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Zero-to-Expert Tutorial

AI and Machine Learning Complete Learning Path

Artificial intelligence and machine learning use data, algorithms, neural networks, and modern foundation models to build systems that learn patterns or generate useful outputs.

  • Starts from zero
  • 101 lessons
  • 16 modules
  • 6 projects
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Begin From ZeroNo prior subject knowledge is assumed.
Ordered ModulesFollow the curriculum in order without skipping prerequisites.
Complete ProjectsPlan, build, integrate, test, and refine real outcomes.
Direct Lesson AccessEvery curriculum item links directly to its lesson.
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About this tutorial

Learn AI and Machine Learning from the beginning

Artificial intelligence and machine learning use data, algorithms, neural networks, and modern foundation models to build systems that learn patterns or generate useful outputs.

This continuous 101-lesson curriculum starts from zero, introduces every required tool and concept in order, and progresses through Prerequisites, Mathematics Foundations for Machine Learning, First Model, Workflow, Machine Learning Foundations, Supervised Learning before capstone work.

Who this tutorial is for

Beginners with no prior ML experience and developers progressing toward deep learning, LLM applications, evaluation, and MLOps.

Prerequisites

No previous AI and Machine Learning experience is required. The opening curriculum begins with “What Artificial Intelligence Machine Learning and Deep Learning Mean” and introduces setup, accounts, software, terminology, and prerequisite checkpoints before advanced work.

Master curriculum

Complete AI and Machine Learning Tutorial

Follow all 101 lessons in exact curriculum order. Open any lesson directly from the curriculum below and follow the modules in order.

Module 1

Start Here

2 lessons · Start from Zero

Module 2

Prerequisites

1 lessons · Start from Zero

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Module 3

Mathematics Foundations for Machine Learning

18 lessons · Start from Zero

Lesson 4

Read Mathematical Notation Used in Machine Learning

Start from Zero · Comprehensive Tutorial Lesson

Start from ZeroLesson
Lesson 5

Understand Scalars Vectors Matrices and Tensors

Start from Zero · Comprehensive Tutorial Lesson

Start from ZeroLesson
Lesson 6

Perform Basic Vector Operations

Start from Zero · Comprehensive Tutorial Lesson

Start from ZeroLesson
Lesson 7

Understand Dot Products and Similarity

Start from Zero · Comprehensive Tutorial Lesson

Start from ZeroLesson
Lesson 8

Understand Matrices Transposes and Matrix Multiplication

Start from Zero · Comprehensive Tutorial Lesson

Start from ZeroLesson
Lesson 9

Understand Functions Graphs Inputs and Outputs

Start from Zero · Comprehensive Tutorial Lesson

Start from ZeroLesson
Lesson 10

Understand Slopes Rates of Change and Derivatives

Start from Zero · Comprehensive Tutorial Lesson

Start from ZeroLesson
Lesson 11

Understand Partial Derivatives and Gradients

Start from Zero · Comprehensive Tutorial Lesson

Start from ZeroLesson
Lesson 12

Understand the Chain Rule for Neural Networks

Start from Zero · Comprehensive Tutorial Lesson

Start from ZeroLesson
Lesson 13

Understand Probability from Zero

Start from Zero · Comprehensive Tutorial Lesson

Start from ZeroLesson
Lesson 14

Understand Conditional Probability and Bayes Intuition

Start from Zero · Comprehensive Tutorial Lesson

Start from ZeroLesson
Lesson 15

Understand Random Variables and Probability Distributions

Start from Zero · Comprehensive Tutorial Lesson

Start from ZeroLesson
Lesson 16

Calculate Mean Median Variance and Standard Deviation

Start from Zero · Comprehensive Tutorial Lesson

Start from ZeroLesson
Lesson 17

Understand Sampling Populations and Estimation

Start from Zero · Comprehensive Tutorial Lesson

Start from ZeroLesson
Lesson 18

Understand Correlation Covariance and Why Correlation Is Not Causation

Start from Zero · Comprehensive Tutorial Lesson

Start from ZeroLesson
Lesson 19

Understand Loss Functions and Objective Functions

Start from Zero · Comprehensive Tutorial Lesson

Start from ZeroLesson
Lesson 20

Understand Gradient Descent Step by Step

Start from Zero · Comprehensive Tutorial Lesson

Start from ZeroLesson
Lesson 21

Understand Regularization Bias Variance and Overfitting Mathematically

Start from Zero · Comprehensive Tutorial Lesson

Start from ZeroLesson
Module 4

Setup

2 lessons · Start from Zero

Module 5

First Model

5 lessons · Beginner

Module 6

Workflow

2 lessons · Beginner

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Module 7

Machine Learning Foundations

4 lessons · Beginner

Module 8

Supervised Learning

6 lessons · Beginner

Module 9

Unsupervised Learning

6 lessons · Intermediate

Module 10

Model Evaluation and Explainability

6 lessons · Intermediate

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Module 11

Deep Learning

6 lessons · Intermediate

Module 12

NLP Computer Vision and Transformers

6 lessons · Advanced

Module 13

LLM Applications and Generative AI

6 lessons · Advanced

Module 14

MLOps Responsible AI and Production

6 lessons · Professional

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Module 15

Projects and Capstones

24 lessons · Capstone

Project 1 · plan

Project: Understand Requirements and Plan End-to-end classification model

Capstone · Project Lesson

CapstoneLesson
Project 1 · build

Project: Build the Foundation of End-to-end classification model

Capstone · Project Lesson

CapstoneLesson
Project 1 · integrate

Project: Complete and Integrate End-to-end classification model

Capstone · Project Lesson

CapstoneLesson
Project 1 · test

Project: Test Debug Refine and Finish End-to-end classification model

Capstone · Project Lesson

CapstoneLesson
Project 2 · plan

Project: Understand Requirements and Plan Customer segmentation pipeline

Capstone · Project Lesson

CapstoneLesson
Project 2 · build

Project: Build the Foundation of Customer segmentation pipeline

Capstone · Project Lesson

CapstoneLesson
Project 2 · integrate

Project: Complete and Integrate Customer segmentation pipeline

Capstone · Project Lesson

CapstoneLesson
Project 2 · test

Project: Test Debug Refine and Finish Customer segmentation pipeline

Capstone · Project Lesson

CapstoneLesson
Project 3 · plan

Project: Understand Requirements and Plan Explainable risk model

Capstone · Project Lesson

CapstoneLesson
Project 3 · build

Project: Build the Foundation of Explainable risk model

Capstone · Project Lesson

CapstoneLesson
Project 3 · integrate

Project: Complete and Integrate Explainable risk model

Capstone · Project Lesson

CapstoneLesson
Project 3 · test

Project: Test Debug Refine and Finish Explainable risk model

Capstone · Project Lesson

CapstoneLesson
Project 4 · plan

Project: Understand Requirements and Plan PyTorch image classifier

Capstone · Project Lesson

CapstoneLesson
Project 4 · build

Project: Build the Foundation of PyTorch image classifier

Capstone · Project Lesson

CapstoneLesson
Project 4 · integrate

Project: Complete and Integrate PyTorch image classifier

Capstone · Project Lesson

CapstoneLesson
Project 4 · test

Project: Test Debug Refine and Finish PyTorch image classifier

Capstone · Project Lesson

CapstoneLesson
Project 5 · plan

Project: Understand Requirements and Plan RAG knowledge assistant

Capstone · Project Lesson

CapstoneLesson
Project 5 · build

Project: Build the Foundation of RAG knowledge assistant

Capstone · Project Lesson

CapstoneLesson
Project 5 · integrate

Project: Complete and Integrate RAG knowledge assistant

Capstone · Project Lesson

CapstoneLesson
Project 5 · test

Project: Test Debug Refine and Finish RAG knowledge assistant

Capstone · Project Lesson

CapstoneLesson
Project 6 · plan

Project: Understand Requirements and Plan Production ML pipeline with monitoring

Capstone · Project Lesson

CapstoneLesson
Project 6 · build

Project: Build the Foundation of Production ML pipeline with monitoring

Capstone · Project Lesson

CapstoneLesson
Project 6 · integrate

Project: Complete and Integrate Production ML pipeline with monitoring

Capstone · Project Lesson

CapstoneLesson
Project 6 · test

Project: Test Debug Refine and Finish Production ML pipeline with monitoring

Capstone · Project Lesson

CapstoneLesson
Module 16

Finish and Continue

1 lessons · Completion

Ready to begin?

Start at lesson 1 and follow the curriculum in sequence.

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