Learn in Bits

Build Intelligent Systems

Master AI & Machine Learning Through Daily Practice

Learn to build intelligent systems through bite-sized lessons delivered to your inbox. From neural networks to LLMs, develop real-world AI skills.

5-15 min
Daily lessons
Hands-on
Practical focus
Real-world
Industry skills

Building RAG Systems

Day 3 of 21

Path: LLM Development ยท 12 minutes ยท Hands-on practice

  • Vector embeddings fundamentals
  • Setting up a vector database
  • Context injection techniques

Start Learning Today

Choose a specific skill to master. Each lesson is designed to teach you practical, hands-on techniques you can apply immediately.

๐Ÿค–

AI Agents Fundamentals

Build autonomous AI agents that can reason, plan, and take actions.

  • Agent Architecture
  • Tool Integration
  • Memory Systems
๐Ÿ”—

LangChain Essentials

Master the leading framework for building LLM-powered applications.

  • Chains & Prompts
  • Document Loaders
  • Vector Stores
๐Ÿ

Python for AI

Essential Python skills for machine learning and AI development.

  • NumPy & Pandas
  • Data Structures
  • API Integration
๐Ÿ’ฌ

Prompt Engineering

Write effective prompts to get the best results from LLMs.

  • Chain-of-Thought
  • Few-shot Learning
  • System Prompts
๐Ÿง 

Neural Networks Basics

Understand the building blocks of modern AI systems.

  • Perceptrons
  • Backpropagation
  • Activation Functions
๐Ÿ“Š

RAG Systems

Build retrieval-augmented generation systems for accurate AI.

  • Embeddings
  • Vector Search
  • Context Injection
๐Ÿ”ฎ

Fine-tuning LLMs

Customize language models for your specific use cases.

  • LoRA & QLoRA
  • Dataset Preparation
  • Evaluation Metrics
๐Ÿ‘๏ธ

Computer Vision Basics

Teach machines to see and understand images.

  • CNNs
  • Object Detection
  • Image Classification
๐Ÿ—ฃ๏ธ

NLP Fundamentals

Process and understand human language with AI.

  • Tokenization
  • Transformers
  • Sentiment Analysis
โšก

TensorFlow Essentials

Build and train ML models with Google's framework.

  • Keras API
  • Model Training
  • Deployment
๐Ÿ”ฅ

PyTorch Basics

Learn the preferred framework for AI research.

  • Tensors
  • Autograd
  • Model Building
๐Ÿ“ˆ

ML Model Evaluation

Measure and improve your model's performance.

  • Metrics
  • Cross-Validation
  • Hyperparameter Tuning
๐ŸŽฏ

Reinforcement Learning

Train agents to make decisions through reward signals.

  • Q-Learning
  • Policy Gradients
  • Environments
๐Ÿ—๏ธ

ML System Design

Design scalable machine learning systems.

  • Data Pipelines
  • Feature Stores
  • Model Serving
๐Ÿ”

AI Safety & Ethics

Build responsible AI systems with proper safeguards.

  • Bias Detection
  • Guardrails
  • Alignment
๐Ÿค–

AI Agents Fundamentals

Build autonomous AI agents that can reason, plan, and take actions.

  • Agent Architecture
  • Tool Integration
  • Memory Systems
๐Ÿ”—

LangChain Essentials

Master the leading framework for building LLM-powered applications.

  • Chains & Prompts
  • Document Loaders
  • Vector Stores
๐Ÿ

Python for AI

Essential Python skills for machine learning and AI development.

  • NumPy & Pandas
  • Data Structures
  • API Integration
๐Ÿ’ฌ

Prompt Engineering

Write effective prompts to get the best results from LLMs.

  • Chain-of-Thought
  • Few-shot Learning
  • System Prompts
๐Ÿง 

Neural Networks Basics

Understand the building blocks of modern AI systems.

  • Perceptrons
  • Backpropagation
  • Activation Functions
๐Ÿ“Š

RAG Systems

Build retrieval-augmented generation systems for accurate AI.

  • Embeddings
  • Vector Search
  • Context Injection
๐Ÿ”ฎ

Fine-tuning LLMs

Customize language models for your specific use cases.

  • LoRA & QLoRA
  • Dataset Preparation
  • Evaluation Metrics
๐Ÿ‘๏ธ

Computer Vision Basics

Teach machines to see and understand images.

  • CNNs
  • Object Detection
  • Image Classification
๐Ÿ—ฃ๏ธ

NLP Fundamentals

Process and understand human language with AI.

  • Tokenization
  • Transformers
  • Sentiment Analysis
โšก

TensorFlow Essentials

Build and train ML models with Google's framework.

  • Keras API
  • Model Training
  • Deployment
๐Ÿ”ฅ

PyTorch Basics

Learn the preferred framework for AI research.

  • Tensors
  • Autograd
  • Model Building
๐Ÿ“ˆ

ML Model Evaluation

Measure and improve your model's performance.

  • Metrics
  • Cross-Validation
  • Hyperparameter Tuning
๐ŸŽฏ

Reinforcement Learning

Train agents to make decisions through reward signals.

  • Q-Learning
  • Policy Gradients
  • Environments
๐Ÿ—๏ธ

ML System Design

Design scalable machine learning systems.

  • Data Pipelines
  • Feature Stores
  • Model Serving
๐Ÿ”

AI Safety & Ethics

Build responsible AI systems with proper safeguards.

  • Bias Detection
  • Guardrails
  • Alignment

Learn AI & Machine Learning Your Way

Structured lessons, practical exercises, and consistent progress tracking to help you master ai & machine learning at your own pace.

๐ŸŽฏ

Practical Projects

Build real AI applications with guided hands-on projects.

๐Ÿ“Š

Track Progress

Monitor your skills development across different AI domains.

๐Ÿš€

Industry Ready

Learn the tools and techniques used by AI engineers today.

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