1.
Home
2.
Introduction: Learning AI the Hard Way
3.
Universal Learning Priority Legend
4.
The Math
5.
Basic Algebra & Pre-Calculus
6.
Logic & Proofs
6.1.
Boolean Algebra
6.2.
Propositional Logic
7.
Sets & Functions
7.1.
Relations
7.2.
Equivalence Relations
8.
Graph Theory
8.1.
Trees & Networks
8.2.
Algorithms on Graphs
9.
Combinatorics
9.1.
Counting Principles
9.2.
Permutations & Combinations
10.
Single Variable Calculus
10.1.
Derivatives
10.2.
Integrals
11.
Multivariable Calculus
11.1.
Partial Derivatives
11.2.
Multiple Integrals
11.3.
Vector Fields
12.
Gradient & Divergence
13.
Curl & Del Operator
14.
Line & Surface Integrals
15.
Green's & Stokes' Theorems
16.
Matrices & Determinants
16.1.
Matrix Operations
16.2.
Gaussian Elimination
17.
Vector Spaces
17.1.
Linear Independence
17.2.
Basis & Dimension
18.
Eigenvalues & Eigenvectors
18.1.
Diagonalization
18.2.
Singular Value Decomposition
19.
Inner Products & Orthogonality
19.1.
Gram-Schmidt Process
20.
Matrix Decompositions
20.1.
LU/QR/Cholesky
21.
Tensor Algebra
22.
Probability Theory
22.1.
Random Variables
22.2.
Distributions
22.3.
Bayes' Theorem
22.4.
Central Limit Theorem
22.5.
Markov Chains
23.
Statistics
23.1.
Descriptive Statistics
23.2.
Hypothesis Testing
23.3.
Confidence Intervals
23.4.
Regression Analysis
23.5.
ANOVA
24.
Optimization Theory
24.1.
Convex Optimization
24.2.
Gradient Descent
24.3.
Lagrange Multipliers
24.4.
Constrained Optimization
24.5.
Linear Programming
25.
Real Analysis
26.
Complex Analysis
27.
Differential Equations
28.
Fourier Analysis
29.
Information Theory
30.
Terminal/Command Line Basics
31.
Git Version Control
32.
SSH & Key Management
33.
Shell Scripting
34.
tmux & Terminal Multiplexing
35.
VS Code Setup
36.
Vim/Neovim
37.
Emacs/Spacemacs
38.
Package Managers
38.1.
pip & virtualenv
38.2.
conda & mamba
38.3.
System Package Managers
39.
Containerization
39.1.
Docker
39.2.
Docker Compose
39.3.
Kubernetes
40.
IDE/Editor Setup
40.1.
Debugger
40.2.
Linting & Code Formatting
40.3.
Testing Frameworks
41.
Jupyter Notebook/Lab
42.
API Testing Tools
43.
Database Tools
44.
GitHub Actions
45.
Jenkins & CI/CD
46.
Advanced DevOps & Monitoring
47.
Programming Logic & Thinking
48.
Variables & Data Types
49.
Control Flow
50.
Functions
51.
Python
52.
JavaScript
53.
Java
54.
C/C++
55.
Other Languages
56.
Basic Data Structures
56.1.
Arrays/Lists
56.2.
Strings
56.3.
Dictionaries/Maps
57.
Intermediate Data Structures
57.1.
Stacks & Queues
57.2.
Sets
57.3.
Linked Lists
57.4.
Trees & Graphs
58.
Basic Algorithms
58.1.
Searching Algorithms
58.2.
Sorting Algorithms
58.3.
Algorithm Complexity
59.
OOP Fundamentals
59.1.
Classes & Objects
59.2.
Methods & Attributes
59.3.
Encapsulation
60.
Advanced OOP Concepts
60.1.
Inheritance
60.2.
Polymorphism
60.3.
Abstraction
61.
File Operations
62.
Error Handling
63.
Debugging Techniques
64.
Code Organization
65.
External Libraries
66.
Package Management
67.
Database Concepts
68.
ACID Properties
69.
Database Design
70.
Basic SQL
71.
Advanced SQL
72.
Database Functions
73.
Query Optimization
74.
PostgreSQL
75.
MySQL
76.
SQLite
77.
Database Administration
78.
Document Databases
78.1.
MongoDB
78.2.
CouchDB
79.
Key-Value & Column Stores
79.1.
Redis
79.2.
Apache Cassandra
80.
Graph Databases
80.1.
Neo4j
81.
Data Warehousing
82.
Big Data Technologies
82.1.
Apache Hadoop
82.2.
Apache Spark
82.3.
Apache Kafka
83.
Cloud Data Platforms
84.
AI-Specific Storage
84.1.
Vector Databases
84.2.
Time Series Databases
84.3.
Feature Stores
85.
Data Manipulation & Analysis
85.1.
NumPy
85.2.
Pandas
85.3.
Data Cleaning
86.
Data Visualization
86.1.
Matplotlib
86.2.
Seaborn
86.3.
Plotly
87.
Exploratory Data Analysis
88.
ML Concepts & Theory
89.
Scikit-Learn Ecosystem
89.1.
Linear & Logistic Regression
89.2.
Decision Trees & Random Forest
89.3.
Classification Metrics
90.
Clustering & Unsupervised Learning
90.1.
K-Means
90.2.
Hierarchical Clustering
90.3.
PCA & Dimensionality Reduction
91.
Neural Network Basics
91.1.
Perceptron
91.2.
Activation Functions
91.3.
Backpropagation
92.
Deep Learning Frameworks
92.1.
TensorFlow/Keras
92.2.
PyTorch
92.3.
JAX
93.
Specialized Architectures
93.1.
Convolutional Neural Networks
93.2.
Recurrent Neural Networks
93.3.
Transformers
94.
Model Deployment
95.
Model Monitoring
96.
Advanced MLOps
97.
Computer Vision
97.1.
OpenCV
97.2.
Image Processing
97.3.
Object Detection
98.
Natural Language Processing
98.1.
Text Preprocessing
98.2.
Word Embeddings
98.3.
Named Entity Recognition
99.
Reinforcement Learning
99.1.
Q-Learning
99.2.
Policy Gradient
99.3.
Actor-Critic
100.
Modern Neural Networks
100.1.
Attention Mechanisms
100.2.
Transformers
100.3.
Self-Attention
101.
Large Language Models
101.1.
BERT Family
101.2.
GPT Family
101.3.
T5/UL2
102.
Advanced Vision Models
102.1.
Vision Transformer
102.2.
CLIP
102.3.
Generative Vision Models
103.
Advanced Optimization
104.
Advanced Training Techniques
105.
Theoretical Foundations
106.
Generative AI
106.1.
GANs
106.2.
VAEs
106.3.
Diffusion Models
107.
Multimodal AI
108.
Advanced RL & Control
109.
Research Methodology
110.
Advanced Implementation
111.
Industry & Impact
112.
Frontier Research
113.
Next-Generation AI
114.
AGI Research
115.
Technical Communication
116.
Team Collaboration
117.
Presentation Skills
118.
Analytical Thinking
119.
Creative Problem Solving
120.
Decision Making
121.
Business Acumen
122.
Domain Expertise
123.
Project Management
124.
Learning Mindset
125.
Adaptability
126.
Teaching & Knowledge Sharing
127.
Networking & Relationships
128.
Leadership & Influence
129.
Career Strategy
130.
Recommended Books
131.
Online Courses
132.
Research Papers
133.
Useful Links
134.
Contributing Guidelines
135.
License
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