail-Giant Sales Forecasting Assignment
  • Model Selection & General ML Techniques
  • SQL Best Practices
  • Advanced Excel
  • Telecom Churn Case Study
  • Structured Problem Solving using Frameworks
  • Structured Problem Solving Assignment
  • Operations Research
  • Data Storytelling
  • Operations Research Case Study
  • Capstone Project
  • Tools Covered: MySQL, Excel, Python, Tableau

  • Introduction to Big Data(Optional)
  • Introduction to Cloud and AWS Setup
  • Introduction to Hadoop and MapReduce Programming
  • MapReduce Programming Assignment (optional)
  • Data Management and Relational Database Modelling
  • NoSQL Databases and Apache HBase and NoSQL Databases and MongoDB(Optional)
  • Data Warehousing (Optional)
  • Data Ingestion with Apache Sqoop and Apache Flume
  • Hive & Querying
  • Hive Assignment (optional)
  • Amazon Redshift
  • Introduction to Apache Spark
  • NYC Parking Assignment (Optional)
  • Project: ETL Data Pipeline
  • Optimizing Spark for Large Scale Data Processing
  • Apache Flink(Optional)
  • Real-Time Data Streaming with Apache Kafka
  • Real-Time Data Processing using Spark Streaming
  • Stock data Analysis Assignment (Optional)
  • Building Automated Data Pipelines with Airflow
  • Analytics using PySpark
  • Classification Assignment (Optional)
  • Project: Real-Time data processing
  • Capstone Project
  • Tools Covered: Hadoop, MapReduce, Spark, Beehive

  • Introduction to Research and Research Process
  • Research Design
  • Literature Reviewing
  • Research Project Management
  • Report Writing and Presentation Skills
  • Scientific Ethics

  • Investigate the risk factors for eye disease from complex longitudinal datasets
  • Investigate a diagnosis of eye diseases using imaging ophthalmic data
  • Multi-task learning for drug design and discovery
  • Using stacking for brain tumor discrimination
  • Investigate dietary patterns and metabolite fingerprints of takeaway (fast) food consumers using PCA and Clustering methods
  • Longitudinal studies to investigate the complex link between corporate environment engagement, green disclosure, business model transformation and supply chain performance
  • Preventing credit card fraud through pattern recognition
  • Developing a recommender system for a Media giant
  • Using social media feed to place tweets regarding natural disasters on a map

Evaluation Process

The Master of Science in Data Science degree does not require candidates to sit for any after-course examinations. The candidates need to do is compulsorily complete all the in-course assessments, and capstone projects successfully to earn the certifications.

Liverpool John Moores University, Liverpool Frequently Asked Questions (FAQ's)

1: What kind of learning experience should one expect from a “Master of Science in Data Science” Certification?

The lectures are content taught by leaders in the Data Science field along with the globally renowned faculty of LJMU and IIT Bangalore.

2: When can a student choose a specialisation track?

The “Master of Science in Data Science” program has nearly 23 weeks of the common syllabus, and the rest 29 weeks will be for course specialization and capstone projects.

3: How will I know which specialisation is the best for me?

When candidates are done with studying the first half of the syllabus, upGrad gives them proper recommendations with respect to their background that will help them select the choice of their specialization. 

4: What is the time commitment that a student should give for the online Master of Science in Data Science course?

The “Master of Science in Data Science” Training requires every candidate to allot at least 15 hours every week to help them complete this program with flying colors.

5: Does a candidate get special different career services for each specialization?

Any specialization that a candidate selects will give him or her learnings based on their background and help them be a master of the domain in Data Science.

6: Are there any fees or down payment for the Master of Science in Data Science program?

There are banks that charge some amount as processing fees ranging from Rs. 99- Rs. 500 on 0% Credit Card EMI transactions. Even if the charge is made, it will be billed along with the first repayment installment.

7: Will I be charged if I opt for cancellation/refund from the course after paying the balance with no cost EMI?

The candidates can be charged with an additional amount towards the interest paid by the upGrad to the bank, but will only be refunded the amount deducted from their card.

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