📚 Syllabus & Course Curriculum
Data Science & Analytics
Module-by-module breakdown of Brain-Computer Interface: P300 Signal Analytics and Classification, from foundations to a certified capstone project.
Outline
Discover fundamentals of Brain‑Computer Interfaces and real‑world applications • Examine EEG signal basics and neural response patterns • Visualize raw EEG data and identify P300 components in Google Colab
Outline
Apply filtering, artifact removal, and normalization techniques • Extract time‑domain and frequency‑domain features for P300 detection • Prepare clean datasets ready for classification modeling
Outline
Implement classification algorithms (LDA, SVM, Random Forest, Deep Learning) • Evaluate model performance using accuracy, precision, recall, and confusion matrices • Explore real‑world BCI use cases such as assistive devices and cognitive research
Earn government-registered certification in Brain-Computer Interface: P300 Signal Analytics and Classification
e-Certificate and e-Marksheet issued on successful completion.
