Community
0
Active members
Matrix
3
Sequence nodes
Duration
14h
Temporal scope
Reception
N/A
Peer review score
Manifest Content
Use Python to work with OpenAI's API, analyse data with Pandas, and build a RAG PDF chatbot with LangChain.
Asset Valuation
₦200,000
Sync Standard
80% MASTERY
Certification
₦2000
Skill Complexity
ADVANCED
Cognitive Classifications
python
openai
pandas
langchain
RAG
advanced
Sequence Metadata
ArchitectAdmin TechHill
InitializedApril 14, 2026
Deployment4/17/2026 SYNC ACTIVE
Target Gains
- Call the OpenAI API with custom system prompts and parse structured responses
- Analyse and visualise a real dataset using Pandas and Matplotlib
- Build a working PDF Q&A chatbot using LangChain and FAISS
Sequence Matrix
Curriculum architectural nodes
1
Module 1: OpenAI API & Prompt Engineering in Python
4 UNITS 180m SCOPE
Calling the OpenAI API from Python
LESSON
Structured Outputs: Parsing JSON from LLM Responses
LESSON
System Prompts, Temperature, and Token Management
LESSON
Project: Build an AI Document Summarizer CLI Tool
PRACTICE
2
Module 2: Pandas + Data Analysis
4 UNITS 180m SCOPE
DataFrames, Series, and Reading CSVs with Pandas
LESSON
Cleaning Messy Data: fillna, dropna, rename, apply
LESSON
Visualising Data with Matplotlib and Seaborn
LESSON
Project: Build an Automated Weekly Expense Report from a CSV File
PRACTICE
3
Module 3: RAG & LangChain
4 UNITS 200m SCOPE
What is RAG? Retrieval Augmented Generation Explained
LESSON
Vector Stores and Embeddings with FAISS
LESSON
Building a LangChain Pipeline: Load → Split → Embed → Retrieve → Generate
LESSON
Project: Build a PDF Q&A Chatbot (ask any question about any PDF)
PRACTICE