Kick-start your Machine Learning journey with a Master's from Liverpool John Moores University, ranked in the top 1% of globally recognized universities. Learn in-demand skills such as Deep Learning, NLP, Reinforcement Learning & work on 15+ industry projects, multiple programming tools & a dissertation. 700+ learners from Singapore have already signed up for our programs.

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Recommended 15 hours/week

Fully Online

Learners from Singapore

700+

Industry Projects

15+

Learn about ChatGPT and the latest trends in AI

Advanced AI Lecture Series

Learner Base

50+ Countries

Learning Duration

20 Months

Admissions Close

Jun 15, 2023

Program Start Date

Coming Soon

Accredited from Institute of Analytics

Program Overview

Key Highlights

Learn from the online M.Sc in Machine Learning & AI for working professionals

Get a WES (World Education Services) Recognised Masters degree

Apply your learnings with 15+ industry projects and 6 Capstone Projects to choose from

Access to 25+ small group coaching session

Get LJMU Alumni Status

Get access to LJMU Supervisors for guidance on Research & Dissertation

Access our dedicated Student Success Mentors

Access to Global Job Opportunities with an M.Sc. from LJMU, UK

Accredited by Institute of Analytics UK (IOA)

Ideal for:
- Engineers
- Software/ IT/ Data Professionals

Syllabus

Experience 450+ hours of best-in-class content developed by leading faculty & industry leaders in the form of videos, case studies & projects

Download Syllabus

20 Programming Languages, Tools & Libraries Covered

LJMU

Master's Degree from LJMU

With a heritage that stretches back to 1823, Liverpool John Moores University, UK is now one of the largest and most well-established universities in the UK. It has been ranked in the Top 100 World Young Universities & Top 50 in the UK by Student Satisfaction.

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Complete all courses to achieve this prestigious M.Sc. Degree from LJMU, UK to jump-start your career in ML & AI
Get access to the complete digital library of LJMU to research & write your dissertation
Earn a Master's degree which is recognized by WES, at 1/10th the cost of an offline program

Instructors

Learn from leading ML & AI faculty and industry leaders

Dr. Gabriela Czanner

Faculty - Engineering and Technology

A Senior Lecturer in Statistics and Data Science at Department of Applied Mathematics at LJMU. Her research focus is advanced statistics for decision support.

Dr. Atif Waraich

Faculty - Computer Science

A Senior faculty of Engineering and Technology at LJMU who has multiple publications in the healthcare domain

Prof. Dhiya Al-Jumeily

Professor - Artificial Intelligence

A Senior Member of the IEEE and a Chartered IT Professional. He is a fellow of the UK Higher Education Academy.

Prof. Paulo Lisboa

Head of Dept - Applied Mathematics

Studied mathematical physics at LU and was the chairman of Industrial Mathematics at LJMU in 1996 and Head of Graduate School in 2002

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.

Ankit Jain

Sr. Research Scientist

An alumnus of IIT Bombay, UCB, and Harvard Business School with over 9 years of experience.

Chandrashekar Ramanathan

Dean | Academics

Prof. Chandrashekar has a Ph.D. from Mississippi State University and over 10 years of experience in several multinational organisations.

Tricha Anjali

Former Associate Dean

Prof. Anjali has a Ph.D. from Georgia Tech as well as an integrated M.Tech. (EE) from IIT Bombay. She is currently the dean of IIIT Bangalore

Debabrat Das

Director, IIITB

He is PI and nodal officer of the project under the National Mission for Interdisciplinary Cyber-Physical Systems.

Prof. G. Srinivasaraghavan

Professor

Prof. Srinivasaraghavan has a Ph.D. in Computer Science from IIT Kanpur and 18 years of experience with Infosys Technologies.

Ujjyaini Mitra

Head of Analytics

An alumnus of McKinsey and Co., Flipkart, and Bharti Airtel with over 11 years of experience.

Mirza Rahim Baig

Lead | Business Analytics

Advanced analytics professional with 8+ years of experience as a consultant in the e-commerce and healthcare domains.

Syllabus

Experience 750+ hours of best-in-class content developed by leading faculty & industry leaders in the form of videos, case studies & projects

Download Brochure

750+

Hours of Content

12+

Case Study and Projects

40+

Live Sessions

Coding Assignments

Tools, Languages & Libraries

Capstone Projects to Choose From

Pre-Program Preparatory Content

3 Weeks

Introduction to Python
Python for Data Science
Data Visualisation in Python
Data Analysis Using SQL (Optional)
Advanced SQL and Best Practices (Optional)
Data Analysis in Excel (Optional)
Analytics Problem Solving (Optional)
Math for Machine Learning

Statistics and Exploratory Data Analytics

5 Weeks

Exploratory Data Analysis
Cloud Essentials: Intro to Git & Cloud
Investment Assignment
Inferential Statistics
Hypothesis Testing
Lending Club Case Study

Machine Learning - I

7 Weeks

Linear Regression
Linear Regression Assignment
Logistic Regression
Naive Bayes
Model Selection

Machine Learning - II

7 Weeks

Advanced Regression
Advanced Regression Assignment
Support Vector Machine (Optional)
Tree Models
Model Selection - Practical Considerations
Boosting
Unsupervised learning: Clustering
Unsupervised Learning: Principal Component Analysis
Telecom Churn Case Study

Deep Learning

8 Weeks

Introduction to Neural Networks
Convolutional Neural Networks - Industry Applications
Convolutional Neural Networks - Assignment
Recurrent Neural Networks
Neural Network Project - Gesture Recognition

Natural Language Processing

7 Weeks

Lexical Processing
Syntactical Processing
Syntactic Processing - Assignment
Semantic Processing
Case Study: Classifying Customer Complaint Tickets

ELective 1: DL with MLops

10 Weeks

Cloud Essentials: Intro to AWS
Working with AWS: case study
MLOps: Introduction
MLOps: Data Lifecycle
MLOps: Model Lifecycle
MLops Assignment
Advanced CV
Advanced CV
MLOps + Deployment: DL (Theory)
MLOps + Deployment: DL (assignment)

Elective 2: NLP with Mlops

10 Weeks

Cloud Essentials: Intro to AWS
Working with AWS: case study
MLOps: Introduction
MLOps: Data Lifecycle
MLOps: Model Lifecycle
MLops Assignment
Advanced NLP
Advanced NLP
MLOps + Deployment: NLP (Theory)
MLOps + Deployment: NLP (assignment)

Elective 3: AI strategy

10 Weeks

Cloud Essentials: Intro to AWS
Working with AWS: case study
MLOps: Introduction
MLOps: Data Lifecycle
MLOps: Model Lifecycle
MLops Assignment
AI Strategy Framework, Structured Problem Solving/ Data Storytelling
Mapping ML with Data architecture strategy
Executing AI Strategy
AI strategy: Assignment
Capstone

Reinforcement Learning (Optional)

Classical Reinforcement Learning
Assignment -Classical Reinforcement Learning
Deep Reinforcement Learning
Reinforcement Learning Project

Research Methodologies

8 Weeks

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

Master's Dissertation

16 weeks

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

AI Mastery Syllabus

Dive into the latest trends like ChatGPT, Dall E, and Explainable AI (XAI) through this series by renowned experts in the field.

Unleashing the Power of AI: Exploring the Latest Trends in Generative Modelling

The GPT-3 Revolution

Introduction to ChatGPT: The world of AI is constantly evolving, and staying up to date with the latest advancements can be challenging. This session will introduce you to the power and potential of GPT-3.
Objective: To comprehensively understand GPT-3, its capabilities like Natural Language Understanding(NLU) & Context Recognition, and how it can be used in their work or business.

Be 10x productive with Prompt Engineering

Prompt engineering is a powerful technique that can help content creators, freelancers, and businesses generate high-quality text quickly and efficiently. This session will introduce you to the concept of prompt engineering and its applications.
Objective: The objective of this session is to provide learners with a comprehensive understanding of prompt engineering and how it can be used with different AI tools like ChatGPT3, Midjourney & Stable Diffusion.
By the end of the session, learners will be able to use prompt engineering techniques to generate high-quality text for a variety of applications.

Crack the Code of AI: Demystifying Model Explainability and Interpretability

From Black Box to Glass Box: An introduction to Explainable AI

With the increasing adoption of AI, there is a growing need to ensure that AI models can be understood and trusted. This session will introduce you to the concept of Explainable AI and Model Interpretability.
Objective: To gain a comprehensive understanding of the importance of XAI (Explainable Aritificial Intelligence) and model interpretability, and learn how to build and interpret an interpretable machine learning model using LIME & SHAP techniques

Is AI racist and biased?

As AI is increasingly used in various domains, it is important to consider the ethical implications and potential biases that can arise. This session will introduce learners to the concepts of ethics and bias in AI and provide real-world examples.
Objective: To understand the ethical and bias considerations in AI and how to identify and mitigate potential issues. Learn through case studies in healthcare, finance, autonomous vehicles, recruitment among others.

Building Innovative Products with AI: Leveraging the Power of Generative Modelling

From Data to Dialogue: Diving into ChatGPT's Architecture and Functionality

This session will provide an overview of GPT models and their architecture, along with advanced techniques like RLHF and InstructGPT.
Objective: The objective of this session is to introduce learners to one of the variant of the Transformer - the GPT model, specifically the Davinci variant. They will gain knowledge about the architecture of GPT models and advanced techniques such as Reinforcement Learning from Human Feedback (RLHF), one-shot & few shot learning. They will also learn how to fine-tune GPT models with prompts and evaluate their performance through hands-on exercises.

ChatGPT-Based Ticket Classifier: A Game-Changer for Support Teams

Using transfer learning with GPT-3 eliminates the need to train NLP models from scratch, and provides access to state-of-the-art language models on various NLP tasks. This session will help you perform 'Ticket Classification Using ChatGPT'
Objective: To build a product that can automatically classify support tickets into different categories based on their topics using the fine-tuned ChatGPT model. This will help companies and organizations to improve their support ticket handling efficiency and reduce the workload of their support teams.

Build an Image generator using Stable Diffusion

Using transfer learning with GPT-3 eliminates the need to train NLP models from scratch, and provides access to state-of-the-art language models on various NLP tasks. This session will help you 'Build an image generator using stable diffusion'
Objective: The objective of this session is to teach learners how to build an image generator using Stable Diffusion and the Hugging Face library. They will learn how to prepare data, build and train a Stable Diffusion model, evaluate its performance, and build a Streamlit dashboard to showcase the model's output.

Innovations in Graph Networks, Computer Vision and Generative Modelling

The world of Graph Networks

This session aims to simplify the process and provide learners with a comprehensive understanding of Graph Neural Networks (GNNs) and how to build a simple GNN model.
Objective: The objective of this session is to introduce learners to the components of a GNN, its working mechanism, and how to build a simple GNN model for a given problem statement. By the end of the session, learners will be able to apply their knowledge to solve problems related to graph data.

Advanced Graph Networks

With the limitations of simple GNNs, there is a need to explore advanced GNN architectures. This session aims to provide an in-depth understanding of advanced graph networks.
Objective: By the end of this session, learners should be able to comprehend the drawbacks of simple GNNs. Additionally, learners should be able to compare and evaluate the performance of advanced GNNs like Graph Convolutional Networks(GATs) & Graph Attention Networks(GANs) to simple GNNs.

State of Art (STOA) architectures in Computer vision

In this session, we will introduce learners to the concept of landmark and feature detection, and enable them to build a simple landmark detection system.
Objective: By the end of the session, learners will be able to understand the fundamentals of landmark detection, popular feature detection algorithms such as SIFT and SURF, and build a landmark detection system using feature detection algorithms.

State of Art(STOA) architectures in generative modelling

Keeping up with the latest advancements in generative modeling can be challenging. This session aims to provide an overview of the state-of-the-art (STOA) architectures in generative modeling and their applications.
Objective: By the end of the session, learners should have an understanding of the STOA architectures in generative modeling and be able to read research papers on topics such as image-to-text models (Vision Transformers), text-to-image models(CoCA, CLIP), and multimodality(Pathways).

Industry Projects

Learn through real-life industry projects sponsored by top companies across industries

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

Telecom Churn

Solve the most crucial business problem for a leading telecom operator in India and southeast Asia - predicting customer churn.

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Classification of Customer Complaints

Create a solution that will help in identifying the type of complaint ticket raised by the customers of a multinational bank

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Credit Card Fraud Detection

Build a machine learning model capable of detecting fraudulent transactions. Here you have to predict fraudulent credit card transactions with the help of machine learning models.

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Melanoma Detection Assignment

Build a neural network from scratch in Tensorflow to identify the type of skin cancer from image.

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Train an Agent to play Tic Tac Toe

Learners will apply Q-Learning to train an RL agent to play the game of numerical Tic Tac Toe.

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Gesture Recognition

Make a Smart TV system which can control the TV with user’s hand gestures as the remote control

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News Recommender System

Build a model to using the concepts of natural language processing and recommender systems to recommend news stories to users on a popular news platform.

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Maximizing profit of cab driver using RL

Learners will use the Markov Decision Process & Q-Learning to build an RL agent that learns to choose the best request so as to maximize the total profit earned by the agent that day.

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Custom Entity detection in Healthcare data

You will build a custom NER to get the list of diseases and their treatment from a medical healthcare dataset.

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Eye for the Blind

Build a model that can help any visually impaired person in understanding image present before them. It is a deep learning model which can explain the content of an image in the form of speech.

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Sentiment analysis based Product Recommender system

Build a sentiment analysis based product recommendation system to recommend the similar products to the users. Sentiment analysis is used to fine tune the product recommendation system.

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Sales Forecasting

Predict the sales for a european pharma giant using a host of different types of variables. Apply VAR and VARMAX models to build the appropriate model

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Style Transfer using GAN's

Build a Model for converting MRI images from one type (T1) into other (T2) and vice versa. CycleGAN model is used for producing T2 type MRI images given T1 type input MRI images

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Machine Translation System

You will build an attention-based neural machine translation model translating from one language to another.

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Face Mask Detection

Create a custom object detector using the YOLO algorithm to detect the presence of face masks in the images of different people.

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Benefits with upGrad

360 Degree Career Support services, Personalized Mentorship from Industry Experts, Hands-on Projects, Peer Networking opportunities & a whole lot more to help you master Machine Learning & AI.

High ROI

Cost Effective

Upgrade your career at 1/10 the cost of the same on campus program

Learn and Earn

Get world class credentials without leaving your job from the comfort of your home

Unique Learning Experience

Industry Driven

Learn through curriculum created by the industry for the industry
Learn and get coached by leading industry experts from around the globe

Flexible

Experience world class education on-demand through our proprietary app and website

Unparalleled Support

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

Career Preparation

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

Networking

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.

Our Learners Work At

Top companies from all around the world have recruited upGrad alumni

Student Reviews

Sondre Rennan Nesset

CEO at Sensor Innovation AS, Norway

The highlights of my course so far are the depth of knowledge it has given me about AI/ML, the assignments which have taught me more about the field as well as the affordability of the course.

Detailed Review

Budhaditya Goswami

Target oriented Biostatistician (ML-AI), Germany

Topics are designed keeping practical application at the forefront which means that learners practice on actual problems in real industries. The content, the reputation of the provider and course fees being within my budget are why I chose upGrad.

Detailed Review

Krishnan Sivasubramanian

VP , Global Consumer Technology, Singapore

I was referred by a friend and decided to give it a shot. Best investment.

Detailed Review

K M Kadir Khan

Data Analyst, Bongo, Bangladesh

I feel lucky to have stumbled upon this course. It is the best investment I've made on myself.

Detailed Review

Emmanuel Idehen

Full Stack Developer, FedEx Services, Memphis

Very happy that I joined the program for upskilling in ML & AI & upGrad gave me the right opportunity.

Detailed Review

Ankit Bansal

Solution Lead, Brane Enterprises Pvt. Ltd.

I really appreciate upGrad's online education system and providing valuable certification.

Detailed Review

Ankit Jain

Senior SDE3, Delphix

More than a quest for career transition it was curiosity that drove me to this course. I am still learning but equipped with better tools.

Detailed Review

Nishant Chalasany

Delivery Manager, Syngenta

upGrad helped me establish communication channels with the Data Science & Data Platforms teams & ensure we worked towards high quality deliveries for my organization.

Detailed Review

Jyothi Rajesh

Software Technical Consultant , Parametric Technology Corporation

The upGrad experience of lectures, live sessions, MCQs, individual and group assignments and exams was overwhelming, but rewarding as I covered topic-after-topic.

Detailed Review

Ridhiman Singh

Data Science Researcher , Data Folkz

Having completed my PGDMLAI from IIITB, I started searching for opportunities and it didn't take much time to find one with all the knowledge and skills.

Detailed Review

Admission Process

There are 3 simple steps in the Admission Process which are detailed below:

Step 1

Take the online eligibility test

Complete your application to take a 18 question online eligibility test to start the admission process. The test is designed to assess your quantitative & logical aptitude ensuring you are 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 in Master's in Machine Learning & Artificial Intelligence.

Step 3

Confirm your seat & begin with your prep - course

Confirm your seat by enrolling into the program and making the initial caution payment. Begin your preparatory course & start your career in Machine learning & AI.

Program Fees

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Frequently Asked Questions

Program Details

How do I know if this program is for me?

This program is for you if you are a:
Data Scientist or Senior Data Analyst: If you are comfortable with data wrangling, have implemented statistical or machine learning models in the past, and have spent at least 2 years as a working professional. You should also have some experience with R/Python/Scala.
Statistician: If you received formal education in statistics or mathematics and have at least 2 years of working experience.
Data Engineer/Big Data Engineer: If you have at least 2 years of experience in creating data pipelines/handling data warehouses and you have created ETL procedures. In addition, you should be familiar with various frameworks and tools like Hadoop and Spark.
Software Developer: If you have worked on creating and deploying software/apps for at least 4 years, you are comfortable with object-oriented programming and know C/C++/Java/Python or a similar language.

How will this program benefit me?

The program will benefit you in different ways depending on your prior experiences:
Data Scientist or Senior Data Analyst: The program will familiarise you with the advancements in ML and AI. It will also help you understand the mathematics behind algorithms and how you can modify them to suit your needs so that you can transition to a Senior Data Science or Machine Learning role.
Statistician/Mathematician: Apart from familiarising you with the advancements in ML and AI, the program will help you understand how to define a structured approach to solve a business problem, and equip you with the right tools so that you can transition to a Machine Learning or Data Science role.
Data Engineer/Big Data Engineer: The program will set up a solid foundation of Statistics, Machine Learning, and AI along with problem-solving skills so that you can solve enterprise-level problems. It will build upon your existing knowledge of various tools to make you a Full-Stack Machine Learning or Data Science professional.
Software Developer: The program will help you create a strong foundation of Statistics, Machine Learning, and Business Understanding. It will leverage your existing knowledge of programming and expand the technologies you are familiar with so that you can become a well-rounded Machine Learning professional.

What is this program intended to do?

This program intends to produce extremely well-rounded data scientists and AI professionals with deep knowledge of mathematics, expertise in relevant tools/languages, and an understanding of cutting-edge algorithms and applications.

What can I expect out of this program?

This program is designed for working professionals looking to pick up skills in advanced concepts like Reinforcement Learning, Graphical Models, NLP, Deep Learning along with a solid foundation of Statistics. This program demands consistent work and time commitment over the entire duration of 18 months.

What should I NOT expect from this program?

This program is NOT intended to serve as an entry point to the field of Data Science. It is aimed at developing professionals who can be absorbed into Senior Data Scientist and Machine Learning/AI roles. Our Master's Degree in Machine Learning Program is aimed at facilitating the transition of professionals to the Machine Learning field.

Is there any certification at the end of the program?

Post completion of the program, a certificate in Executive PG Program in Machine Learning and AI will be granted from IIIT Bangalore and a Master's Degree from LJMU.

Support

What type of learning should I expect?

The content will be a mix of asynchronous lectures from industry leaders as well as world-class faculty. Additionally, the program comprises of some live lectures or hangout sessions dedicated to solving your academic queries and to reinforce learning.

Selection Criteria

What is the selection process for this program?

upGrad, IIITB, LJMU, world-class faculty, and many industry leaders have committed a lot of time in conceptualising and creating this program to make sure that the candidates can receive the best possible learning experience. Hence, we want to make sure that the participants of this program also show a very high level of commitment and passion for Machine Learning and AI.

The applicants will have to take a selection test designed to check their mathematical and programming abilities. The applicants can skip the test if they meet the following criteria:

Minimum 1 year of work experience in a technical domain or a degree in mathematics or Statistics with programming experience.

Refund Policy/Financials

Is there any deferral or refund policy for this program?

Click here to refer to our Refund policy.

Disclaimer

1. 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.

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