📊Data Science & AIML
Curriculum: Data Science & AIML
Python, statistics, ML models and MLOps basics — a practitioner's path into data science.
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Curriculum
Week-by-week breakdown
A clear, transparent syllabus — no surprises.
01
Python & statistics foundations
The core toolkit: pandas, numpy, and the statistics that underpin ML.
02
Data wrangling & EDA
Cleaning, exploring and understanding real, messy datasets.
03
Machine learning models
Classical ML and an introduction to deep learning.
04
MLOps & deployment basics
Versioning, APIs and monitoring for models in production.
05
Capstone project
An end-to-end project you can show in interviews.
📊 Data Science & AIML
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