Intermediate Path

NLP is how AI reads, understands, and generates human language. Learn the techniques behind chatbots, translation, and text analysis.

8 min read

Embeddings convert text into numbers that capture meaning. Essential for search, recommendations, and RAG systems.

7 min read

How AI tools search and retrieve information from documents. Understand embeddings and Retrieval-Augmented Generation without the math.

11 min read

AI APIs charge per token. Learn how tokens work, how to estimate costs, and how to optimize spending.

6 min read

Context windows determine how much text an AI can process at once. Learn how they work, their limits, and how to work within them.

6 min read

Temperature, top-p, and other sampling parameters control how creative or deterministic AI outputs are. Learn how to tune them.

6 min read

From transformers to CNNs to diffusion models—understand the different AI architectures and what they're good at.

7 min read

AI quality depends on training data quality. Learn what makes good training data, common issues, and how to evaluate it.

7 min read

AI inherits biases from training data. Learn to detect, measure, and mitigate bias for fairer AI systems.

7 min read

How do you know if your AI is good? Learn key metrics for evaluating classification, generation, and other AI tasks.

6 min read

How to spot when AI gets it wrong. Practical techniques to verify accuracy, detect hallucinations, and build trust in AI outputs.

10 min read

Advanced prompting: structured formats, JSON output, few-shot learning, chain-of-thought, and prompt templates for production.

11 min read

Master advanced prompting techniques: chain-of-thought, few-shot, role prompting, and more. Get better AI outputs with proven patterns.

8 min read

Learn how to integrate AI APIs into your applications. Authentication, requests, error handling, and best practices.

6 min read

Process thousands of items efficiently with batch AI operations. Learn strategies for large-scale AI tasks.

5 min read

Multi-modal AI processes multiple types of data—text, images, audio, video. Learn how these systems work and their applications.

6 min read

RAG systems retrieve relevant context before generating responses. Learn retrieval strategies, ranking, and optimization techniques.

7 min read

Semantic search finds results based on meaning, not exact keyword matches. Learn how it works and how to implement it.

6 min read

Deep dive into vector databases. How they work, when to use them, and how to choose the right one for your needs.

11 min read

Practical examples of vector databases in action: semantic search, chatbot memory, recommendation systems, and more with code snippets.

9 min read

AI alignment ensures models do what we want them to do safely. Learn about RLHF, safety techniques, and responsible deployment.

7 min read

Deploying AI responsibly requires planning, testing, monitoring, and safeguards. Learn best practices for production AI.

7 min read

How do you know if your AI changes improved outcomes? Learn to A/B test prompts, models, and parameters scientifically.

6 min read

Production AI requires continuous monitoring. Track performance, detect drift, alert on failures, and maintain quality over time.

7 min read

Protect user privacy while using AI. Learn anonymization, differential privacy, on-device processing, and compliance strategies.

7 min read

Should you use OpenAI's GPT, or self-host Llama? Compare open source and proprietary models on cost, control, and capabilities.

7 min read

Use AI to analyze data, generate insights, create visualizations, and answer business questions from your datasets.

6 min read

Chain multiple AI steps together into workflows. Learn orchestration patterns, error handling, and tools for building AI pipelines.

7 min read

Understand AI agents that use tools to complete tasks. When they work, when they fail, and how to use them safely.

10 min read

Fine-tuning adapts pre-trained models to your specific use case. Learn when to fine-tune, how it works, and alternatives.

8 min read

Vector databases store and search embeddings efficiently. Learn how they work, when to use them, and popular options.

7 min read