Practical applications of Python for data analysis, machine learning, and computational modeling, including real-world problems in biology, networks, and complex systems.
Tools: Python · NumPy · Pandas · Machine Learning Libraries
Applications: AI · Bioinformatics · Network Analysis · Data Science
Focus: Data Analysis · Machine Learning · Scientific Computing · Complex Systems
Level: Undergraduate / Graduate
Introduction to data manipulation, cleaning, and analysis using Python.
Access materialsSimple segmentation and modeling techniques for structured data.
Access materialsAlgorithms for comparing biological sequences and detecting similarities.
Access materialsIntroduction to learning through interaction and reward-based systems.
Access materialsFoundations of neural computation and basic architectures.
Access materialsRecurrent neural networks for associative memory and pattern storage.
Access materialsGraph-based analysis of neural connectivity using Python.
Access materials Download datasetDynamic modeling of neural connectomes using ordinary differential equations to analyze activity propagation and network behavior.
Access materials Download dataset