1. Introduction to the functional data analysis. 2. Tools for exploring functional data: a. Functional mean and variance. b. Covariance and correlation functions. c. Cross-covariance and cross-correlation functions. 3. From functional data to smooth functions: a. Basis functions. b. Smoothing functional data by least-squares. c. Smoothing functional data with a roughness penalty. 4. Principal component analysis for functional data: a. Defining functional PCA. b. Visualizing the results. c. Computational methods for functional PCA. d. Regularized PCA. 5. Regression for functional data: a. Functional linear models with scalar responses. b. Functional linear models with functional responses. 6. Supervised classification for functional data: a. k-nearest neighbors. 7. Unsupervised classification for functional data 1. k-means.