Teaching Material

Micro-Lectures

Basic Concepts:

Title	PDF Link	Youtube Link
Introduction to ML	Introduction to ML	Introduction to machine learning
Classification	Classification 1 Classification 2 Classification 3	Classification I Classification II Classification III
Regression	Regression analysis quide	Regression Analysis Guide
Clustering	Clustering	Clustering
Time-Series Forecasting	Time Series Forecasting	Time-Series Forecasting
Computer Vision		Computer vision – Part I Computer vision – Part II Computer vision – Part III Computer vision – Part IV Computer vision – Part V Computer vision – Part VI Computer vision – Part VII
Installing Python & using it	Installing Python	Installing Python
Introduction to Git	Introduction to Git	Introduction to Git

Data Preprocessing:

Title	PDF Link	Youtube Link
Feature Selection & Engineering	Feature Engineering	Feature Engineering
Data Preparation & Visualization	Data Preparation (for tabular data)	Data preparation (for tabular data)
Hyperparameter Tuning	Hyperparameter Tuning	Hyperparameter Tuning
Evaluation Metrics	Evaluation metrics	Evaluation metrics

Machine Learning Frameworks:

Title	PDF Link	Youtube Link
Explainability & Interpretability	Interpretability	Interpretability I Interpretability II Interpretability III
Fairness in ML	Fairness in Machine Learning	Fairness in Machine Learning
Low Code No Code ML	Low code 1 Low code 2 No code	Low code I – Model creation Low code II – Model evaluation No code

Machine Learning Algorithms:

Title	PDF Link	Youtube Link
Neural Networks		Neural networks – Part I Neural networks – Part II Neural networks – Part III Neural networks – Part IV Neural networks – Part V Neural networks – Part VI Neural networks – Part VII Neural networks – Part VIII
Random Forest	Random Forest	Random Forest
XGBoost	XGBoost	Introduction to XGBoost Algorithm
LightGBM	LightGBM	LightGBM
Time-Series Methods	Forecasting Methods	Forecasting Methods
Large Language Models		Large language models – Part I Large language models – Part II Large language models – Part III Large language models – Part IV Large language models – Part V Large language models – Part VI Large language models – Part VII

In addition to the lecture materials, a glossary of key terms is provided to support understanding and offer quick reference.
Download Glossary