Comprehensive list of core software engineering, analytics, AI modeling, and hardware circuit courses.
Syntax, loops, structured data types, file handling, OOP models, and algorithm writing.
Pandas, NumPy, Matplotlib, exploratory data analysis (EDA), data cleaning, and regression paradigms.
Supervised and unsupervised models, SVMs, decision trees, neural network logic, and model tuning.
Multilayer perceptrons, backpropagation, CNNs, RNNs, transformers, and sequence classification.
Image matrices, edge detections, spatial filtering, object detections, and CNN applications.
Circuits parameter, microcontroller configurations, signal processes, control systems, and in-person lab experiments.
Practice Python coding problems, machine learning foundations math, and circuits formulas in a timed simulator environment.