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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
    Learn from the online M.Sc in Machine Learning & AI for working professionals
    Get a WES (World Education Services) Recognised Masters degree
    Get a WES (World Education Services) Recognised Masters degree
    Apply your learnings with 15+ industry projects and 6 Capstone Projects to choose from
    Apply your learnings with 15+ industry projects and 6 Capstone Projects to choose from
    Access to 25+ small group coaching session
    Access to 25+ small group coaching session
    Get LJMU Alumni Status
    Get LJMU Alumni Status
    Get access to LJMU Supervisors for guidance on Research & Dissertation
    Get access to LJMU Supervisors for guidance on Research & Dissertation
    Access our dedicated Student Success Mentors
    Access our dedicated Student Success Mentors
    Access to Global Job Opportunities with an M.Sc. from LJMU, UK
    Access to Global Job Opportunities with an M.Sc. from LJMU, UK
    Accredited by Institute of Analytics UK (IOA)
    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.
    Master's Degree from LJMU
    Click to zoom
    • 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

    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
    11
    Coding Assignments
    20
    Tools, Languages & Libraries
    6
    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.
    benefits

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

     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.
    benefits

    Crack the Code of AI: Demystifying Model Explainability and Interpretability

    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.
    benefits

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

    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.
    benefits

    Innovations in Graph Networks, Computer Vision and Generative Modelling

    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

    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.
    benefits

    High ROI

    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
    benefits

    Unique Learning Experience

    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
    benefits

    Career Outcomes

    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

    Admission Process

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

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    Empowering learners of tomorrow

    Over 2,300 students have completed this course and started working at their dream job, whats stopping you?

    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?

    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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