Machine Learning and Applied AI

[COURSE INCOMPLETE]

Installfest Guides

Name of Guide Required Before Start of Course Description
Tech Setup Guide No Guide for installing and configuring tools required for the machine learning and applied AI labs.

Pacing Guide

None

Content

Module name Type Duration About
Data Science Lifecycle Lecture 120 min Introduction to the overall data science process.
Framing a Data Science Problem Lecture 120 min Identifying, scoping, and translating problems into data science workflows.
Deep Learning Computer Vision Lecture/Lab 120 min Overview of machine learning libraries and toolchains such as scikit-learn, pandas, and PyTorch.
Building and Optimizing Neural Networks with Pytorch Lecture/Lab 120 min Build and optimize neural networks using PyTorch.
Neural Network Architectures Lecture 120 min Explore key neural network architectures such as feedforward networks, CNNs, and RNNs.
Lab: Feedforward Neural Network Lab 120 min Hands-on implementation of a feedforward neural network.
Foundations of Modern NLP Lecture 120 min Introduction to natural language processing and modern NLP approaches.
Pipelines Lecture/Lab 60 min Build end-to-end NLP pipelines.
Transformers Lecture/Lab 120 min Understand transformer architectures and how they are used in modern AI systems.
Evaluating NLP Models Lecture/Lab 90 min Techniques for evaluating and fine-tuning NLP and LLM models.
NLP Lab Lab 120 min Practical NLP exercises applying the concepts learned in earlier modules.
AI Engineering: Prompt Engineering Lecture/Lab 120 min Learn how to craft effective prompts for generative AI systems.
AI Engineering: Fundamentals of Chaining Lecture/Lab 120 min Build multi-step AI workflows by chaining prompts and tools.
AI Engineering: Vector Databases and QA Lecture/Lab 120 min Use vector databases for retrieval-augmented question answering systems.
Total content Total ~26 hours  

Projects

Module name About
LLM and AI Project Capstone project integrating concepts from the course into a practical AI or LLM application.