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Browse our AI-tutored courses with spaced repetition. Each course includes interactive lessons, review schedules, and progress tracking.
Python Programming, Fundamentals
Learn Python from scratch — master variables, data types, control structures, and basic collections with hands-on examples.
A Whirlwind Tour of Python
Python fundamentals covering syntax, variables, operators, built-in types, data structures, and control flow.
Python Programming, Intermediate Concepts
Master intermediate Python concepts including functions, data structures, error handling, OOP, and file operations with practical examples and real-world applications.
Unit Testing with C#
Write trustworthy, maintainable tests, work with isolation frameworks, handle legacy code in C#.
Statistical Inference with R
A practical introduction to data analysis that covers visualization, wrangling, and linear modeling using R and the tidyverse.
Bayesian Statistics with Python
Practical Python programming and real-world case studies guide the transition from basic probability rules to multi-dimensional parameter estimation.
Econometrics with R
Bridge the gap between mathematical theory and practical code by applying rigorous econometric models to real-world data in R.
Econometrics with Python
The intersection of economic theory and modern data science. Handle real-world datasets and perform rigorous analysis, from regression techniques to time-series forecasting using Python.
Data Science with Python
An introduction to data science in Python, covering the foundations of NumPy, data manipulation with Pandas, visualization using Matplotlib and Seaborn, and machine learning workflows with Scikit-Learn.
Computational Cognitive Neuroscience
An exploration of the computational mechanisms of the brain, from biological neurons to artificial neural networks. Learn how distributed processing, learning algorithms, and functional brain architecture combine to create perception, memory, and intelligent behavior.