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Highlights
| Medium of Instructions | Mode Of Delivery |
|---|---|
| English | Video 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 Python, Machine Learning, Statistics, Data Visualization, Big 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.