AWS for AI Services

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Course Overview

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Mentor Based

Program Syllabus

Module 1

About This Course

This course provides an in-depth exploration of AWS’s powerful cloud computing services tailored for artificial intelligence, including machine learning, deep learning, data management, and processing services.

Module 2

Aim

To enable learners to utilize AWS’s robust cloud capabilities for developing, training, and deploying AI models effectively and efficiently.

Module 3

Program Objectives

Master AWS tools and services for AI and machine learning.
Develop, deploy, and manage AI solutions efficiently on the cloud.
Optimize AI applications for scalability and cost.

Module 4

Program Structure

Introduction to AWS and AI Services:
- Basics of AWS’s architecture and its comprehensive AI services.
AWS Machine Learning Services:
- Detailed insights into using SageMaker, Comprehend, and Rekognition for practical AI applications.
AWS for Deep Learning:
- Utilization of AWS Deep Learning AMIs and containers, TensorFlow, and PyTorch integration.
Data Management and Processing in AWS:
- Building AWS data lakes, using AWS Kinesis for real-time data streaming and analytics.
Scalability and Cost Management:
- Strategies for managing scalability and optimizing costs in AWS.
Security and Compliance:
- Ensuring robust security measures and understanding AWS’s compliance frameworks.
Project and Capstone:
- Comprehensive project from design to implementation using AWS to solve real-world AI challenges.

Lead Instructor

Dr. Sarah Chen

PhD in Computational Mechanics from MIT with 15+ years of experience in Industrial AI. Former Lead Data Scientist at Tesla and current advisor to Fortune 500 manufacturing firms.

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