| Level 1 |
1 |
Gen AI: Overview |
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2 |
Open Source and Closed Source AI |
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3 |
NLP Tasks: Summarization, Translation, Conversation, Sentiment Analysis, Topic Modeling |
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4 |
Prompt Engineering - Basics: Zero Shot, One Shot, Few Shot |
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5 |
Tokenization |
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6 |
Embeddings |
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7 |
Search |
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| Level 2 |
8 |
Langchain, Llama Index |
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9 |
Vector Databases: Qdrant, Milvus, ChromaDB |
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10 |
Python Frameworks: FastAPI, Flask, Streamlit, Gradio |
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11 |
Prompt Engineering - Advanced: CoT, ReAct |
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12 |
Knowledge Base: PDF, CSV, Excel, Text, PPT, Word, Databases, Websites |
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13 |
Chunking Methodologies |
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| Level 3 |
14 |
Re-Ranker: Cross Encoders |
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15 |
MultiQuery Expansion |
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16 |
Metadata Filtering |
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17 |
Hybrid Search (BM25) |
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18 |
Memory Based Retrieval |
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19 |
Summarization / Compression of Larger Docs |
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| Level 4 |
20 |
Tool Calling, Function Calling |
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21 |
Agents: Zero Shot Agents, ReAct Agents, Plan and Execute Agents |
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22 |
Tool Kit: Calculator, Websearch, Code Interpreter |
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23 |
Persona Based Agents / Role Playing Agents: Product Manager, Doctor |
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24 |
Multi Agent Frameworks: LangGraph, Agno, AutoGen, CrewAI |
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25 |
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26 |
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27 |
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28 |
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