✦Sparkl
innovator · talks

Retrieval & Tools: Building Smart AI Assistants

Learn how AI retrieves information from vast knowledge bases and uses external tools to solve real-world problems. Build a retrieval-augmented generation assistant that searches documents and answers questions intelligently.

20 modules·Difficulty: ★★★★☆· 5 Free
Start module 1

Modules

  • 1
    Free8 min
    What Is Vector Search?
    Discover how AI converts words into numbers to find similar meanings across huge libraries 📚
  • 2
    Free10 min
    Embeddings Explained
    Learn how transformer models produce high-dimensional vectors that capture semantic meaning
  • 3
    Free9 min
    Distance Metrics and Similarity
    Compare cosine similarity and Euclidean distance to measure how close two vectors are
  • 4
    Free11 min
    Building a Simple Vector Store
    Create your first in-memory database that indexes short documents and finds the nearest matches
  • 5
    Free10 min
    Why Retrieval Matters for AI
    Understand how retrieval helps models answer questions they were never trained on
  • 6
    Paid12 min
    Chunking Strategies for Long Documents
    Split large texts into overlapping chunks that preserve context and improve search accuracy
  • 7
    Paid11 min
    Prompt Engineering for Retrieval
    Write prompts that guide the model to use retrieved snippets effectively in its answers
  • 8
    Paid10 min
    Hands-On: Build a Mini RAG
    Combine embedding, search, and generation into one pipeline that answers user queries
  • 9
    Paid9 min
    Evaluating Retrieval Quality
    Measure precision and recall to see if your system fetches the right documents
  • 10
    Paid11 min
    What Are Function Calls?
    Explore how models decide to invoke external tools like calculators or databases mid-conversation
  • 11
    Paid10 min
    Defining Tool Schemas
    Describe each tool with parameters and return types so the model knows when and how to call it
  • 12
    Paid12 min
    Building Your First Tool Interface
    Code a simple function that fetches weather data and connect it to your AI assistant
  • 13
    Paid11 min
    Chaining Tool Calls
    Let your model call multiple tools in sequence to solve complex multi-step problems
  • 14
    Paid10 min
    Error Handling in Tool Execution
    Catch failures gracefully and teach the model to retry or request clarifications from users
  • 15
    Paid9 min
    Combining RAG with Tool Calling
    Merge retrieval and function calls so your assistant can search documents and execute actions together
  • 16
    Paid12 min
    Designing a Document QA Bot
    Plan the architecture of an assistant that reads a small knowledge base and answers specific queries
  • 17
    Paid11 min
    Adding Source Citations
    Track which chunks the model used and display references so users can verify facts
  • 18
    Paid10 min
    Safety Filters and Content Moderation
    Implement checks that prevent your bot from returning harmful or inappropriate information
  • 19
    Paid12 min
    Capstone: Complete RAG Helper
    Integrate all techniques to deploy a working assistant on a custom dataset of your choice
  • 20
    Final exam10 min
    Final Assessment: Retrieval & Tools Mastery
    Prove your understanding of vector search, RAG pipelines, and tool-calling in one comprehensive exam