cs_notes

This notes was automatically generated by AI

ASU

• ASU CSE365 - Fall 2022
• ASU CSE466 - Fall 2021

CMU

• 15-213 15-513 Introduction to Computer Systems
• 15 418 Parallel Computer Architecture and Programming 2016 SP
• CMU Intro to Database Systems 15-445 645 Fall 2022

Cambridge

• Information Theory Pattern Recognition and Neural Networks

CrashCourse

• Computer Science

DeepLearning_AI

• Machine Learning Specialization by Andrew Ng

The_Deep_Learning_Specialization

• 1 Neural Networks and Deep Learning
• 2 Improving Deep Neural Networks Hyperparameter Tuning Regularization and Optimization
• 3 Structuring Machine Learning Projects
• 4 Convolutional Neural Networks
• 5 Sequence Models

HUJI

• Nand To Tetris 1
• Nand To Tetris 2

Harvard

• CS50 s Introduction to Artificial Intelligence with Python 2023

Khan

• Complex Variables and Functions
• Partial Differential Equations

MIT

• 18 01 Single Variable Calculus
• 18 02SC Homework Help for Multivariable Calculus
• 18 06 Linear Algebra Spring 2005
• 6 0002 Introduction to Computational Thinking and Data Science Fall 2016
• 6 S081 Operating System Engineering
• IAP 2023
• Information Theory Pattern Recognition and Neural Networks
• MIT 18 03SC Differential Equations Fall 2011
• MIT 6 003 Signals and Systems Fall 2011
• MIT 6 006 Introduction to Algorithms Spring 2020
• MIT 6 033 Computer System Engineering Spring 2005
• MIT 6 046J Design and Analysis of Algorithms Spring 2015
• MIT 6 824 Distributed Systems Spring 2020
• Missing Semester IAP 2020
• Qiqi Wang-Numerical Methods MIT
• numerical analysis

Stanford

• CS110 Principles of Computer Systems Spring 2019
• CS231n Convolutional Neural Networks for Visual Recognition
• Convex Optimization I
• Convex Optimization II
• Mining Massive Datasets - Stanford University
• Stanford CS224N Natural Language Processing with Deep Learning Winter 2021
• Stanford CS224W Machine Learning with Graphs
• Stanford CS229 Machine Learning
• cs107 Programming Paradigms
• cs144 Introduction to Computer Networking

UCB

• CS61C Great Ideas in Computer Architecture
• CS 162 Operating Systems and Systems Programming - Berkeley
• CS 285 Deep Reinforcement Learning Fall 2022 UC Berkeley
• CS 61B - Data Structures - Jonathan Shewchuk - UC Berkeley
• EECS 20N - Structure and Interpretation of Signals and Systems - Babak Ayazifar - UC Berkeley
• EECS 70 Discrete mathematics and probability theory
• Introduction to number theory
• UCB CS70 discrete Math and probability theory
• UC Berkeley CS186 Intro to DB Systems Playlist
• UC Berkeley CS 188 Introduction to Artificial Intelligence Fall 2018
• UC Berkeley Data 100 Su19 Lectures

other

• Algorithms Robert Sedgewick
• CS106B Programming Abstraction in CPP
• CS170 Spring 2020
• Cryptography Lecture Series
• Deep Learning for Computer Vision UMich EECS 498-007

washington

• CSE 143 Spring 2021