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Structured step-by-step learning paths from beginner to expert
Start from zero and become proficient in AI fundamentals
Learn Python from scratch
AI concepts, history and applications
Core algorithms and data handling
Master AI model communication
Build and deploy a real AI project
From programmer to professional AI app developer
NumPy, Pandas and ML Basics
Advanced algorithms and model optimization
LLMs, RAG and their applications
Build full AI applications
Deploy and run AI applications
Build a complete AI app for portfolio
Master every aspect of Claude and build advanced workflows
Claude interface and core features
Advanced prompting techniques and professional framework
Using Claude Code for software development
Model Context Protocol and extending Claude
Build a complete product from idea to deployment
From local development to AI cloud infrastructure
Linux fundamentals and containers
Core cloud concepts across providers
Bedrock, SageMaker, and model deployment
Managing model lifecycle in production
Securing AI cloud infrastructure
Design and deploy a complete architecture
Using AI to transform business and boost productivity
Best AI tools for productivity boost
Automate repetitive tasks with Make and Zapier
Using Claude for business tasks
Building an AI strategy for your organization
Deploy, manage, and monitor ML models in production
What is MLOps and why we need it
DVC and MLflow for model tracking
Deploying ML models as APIs
Performance monitoring and data drift
Continuous integration and deployment pipelines for models
Build a full MLOps pipeline end-to-end
Master prompt engineering from scratch to pro — from Zero-shot to AI agents
Definition of a prompt and how humans communicate with AI models
Ask the model to perform a task directly without prior examples
Provide a few examples to the model to improve output quality
Guide the model to think step-by-step for complex problem solving
Give the model a specific role or persona for specialized output
Request structured output (JSON/Markdown/table) from the model
Write prompts that work with context retrieved from knowledge bases
Design prompts for multi-step agents with tool use
Measure prompt quality and improve it systematically