Live in-person teaching:
Learn neural data analysis in person this summer.
Mathematical programming gives you tools for learning, exploring, and discovering applied mathematics in areas including statistics, data science, and signal processing. This is why I use a combination of traditional instruction (lecture slides, words, diagrams) and hands-on programming in MATLAB and Python when teaching.
Learn neurosience data analysis in Bucharest.
Time series, spectral decomposition, synchronization, statistics.
Matrix analysis, statistical modeling, source separation, dimension reduction, statistics.
4+ hours on using ChatGPT to code, learn about, apply, and communicate data science. This will change your life.
3.5 hours of clear instruction on how to use AI-assisted writing for various tasks. The goal is to use ChatGPT to help you be a better writer.
Use ChatGPT to accelerate your math skills.
Make ChatGPT your virtual tutor to help you learn MATLAB.
57+ hours of instruction on modern deep learning (using PyTorch), with LOTS of exercises and code-challenges to help you hone your DL skills. Includes a Python tutorial.
35 hours of instruction (>50 hours in total, including exercises) on a rigorous deep-dive into statistics and machine learning. All concepts are implemented in Python and MATLAB.
Learn why, when, and how to maximize the quality of your data to optimize data-based decisions.
24+ hours of clear explanations of concepts in linear algebra, including vectors, matrix multiplications, least-squares projections, eigendecomposition, and singular value decomposition.
Over 41 hours of instruction (including a Python intro tutorial). Develop a deep understanding and intuition for calculus. Solve problems and implement algorithms by hand and in Python.
31+ hours of instruction (>50 hours in total, including exercises) on how to use Python as a tool for learning concepts and visualizations in mathematics.
Strong focus on proofs, with coding and applications.
Strong focus on coding and applications, with proofs.
Work-in-progress! Hopefully available by the end of 2023.
12+ hours of instruction about applied signal-processing methods, including filtering, denoising, convolution, resampling, interpolation, and outlier detection.
Theoretical and computational bases of the Fourier transform, and its implementation in modern applications in digital signal processing, data analysis, and image filtering. MATLAB and Python codes are included.
40+ hours of YouTube video lectures that supplement my book "Analyzing Neural Time Series Analysis." Look for NEW ANTS playlists.
Follow-up to the previous course with a lot more exercises and fully explained solutions.
17 hours of instruction on theory, practice, and implementation of dimension-reduction and source-separation methods for multivariate data. MATLAB codes and sample datasets are included. Includes a 3-hour linear-algebra crash-course.
Free 10-hour course on using MATLAB for neuroscience data analysis, featuring various topics including computational modeling, fMRI, EEG, and spiking.
A comprehensive guide to the conceptual, mathematical, and implementational aspects of analyzing electrical brain signals, including data from MEG, EEG, and LFP recordings.
This low-cost book focuses on practical implementations of time-frequency analyses in Matlab/Octave. The book explains time-frequency analyses through written explanations and many figures, rather than through opaque mathematical equations.
32+ hours of instruction (>80 hours in total, including exercises) on using Python for scientific computing. No previous background in Python necessary!
31+ hours of instruction (>50 hours in total, including exercises) on how to use Python as a tool for learning concepts and visualizations in mathematics.
6+ hours of video instruction on getting started with MATLAB, debugging code, and developing a programming style. Learn how ChatGPT can help you learn MATLAB. Ideal for a beginner who needs to get up-to-speed with MATLAB.
40 hours of video instruction on MATLAB programming instruction (longer if you do all the exercises!). Lessons revolve around specific applications in graphics, data analysis, image processing, import/export, and so on.
Learn key image processing techniques including spatial filtering, segmentation, transparency, and histogram equalization. You will also learn to create and program in graphical user interfaces (GUIs).
In this course you will learn how to simulate different kinds of data, including time series and images. Generated data can be used to validate data analysis methods.
This book is designed to bring scientists in psychology, neuroscience, and related fields to intermediate and advanced levels of programming proficiency.
Sincxpress Education SRL is registered in Romania with CIU/CIF 46732489.