| Mathematical Foundations for ML (AIMLZC416) | Vector algebra, Gradient descent, & PCA. | ML System Optimization: Using PCA for dimensionality reduction to optimize the performance of the ClickHouse-powered analytics dashboard you built at xyz. |
| Introduction to Statistical Methods (AIMLZC418) | Bayes Theorem, Hypothesis Testing, & Time series analysis. | Inventory Forecasting: Applying ARIMA/SARIMA time series models to your SKU-level inventory API at abc to predict stock-outs with higher statistical significance. |
| Machine Learning (AIMLZG565) | Supervised/Unsupervised Learning & Ensemble methods | Intelligent Fraud Detection: Utilizing Random Forest or SVMs to enhance the real-time reconciliation system designed for upi payments at xyz. |
| Deep Neural Networks (AIMLZG511) | Backpropagation, CNNs, & Transformers. | B2B Communication Intelligence: Using Transformer-based NLP models to extract intent and automate tracking from the Order Notes API you designed. |
Techglot 