Artificial Intelligence

+ Microsoft Azure AI Fundamentals Certification Prep

 

About the Program

There are multiple definitions of Artificial Intelligence (AI), but the most common view is that it is software which enables a machine to think and act like a human, and to think and act rationally. Because AI differs from plain programming, the programming language will depend on the application, such as the ethics and reliability of its use. Gain the ability to communicate the value AI can bring to businesses today, along with multiple areas where AI is already being used.

This program is self-paced. Self-paced programs create a unique learning experience that allows students to learn independently and at a pace that best suits them.

Certification

This course fully prepares students to take the AI-900 Microsoft Azure AI Fundamentals certification exam.

The certification exams are not a requirement for graduation. Vendor certifications are at the student’s expense. Vouchers may be available depending on the student’s funding and financial aid.

TUITION: $3,895

Duration: 81 Hours (50 Hours + 31 Hours of Virtual Practice Lab)

Students will have access to the program for 1 full year.

Includes e-books, virtual practice lab and exam review questions for AI-900.

Prerequisites: HS diploma/GED, basic computer skills and familiarity with the internet

Job Roles: Business Intelligence Developer, AI Engineer, Robotic Scientist

To learn more about ETI’s tuition and financial aid options, click here.

Course Outline

    • Artificial Intelligence and Machine Learning

    • Machine Learning with Azure Services

    • Using Azure Machine Learning Studio

    • Authoring with the Azure ML Studio Designer

    • Evaluating Models with the ML Designer

    • Anomaly Detection

    • Natural Language Processing

    • Creating a Conversational AI Bot

    • Computer Vision

    • Face and Optical Character Recognition

    • AI Apprentice Virtual Practice Lab - 8 Hours

    • Basic AI Theory

    • Types of Artificial Intelligence

    • Human-computer Interaction Overview

    • Human-computer Interaction Methodologies

    • Python AI Development – Introduction

    • Python AI Development – Practice

    • Computer Vision – Introduction

    • Computer Vision – AI and Computer Vision

    • Cognitive Models – Overview

    • Cognitive Models – Approaches to Cognitive Learning

    • Final Exam – AI Apprentice

    • AI Developer Virtual Practice Lab - 8 Hours

    • AI Developer Role

    • Development Frameworks

    • Working with Cognitive Toolkit (CNTK)

    • Deep Learning Packages: Keras – a Neural Network Framework

    • Introducing Apache Spark for AI Development

    • Implementing AI with Amazon ML

    • Implementing AI Using Cognitive Modeling

    • Applying AI to Robotics

    • Working with Google BERT: Elements of BERT

    • Final Exam – AI Developer

    • AI Practitioner Virtual Practice Lab - 8 Hours

    • Role and Responsibilities

    • Optimizing AI Solutions

    • Tuning AI Solutions

    • Advanced Functionality of Microsoft Cognitive Toolkit (CNTK)

    • Working with the Keras Framework

    • Using Apache Spark for AI Development

    • Extending Amazon Machine Learning

    • Using Intelligent Information Systems in AI

    • Final Exam – AI Practitioner

    • AI Architect Virtual Practice Lab - 8 Hours

    • Elements of an Artificial Intelligence Architect

    • AI Enterprise Planning

    • AI in Industry

    • Leveraging Reusable AI Architecture Patterns

    • Evaluating Current and Future AI Technologies and Frameworks

    • Explainable AI

    • Final Exam – AI Architect

    • Effective Team Communication

    • Contributing as a Virtual Team Member

    • Knowing when to Take Strategic Risks

    • Taking your Team to the Next Level with Delegation

    • Choosing and Using the Best Solution

    • Developing a Successful Team

    • Encouraging Team Communication & Collaboration

    • Strategies for Managing Technical Teams

    • Facing Virtual Team Challenges

    • Positive Atmosphere: How Organizational Learning Drives Positive Change