#Course-materials
Showing 28 of 28 repositories tagged #course-materials, ranked by stars
This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.
A course in reinforcement learning in the wild
Web site for www.py4e.com and source to the Python 3.0 textbook
DL course co-developed by YSDA, HSE and Skoltech
USC urban data science course series in Python
Lecture notes, tutorial tasks including solutions as well as online videos for the reinforcement learning course hosted by Paderborn University
A learning management system using django web framework. Course add and drop, grade and assessment result management, online quiz, report generator, student and lecturers management, dashboard, and so much more...
Course materials for: Geospatial Data Science
Probability and Statistics for Data Science: A self-contained introduction to probability and statistics for data science, including a free pdf, 103 Python notebooks using 23 real-world datasets, 118 videos with slides, and solutions to 200 exercises
Machine learning course materials.
π A compilation of everything that I learn; Computer Science, Software Development, Engineering, Math, and Coding in General. Read the rendered results here ->
Course about deep learning for computer vision and graphics co-developed by YSDA and Skoltech.
Course notes for Data Science related topics, prepared in LaTeX
Computer vision and Deep learning
Course materials for: Introduction to Data Science and Programming
Course materials for Dartmouth Course: Storytelling with Data (PSYC 81.09).
Course Material for the machine learning in financial context bootcamp
An Introduction to Programming in Python
Course materials for Introduction to Computational Literary Analysis, taught at UC Berkeley in Summer 2018, 2019, and 2020, at Columbia University in Fall 2020, and again at UC Berkeley in Summer 2021 and 2022.
Data Science and Matrix Optimization course
A course on Deep Reinforcement Learning in Computer Vision. Visit Website:
Short undergraduate course taught at University of Pennsylvania on computational and theoretical neuroscience. Provides an introduction to programming in MATLAB, single-neuron models, ion channel models, basic neural networks, and neural decoding.
εδΊ¬θͺη©Ίθͺ倩倧ε¦θͺε¨εδΈδΈθ―Ύη¨θ΅ζ BUAA Course Material of Major in Automation
Master AI prompting for business innovation. O'Reilly Live Learning course by Tim Warner covering ChatGPT, Claude, Copilot, and enterprise prompt engineering with MCP implementation.
Penetration Testing with Golang
Learn to build, test, and deploy production-ready AI agents with this complete "From Zero to Hero" training course for the Google Agent Development Kit (ADK).
Programming in Python and Fundamentals of Software Development - Summer 2017
A course to learn how to code a mobile app - for complete beginners