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What is AI

Complete foundations course covering AI concepts from basics to advanced applications. Hands-on chapters with labs, quizzes, and Ollama experiments.

142 chaptersFirst 2 chapters free to preview

After this course, you'll be able to:

Explain AI concepts to anyone — team, boss, or client
Understand neural networks, transformers, and tokenization
Build 5 real projects: image classifier, NLP analyzer, RAG chatbot, AI agent, production deploy
Know which AI approach to use for any business problem

Full syllabus

1

Pattern Recognition Basics

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2

Types Of AI And Common Myths

3

Your First Local AI Conversation

4

AI Learning Journey

5

Three Ways AI Learns

6

Training In Practice

7

Attention Mechanism

8

Multi Head Attention And Context

9

How GPT Generates Text

10

Understanding Model Sizes

11

Choosing And Running Models

12

Tokenization Basics

13

Embeddings And Token Impact

14

Neurons Layers And Depth

15

Training Networks And Types

16

Dataset Strategy And Sources

17

Dataset Formats Code And Practice

18

Training Loop And Hyperparameters

19

Training Code And Ollama Export

20

Fine Tuning

21

Local Vs Cloud

22

Real World AI

23

Your AI Journey

24

Appendices

25

Prompt Engineering Fundamentals

26

Getting Started With Ollama

27

Understanding AI Bias

28

Measuring Fairness And Building Fair AI

29

AI Environmental Impact Understanding

30

AI Environmental Impact Reducing

31

AI Laws And Regulations

32

Visual Aids And Diagrams

33

Interactive Exercises Labs

34

Interactive Exercises Projects And LocalAI

35

Real World Case Studies

36

Practical Tools Platforms

37

Practical Tools Prompts Pricing

38

Community Online Groups

39

Community Books Courses Plan

40

AI 2025 Models Hardware

41

AI 2025 Jobs Tools Future

42

Learning Paths Summaries

43

Learning Paths FAQ Glossary

44

Dataset Creation Basics

45

Dataset Creation Practice

46

AI Limitations

47

RLHF How AI Became Helpful

48

AI Safety Spotting Protecting

49

AI Safety Deepfakes Checklist

50

Making Money Services Pricing

51

Making Money Examples Scaling

52

Technical Prerequisites Setup

53

Technical Prerequisites Troubleshooting

54

Healthcare AI Overview And HIPAA

55

Healthcare AI Clinical Applications

56

Healthcare AI Implementation And Local

57

Education AI Lesson Planning

58

Education AI Assessment And Personalization

59

Education AI Implementation And Local

60

Small Business AI Customer Service

61

Small Business AI Marketing And Sales

62

Small Business AI Operations And Local

63

Creator AI YouTube

64

Creator AI Podcasts And Blogs

65

Creator AI Social And Monetization

66

Legal AI Contracts

67

Legal AI Research And Drafting

68

Legal AI Ethics And Local

69

AI For Real Estate

70

AI For Finance Accounting

71

AI Ecommerce Products Pricing Service

72

AI Ecommerce Marketing Cases

73

Marketing Agency AI Production

74

Marketing Agency AI Reporting And Pricing

75

AI For Software Developers

76

Dataset Versioning And Labeling

77

Dataset Leakage And Splits

78

Dataset Augmentation And Documentation

79

Beginner Foundations AI And Models

80

Beginner Foundations Training And Overfitting

81

Beginner Foundations Metrics Loss Optimizers

82

Beginner Foundations Features And Pipeline

83

Classical ML Linear Models

84

Classical ML Tree Models

85

Classical ML SVM Clustering PCA

86

RAG Embeddings And Vector Databases

87

RAG Pipeline And Advanced

88

RAG Production Patterns

89

RAG Evaluation And Optimization

90

MLOps Tracking And Versioning

91

MLOps Docker Containerization

92

MLOps Kubernetes And CICD

93

MLOps Monitoring And AB Testing

94

MLOps Feature Stores And Best Practices

95

Tools Decision Framework And LLM Comparison

96

Tools OSS VS SAAS And Comparisons

97

Tools ADRs And Quick Reference

98

Math Vectors And Matrices

99

Math Calculus And Backpropagation

100

Math Probability And Statistics

101

Multimodal AI Primer

102

System Design Online Offline Streaming

103

System Design Serving And Scaling

104

System Design Caching And Checklist

105

Project Image Classifier Setup

106

Project Image Classifier Data

107

Project Image Classifier Models

108

Project Image Classifier Training

109

Project Image Classifier API

110

Project Image Classifier Deploy

111

Project NLP Setup And Data

112

Project NLP Models

113

Project NLP Training And API

114

Project RAG Configuration

115

Project RAG Document Loaders

116

Project RAG Chunking

117

Project RAG Embeddings

118

Project RAG Vector Stores

119

Project RAG Retrieval

120

Project RAG LLM And Memory

121

Project RAG Chain And Pipeline

122

Project RAG API And UI

123

Project RAG Evaluation And Deployment

124

AI Agents Conceptual Primer

125

Project Agent Core

126

Project Agent Tools

127

Project Agent ReAct And Plan

128

Project Agent MultiAgent And Safety

129

Project Agent API And Examples

130

Project Production Setup

131

Project Production MLflow Training

132

Project Production Serving

133

Project Production Monitoring

134

Project Production Docker K8s CICD

135

Project Production AB Testing And Examples

136

Interview ML Fundamentals Part1

137

Interview ML Fundamentals Part2

138

Interview Deep Learning

139

Interview Statistics

140

Interview System Design

141

Interview Coding Challenges

142

Interview Behavioral Cheatsheets StudyPlan

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