ByteTrail

Level 18 · Module 65

Modern AI Engineering

A structured module covering the essential ideas of modern ai engineering.

Difficulty
advanced
Published path
13 lessons · 130 min

What you will learn

  • LLMs
  • Tokens
  • Embeddings
  • Vector databases
  • Semantic search
  • RAG
  • Prompt engineering
  • Function/tool calling
  • AI agents
  • MCP
  • Evaluation
  • Guardrails
  • AI application architecture
Prerequisites:Deep Learning

Start here

Lessons · 130 min

  1. LLMsPlanned

    Planned lesson: LLMs. This lesson has not been written yet.

    10 min · advanced

  2. TokensPlanned

    Planned lesson: Tokens. This lesson has not been written yet.

    10 min · advanced

  3. EmbeddingsPlanned

    Planned lesson: Embeddings. This lesson has not been written yet.

    10 min · advanced

  4. Vector databasesPlanned

    Planned lesson: Vector databases. This lesson has not been written yet.

    10 min · advanced

  5. Semantic searchPlanned

    Planned lesson: Semantic search. This lesson has not been written yet.

    10 min · advanced

  6. RAGPlanned

    Planned lesson: RAG. This lesson has not been written yet.

    10 min · advanced

  7. Prompt engineeringPlanned

    Planned lesson: Prompt engineering. This lesson has not been written yet.

    10 min · advanced

  8. Function/tool callingPlanned

    Planned lesson: Function/tool calling. This lesson has not been written yet.

    10 min · advanced

  9. AI agentsPlanned

    Planned lesson: AI agents. This lesson has not been written yet.

    10 min · advanced

  10. MCPPlanned

    Planned lesson: MCP. This lesson has not been written yet.

    10 min · advanced

  11. EvaluationPlanned

    Planned lesson: Evaluation. This lesson has not been written yet.

    10 min · advanced

  12. GuardrailsPlanned

    Planned lesson: Guardrails. This lesson has not been written yet.

    10 min · advanced

  13. AI application architecturePlanned

    Planned lesson: AI application architecture. This lesson has not been written yet.

    10 min · advanced

What you will cover

Module units

  1. LLMs

    A planned unit covering LLMs.

  2. Tokens

    A planned unit covering Tokens.

  3. Embeddings

    A planned unit covering Embeddings.

  4. Vector databases

    A planned unit covering Vector databases.

  5. Semantic search

    A planned unit covering Semantic search.

  6. RAG

    A planned unit covering RAG.

  7. Prompt engineering

    A planned unit covering Prompt engineering.

  8. Function/tool calling

    A planned unit covering Function/tool calling.

  9. AI agents

    A planned unit covering AI agents.

  10. MCP

    A planned unit covering MCP.

  11. Evaluation

    A planned unit covering Evaluation.

  12. Guardrails

    A planned unit covering Guardrails.

  13. AI application architecture

    A planned unit covering AI application architecture.