IIIT Online Courses in IIIT PG Certificate In AI and ML Course Subjects/Syllabus

Course 1

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

Course 2

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

Course 3

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

Course 4

• Introduction to Neural Networks - Part 1
• Introduction to Neural Networks - Part 2
• Assignment: Convolutional Neural Networks
• Convolutional Neural Networks
• Recurrent Neural Networks
• Gesture Recognition - Project
• Revision week - Skill test (DL)
• Weekly Test

Course 5

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

Capstone Project

Generative AI Elective

• Fundamentals of Generative AI, ChatGPT & Prompt Engineering using Non Reasoning, Chain of Thought & Advanced Techniques
• Integrating speech using Whisper API and application deployment using Flask
• Fundamentals of Multimodal LLMS like Stable Diffusion, Mid Journey
• Product Development using OpenAI APIs, Fine Tuning using STaR technique in Python
• Fundamentals of Design, Photography & Product Development using Stable Diffusion in Python & Applications of LLMs for Data Science problems like clustering, classification
• Applications of Vectorstores like Pinecone to store and index embeddings of large documents
• Applications of LLMs to create Embeddings for Large Documents
• Initialise the agents, tools and vectorstore for storage and retrieval
• Scale and Deploy Generative AI Apps using Azure OpenAI services
• Understand the importance of LangChain and it's importance
• Connect the components using Chain and explore the power of tools in LangChain
• Future Developments in Generative AI

MLOps Elective

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