AI Roadmap 2026

Simple, Clear, and Example-Driven

STAGE 0

📐 Foundations

Programming
Python Basics
Variables, loops, functions, OOP
💡 Example: Automate tasks, manipulate data with pandas
Data
Data Structures
Organize data efficiently
💡 Example: Arrays for lists, trees for decisions, graphs for networks
Logic
Algorithms
Step-by-step problem solving
💡 Example: Sort prices, search large datasets quickly
STAGE 1

🤖 Machine Learning

Core
ML Basics
Training, testing, accuracy, choosing algorithms
💡 Example: Predict house prices, classify spam emails
Supervised
Labeled Learning
Teach AI with examples
💡 Example: Spam/not spam email classifier
Unsupervised
Pattern Discovery
Find structure without labels
💡 Example: Group customers by shopping habits
STAGE 2

🧠 Deep Learning

Neural Nets
Neural Networks
Inspired by the brain, layers learn from data
💡 Example: Recognize digits, classify images
Architectures
CNN, RNN, LSTM
CNN=images, RNN=text/sequences, LSTM=long-term patterns
💡 Example: CNN detects objects, RNN predicts words, LSTM forecasts stocks
Tools
PyTorch / TensorFlow
Frameworks to build/train models
💡 Example: Face recognition system, recommendation engine
STAGE 3

🚀 Advanced AI

NLP
Large Language Models
AI that understands & writes language
💡 Example: ChatGPT writes essays, answers questions
Vision
Computer Vision
AI sees and interprets images/videos
💡 Example: Detect pedestrians, recognize objects in photos
Multimodal
Vision+Language Models
Understand images & text together
💡 Example: Describe photos, answer image questions
STAGE 4

⚙️ MLOps & Deployment

DevOps
MLOps
Manage models in production
💡 Example: Track model versions, retrain automatically
Container
Docker
Package models to run anywhere
💡 Example: Deploy chatbot to any server without issues
Automation
CI/CD
Automate testing & deployment
💡 Example: Update model code → auto test & deploy
Data
Data Pipelines
ETL: collect, clean, transform data
💡 Example: Daily update of user data for recommendations
Cloud
AWS / Cloud
Train & deploy AI at scale
💡 Example: Serve predictions to millions of users

🎯 Start from Stage 0 and progress systematically • Practice with real projects at each stage