AI Specialization Program

WEEK 6:

Computer Vision, Deployment & AI Automation

Theme: Deploy & Scale AI Systems

Week 6 shifts from modeling → real-world system deployment.

Week 6 —

6 Lesson Structure

Lesson 1:

Computer Vision Fundamentals

Focus:

Images as numerical arrays

CNN intuition

Image classification

Object detection basics

Real-world CV applications

Outcome: Students understand how machines interpret images.

Lesson 2:

Building Basic Vision Models

Focus:

Using PyTorch for image models

Pre-trained vision models

Transfer learning concept

Evaluating CV systems

Outcome: Students can implement a simple vision pipeline.

Lesson 3:

Deployment Basics (FastAPI / Streamlit)

Focus:

What is model serving?

API-based deployment

Simple FastAPI app

Streamlit demo apps

Turning models into usable tools

Outcome: Students can expose models via APIs or simple interfaces.

Lesson 4:

Docker & Reproducible Environments

Focus:

What is containerization?

Why Docker matters

Basic Dockerfile

Running model inside container

Environment reproducibility

Outcome: Students understand portable AI deployment.

Lesson 5:

Monitoring, Guardrails & Drift

Focus:

Model monitoring basics

Performance tracking

Data drift detection

Guardrails for GenAI

Logging & alerting mindset

Outcome: Students understand post-deployment responsibilities.

Lesson 6:

AI Automation Pipelines (Capstone Integration)

Focus:

Automating workflows

Connecting APIs

LLM + CV integration possibilities

Designing production pipelines

Capstone preparation guidance

Outcome: Students design a full AI system architecture.

Week 6 Final Outcome

By the end of Week 6, students can:

✔ Build basic computer vision systems

✔ Deploy ML or LLM models

✔ Create API-based AI services

✔ Understand containerization

✔ Monitor deployed systems

✔ Design automation pipelines

✔ Think end-to-end AI architecture

Week 6 produces:

Deployment-ready AI system engineers.

Full 6-Week Technical Track Summary

Week 1 → Engineering Foundations

Week 2 → Data Engineering

Week 3 → Machine Learning

Week 4 → Deep Learning + MLOps

Week 5 → NLP & Generative AI

Week 6 → Computer Vision + Deployment

This is now a complete, production-grade AI Engineering specialization.

As we continue on week 6 and move on to weeks 7 and finally week 8.

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