upGrad

Master of Science in Machine Learning & AI - Liverpool John Moores University

Stats and EDA

• EDA + Welcome
• Intro to Git & Github
• Lending Club case study
• Inferential Stats
• Hypothesis Testing

Machine Learning - I

• Linear Regression Module
• Linear Regression Assignment: Bike sharing company(demand regression)
• Logistic Regression
• Naive Bayes
• Model Selection
• Revision week - Skill test

Machine Learning - II

• Advanced Regression
• Advanced regression assignment + SVM (Optional)
• Tree Models
• Random Forests + Practical Considerations
• Boosting - 1
• Unsupervised Clustering
• PCA
• Telecom Churn Case Study
• Buffer - Skill test

Deep Learning

• Introduction to Neural Networks - Part1
• Introduction to Neural Networks - Part2
• Convolutional Neural Networks
• Assignment: Convolutional Neural Networks
• CNN: Practical Considerations
• Recurrent Neural Networks
• Gesture Recognition - Project
• Exam on Sunday End of the week
• Revision week - Skill test (DL)

Natural Language Processing

• NLP - Lexical Processing
• NLP - Syntactic Processing
• NLP Assignment - Syntactic Processing
• NLP - Semantic Processing
• Ticket classification Project
• Buffer - Skill test(NLP)

Elective : MLops Elective

• Pre-Requisite Module
• Introduction to MLops
• Designing Machine Learning Systems
• Experimenting with Data and Model using MLflow
• Automating and Orchestrating piepelines with Airflow
• Building continuous learning infrastructure
• MLOps Project
• Advanced NLP - Introduction to Attention Mechanism
• Advanced NLP - Introduction to Transformers
• Advanced CV - Object Detection & Semantic Segmentation
• MLOps + Deployment: DL (Theory)
• MLOps + Deployment: DL (Case Study)
• Exam on Sunday End of the week
• Revision week - Skill test

Elective: Generative AI Elective

• Advanced NLP - Introduction to Attention Mechanism
• Advanced NLP - Introduction to Transformers
• "Fundamentals of Generative AI, ChatGPT & Prompt Engineering using Non Reasoning, Chain of Thought & Advanced Techniques"
• Product Development using OpenAI APIs, Fine Tuning using STaR technique in Python
• Integrating speech using Whisper API and application deployment using Flask
• Fundamentals of Multimodal LLMS like Stable Diffusion, Mid Journey
• "Fundamentals of Design, Photography & Product Development using Stable Diffusion in Python & Applications of LLMs for Data Science problems like clustering, classification"
• GenAI Project
• Applications of LLMs to Create Embeddings for Large Documents
• Applications of Vector stores like Pinecone to store and index embeddings of large documents
• Understand the importance of LangChain and its applications
• Initialize the agents, tools and vector store for storage and retrieval
• Connect the components using Chain and explore the power of tools in LangChain
• Scale and Deploy Generative AI Apps using Azure OpenAI services
• Future Developments in Generative AI

Capstone

• Capstone

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 feeds 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 modeling for Financial activities and Investment Banking

By completing this program, you will: 

• Master AI and ML concepts with industry-relevant applications 
• Build and deploy AI models for real-world use cases 
• Gain expertise in deep learning, NLP, and computer vision 
• Develop hands-on experience with 10+ ML/AI projects 
• Advance your career with globally recognized credentials from LJMU 

After completing this program, you can explore roles such as: 

• Master AI and ML concepts with industry-relevant applications 
• Build and deploy AI models for real-world use cases 
• Gain expertise in deep learning, NLP, and computer vision 
• Develop hands-on experience with 10+ ML/AI projects 
• Advance your career with globally recognized credentials from LJMU 

This program is ideal for: 

• Working professionals looking to transition into AI/ML roles 
• Software engineers and developers aiming to specialize in AI-driven solutions 
• Data scientists and analysts seeking advanced knowledge in deep learning and AI 
• STEM graduates eager to build expertise in machine learning and AI applications