Everything in one place — courses, tutorials, articles, and AI tools.
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Machine Learning Fundamentals
beginner • 3 sections
AI Agents from Scratch
Understand what an AI agent really is and build one yourself. Covers tool use, the agent loop, memory, multi-agent patterns, and the guardrails that keep agents safe and affordable.
advanced • 3 sections
AI for Absolute Beginners
Start from zero. Understand what AI really is, how modern models work, and how to use them confidently in everyday life and work — no math or coding required.
beginner • 2 sections
AI Image Generation Studio
A complete beginner-friendly course for planning, prompting, generating, reviewing, and publishing AI images for lessons, tutorials, products, and websites — with a reusable visual workflow from brief to final asset.
beginner • 4 sections
Building LLM Apps with RAG
Go from prompts to products. Learn how to ground an LLM in your own data using Retrieval-Augmented Generation, including embeddings, vector search, chunking, and evaluation.
intermediate • 3 sections
Data Science Foundations
Learn the workflow that turns raw data into insight: asking questions, exploring data, visualizing it, and reasoning about uncertainty — the groundwork for all of ML.
intermediate • 3 sections
Deep Learning Essentials
Understand how neural networks learn and meet the architectures behind modern AI — from the perceptron to CNNs and transformers — with intuition over heavy math.
intermediate • 3 sections
Generative AI: Images, Audio & Video
A hands-on tour of creative AI. Learn how diffusion models generate images, how to prompt them well, and how to create voice, music, and video — with both no-code tools and APIs.
beginner • 3 sections
Machine Learning Foundations
Build a solid base in classical machine learning: how supervised learning works, how to train and evaluate models, and how to avoid the most common pitfalls — with hands-on Python.
intermediate • 3 sections
Prompt Engineering Mastery
Learn the repeatable techniques that turn vague prompts into reliable, high-quality results — from clear instructions to few-shot examples, structured output, and chain-of-thought.
beginner • 3 sections
Python for AI: A Gentle Start
New to coding? This course teaches just enough Python to start doing AI — variables, data structures, functions, and the data libraries you’ll use every day.
beginner • 3 sections
Multi-Domain Research Agent Tutorial
A comprehensive guide to building and deploying a multi-agent research application using OpenAI's Agents SDK.
Write Your First Effective Prompt
Turn vague requests into prompts that get great results on the first try.
Prompt Engineering
Few-Shot Prompting Explained
Teach a model the exact format and style you want using a few examples.
Prompt Engineering
Get Reliable JSON Output from an LLM
Stop fighting malformed responses and get clean, parseable JSON every time.
Prompt Engineering
Call an LLM API in Python
Make your first programmatic call to a language model and handle the response.
LLM Application Development
Build a Simple Chatbot with Memory
Create a command-line chatbot that remembers the conversation.
LLM Application Development
Stream LLM Responses for a Snappy UX
Show tokens as they arrive instead of making users wait for the full answer.
LLM Application Development
An Intro to Embeddings
Understand embeddings and use them for semantic similarity.
LLM Application Development
Build a Minimal RAG System
Ground an LLM in your own documents end to end.
LLM Application Development
Run LLMs Locally with Ollama
Run open models on your own machine — private, offline, and free.
AI Tools & Workflows
Fine-Tuning vs. RAG: Which Do You Need?
A practical decision guide for customizing model behavior.
LLM Application Development
Five Ways to Reduce Hallucinations
Practical tactics to make model outputs more trustworthy.
LLM Application Development
Tokenization Explained
Understand tokens — the units LLMs actually read and bill you for.
Deep Learning
How Transformers Work (Intuitively)
A plain-language tour of the architecture behind modern AI.
Deep Learning
Pandas for Data Cleaning
The handful of pandas operations you use in almost every ML project.
Python for AI
Splitting Data the Right Way
Avoid the most common cause of misleading ML results: leakage.
Machine Learning
Evaluate Classification Models
Go beyond accuracy with precision, recall, and the confusion matrix.
Machine Learning
Generate Images with Stable Diffusion
Run an open image model and learn what each setting does.
Generative AI
Prompt Injection: What It Is and How to Defend
Understand the top security risk in LLM apps and practical mitigations.
LLM Application Development
How to Choose the Right Model
Balance quality, speed, and cost when picking a model.
AI Tools & Workflows
Evaluate LLM Outputs Systematically
Build a lightweight eval so you can improve prompts with confidence.
LLM Application Development
Function Calling: Let an LLM Use Your Tools
Connect a model to real functions so it can fetch data and take actions.
LLM Application Development
Build a Tool-Using AI Agent
Turn function calling into a simple autonomous agent loop.
LLM Application Development
Cut LLM Costs with Caching
Three caching strategies that dramatically reduce token spend.
LLM Application Development
Serve an ML Model with FastAPI
Wrap a trained model in a production-ready HTTP endpoint.
Python for AI
Sentiment Analysis with Hugging Face
Run a state-of-the-art NLP model in three lines with pipelines.
Machine Learning
Image Classification with Transfer Learning
Reuse a pretrained network to classify your own images with little data.
Deep Learning
Transcribe Audio with Whisper
Turn speech into text locally with OpenAI’s open-source Whisper.
AI Tools & Workflows
Generate Images with the OpenAI API
Create images programmatically and save them to disk.
Generative AI
Fine-Tune a Model Efficiently with LoRA
Customize a model on a single GPU using parameter-efficient fine-tuning.
Deep Learning
Writing System Prompts That Work
Set durable behavior for an assistant with a strong system prompt.
Prompt Engineering
Multimodal Prompting: Ask About Images
Send images to a model and ask questions about them.
Generative AI
Chunking Strategies for Better RAG
How you split documents quietly decides your RAG quality.
LLM Application Development
Measure Retrieval Quality in RAG
Diagnose whether your RAG problem is retrieval or generation.
LLM Application Development
Pandas GroupBy and Aggregation
Summarize data the way you would in SQL, in one line.
Python for AI
Set Up a Clean Python Environment for AI
Avoid dependency chaos with isolated, reproducible environments.
Python for AI
Feature Engineering Basics
Often the biggest accuracy gains come from features, not fancier models.
Machine Learning
Cross-Validation Explained
Get a stabler estimate of performance than a single train/test split.
Machine Learning
Tune Hyperparameters Without Overfitting
Search for better settings the right way — with cross-validation.
Machine Learning
Random Forests, Explained
A robust, hard-to-beat default for tabular data.
Machine Learning
Gradient Boosting with XGBoost
The algorithm behind countless winning tabular models.
Machine Learning
Unsupervised Learning with K-Means
Find natural groups in unlabeled data.
Machine Learning
An Intro to Time Series Forecasting
Forecasting is different — respect the arrow of time.
Machine Learning
How Recommendation Systems Work
The ideas behind "you might also like."
Machine Learning
Data Visualization with Matplotlib
See your data before you model it.
Python for AI
Prompt Chaining for Complex Tasks
Break a hard task into a pipeline of focused steps.
Prompt Engineering
Validate LLM Output with Pydantic
Guarantee the shape of model output before it hits your code.
LLM Application Development
Build an AI App with Streamlit
Turn a script into a shareable web app in minutes.
Python for AI
Discover Topics with Embeddings + Clustering
Group hundreds of documents into themes automatically.
LLM Application Development
Token Budgeting for LLM Apps
Stay within context limits and control cost as conversations grow.
LLM Application Development
Temperature and Sampling Settings
Control how random or focused a model’s output is.
LLM Application Development
Build RAG with LlamaIndex
Use a high-level framework to stand up RAG in minutes.
LLM Application Development
Add Citations to RAG Answers
Make answers trustworthy by showing their sources.
LLM Application Development
Hybrid Search: Keyword + Vector
Combine the strengths of semantic and keyword search.
LLM Application Development
A Neural Network from Scratch (Intuition)
Understand what a neural net is really doing under the hood.
Deep Learning
Activation Functions, Demystified
Why neural networks need non-linearity, and which functions to use.
Deep Learning
Gradient Descent, Intuitively
The optimization idea that powers nearly all model training.
Deep Learning
Regularization: Fighting Overfitting
Techniques to help models generalize beyond the training data.
Machine Learning
Reading a Confusion Matrix
Turn four numbers into a clear picture of model behavior.
Machine Learning
SQL Essentials for Data Science
The queries you’ll actually use to pull and shape data.
Python for AI
NumPy Essentials for AI
The array library underneath every ML framework.
Python for AI
Deploy a Next.js AI App to Vercel
Ship your AI side project to the web for free.
LLM Application Development
Handle Rate Limits and Retries
Make your LLM calls resilient in production.
LLM Application Development
Add Content Moderation to Your App
Screen user input and model output for unsafe content.
LLM Application Development
Choosing an Embedding Model
Not all embeddings are equal — pick the right one for retrieval.
LLM Application Development
Build a "Chat with PDF" App
A complete mini-RAG project over your own documents.
LLM Application Development
Trace and Debug LLM Apps
You can’t fix what you can’t see — instrument your AI calls.
LLM Application Development
Cache Embeddings to Save Time and Money
Never pay to embed the same text twice.
LLM Application Development
Understanding Bias in Machine Learning
Where bias creeps in, and how to catch it.
Machine Learning
MLOps Basics: From Notebook to Production
What it takes to keep a model working after you ship it.
Machine Learning
Detect Data Drift Before It Hurts
Models silently decay when the world changes — watch for it.
Machine Learning
Coding with AI Assistants, Responsibly
Get the productivity boost without the footguns.
AI Tools & Workflows
Version Your Prompts Like Code
Treat prompts as a first-class, tested artifact.
Prompt Engineering
Object Detection with YOLO
Detect and locate objects in images with a few lines of code.
Deep Learning
Image Segmentation Basics
Label every pixel, not just bounding boxes.
Deep Learning
PCA for Dimensionality Reduction
Compress many features into a few while keeping the signal.
Machine Learning
Visualize High-Dimensional Data with t-SNE & UMAP
Turn embeddings into a 2D map you can actually see.
Machine Learning
Handling Imbalanced Datasets
When 99% of examples are one class, accuracy lies.
Machine Learning
Explain Model Predictions with SHAP
Open the black box and see why a model decided what it did.
Machine Learning
A Gentle Intro to Reinforcement Learning
Learning by trial, error, and reward.
Deep Learning
How RLHF Aligns Language Models
The technique that made chat assistants helpful and polite.
Deep Learning
Word Embeddings and word2vec
The idea that "king − man + woman ≈ queen."
Deep Learning
Zero-Shot Classification with LLMs
Classify text into your own labels — no training data needed.
LLM Application Development
Improve RAG with a Reranker
A second-stage model that sharpens which chunks you keep.
LLM Application Development
Query Rewriting for Better Retrieval
Fix vague or conversational questions before you search.
LLM Application Development
Build a Fully Local RAG with Ollama
Private RAG that never sends your data to the cloud.
LLM Application Development
Build an AI Slack Bot
Bring an assistant into the tools your team already uses.
LLM Application Development
Generate Synthetic Data with LLMs
Bootstrap datasets when real labeled data is scarce.
LLM Application Development
How to Evaluate AI Agents
Agents are hard to test — here’s a practical approach.
LLM Application Development