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Data-Centric AI: A Data First Approach to AI (Registration is now open) (Batch period: May 19th - July 1st 2025)

Intel via SWAYAM Plus

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The two pillars of AI are code and data. In Data-Centric AI, students will primarily focus on the data aspect of AI by learning how to work with data (statistical, text, and visual) and how continuous improvements to datasets improve AI solutions. Students will then learn how to integrate and manage data pipelines with MLOps.

Session Timing: Monday to Friday: 04:00 PM - 06:00 PM

Intended audience

Prerequisites

Students having prior experience with Python programming, fundamental AI & ML knowledge, foundational mathematics, and statistics.

Assessment & certification

Assessment fee: Included — no extra fee
Assessment mode: Online
Assessment type: MCQ
Assessment provider: Intel
Certificate provider: NA

Syllabus

Week 1: Data-Centric AI vs Model-Centric AI
Week 2: AI Project Cycle & MLOps
Week 3: Fundamentals of Data
Week 4: Data Engineering Pipelines: Fundamentals & Relationship with MLOps
Week 5: Data Collection
Week 6: Data Wrangling (Cleaning)
Week 7: Data Enrichment
Week 8: Data Labeling
Week 9: Data Exploration
Week 10: Modeling & Evaluation
Week 11: Introduction to MLOps Platform
Week 12: Introduction to AutoML
Week 13: Implementing AutoML 1: Model Building, EDA and Advanced Pre-processing
Week 14: Implementing AutoML 2: Production Deployment, registration & versioning of Models
Week 15: Explainable AI & Model Interpretability
Week 16: Overview of Containerization & Deployment