New graduate students working in diffusion MRI and researchers/clinicians seeking to know the basic principles of diffusion tractography.The audience will learn the basic principles of diffusion tractography and be cautious of the limitations of current methods. In particular, the audience will learn the difference between Diffusion Tensor Imaging (DTI) and High Angular Resolution Diffusion Imaging (HARDI) tracotgraphy, from both a deterministic and probabilistic point of view.The purpose is to perform robust fiber tractography that is necessary in many neuroscience applications. At the era of human connectomics studies, it is important to know how to go from HARDI acquisition to whole brain tractography and be aware of the current pitfalls and limitations of the techniques.Several methods will be presented: i) Algorithms to reconstruct the local diffusion phenomenon at every voxel. ii) Deterministic and probabilistic fiber tracking algorithms. iii) Visualisation techniques and post-processing of tractography results.The impact of the methods mentioned above will be shown on healthy brain datasets and in neurosurgical applications. Some results can be found here: http://scil.dinf.usherbrooke.ca.A special attention will be given to the pitfalls and limitations of the methods, and also, to the false interpretations that can be made from the diffusion metrics and tractography results. Validation is a bottleneck for the diffusion MRI community and will be discussed (see http://tractometer.org).