Linear algebra, calculus, descriptive statistics, probability models

Data structures, vector operations, matrices, indexing styles

Querying complex data tables with relational expressions

Data cleaning, normalization, transformation, managing missing figures

Building, training, hyper-tuning, and evaluating neural network layers

Implementing linear regression, classification models, and tree variants

Dimensionality reduction techniques and clustering algorithm parameters

Processing high-volume pipelines using distributed computing clusters

Building, training, hyper-tuning, and evaluating neural network layers

Deploying an active machine learning model for business forecasting