Artificial Intelligence (AI) for Business Leaders

4.6

Instructor: /

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This executive program provides business leaders with the knowledge and skills to effectively utilize artificial intelligence in their organization. Participants will gain the confidence to strategically implement AI and maximize its potential. ▼▲

Course Feature Course Overview Course Provider Discussion and Reviews

Go to class

Course Feature

Cost:

Paid

Provider:

Udacity

Certificate:

No Information

Language:

English

Start Date:

Self Paced

Course Overview

❗The content presented here is sourced directly from Udacity platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.

Updated in [March 06th, 2023]

This course provides business leaders with an introduction to Artificial Intelligence (AI) and Machine Learning (ML). Participants will gain an understanding of how probabilistic reasoning is applied to ML, and will learn key terms and components involved in ML approaches, such as algorithm, model, training, feature, test set, training set, and ground truth dataset. Additionally, participants will develop ideas for ML and AI use cases for their business, and create before/after storyboards to evaluate the feasibility and impact of an ML/AI use case. By the end of the course, participants will have a better understanding of AI and ML, and will be able to apply their knowledge to their own business.

[Applications]
After completing this course, business leaders can apply the knowledge gained to develop ideas for machine learning and AI use cases for their business. They can create before/after storyboards to evaluate the feasibility and impact of an ML/AI use case, and use probabilistic reasoning to apply machine learning approaches. Additionally, they can become familiar with key terms and components involved in machine learning approaches, such as algorithm, model, training, feature, test set, training set, and ground truth dataset.

[Career Paths]
1. AI Business Analyst: AI Business Analysts are responsible for analyzing data and developing strategies to help businesses make better decisions. They use machine learning and AI technologies to identify trends and patterns in data, and then develop strategies to help businesses make better decisions. AI Business Analysts are also responsible for developing and implementing AI-based solutions to improve business processes.

2. AI Product Manager: AI Product Managers are responsible for developing and managing AI-based products. They work closely with engineers, designers, and other stakeholders to ensure that the product meets customer needs and is successful in the market. AI Product Managers must have a deep understanding of AI technologies and be able to identify and develop use cases for AI-based products.

3. AI Engineer: AI Engineers are responsible for developing and deploying AI-based solutions. They must have a deep understanding of AI technologies and be able to develop algorithms and models to solve complex problems. AI Engineers must also be able to integrate AI-based solutions into existing systems and processes.

4. AI Consultant: AI Consultants are responsible for providing advice and guidance to businesses on how to use AI technologies to improve their operations. They must have a deep understanding of AI technologies and be able to identify and develop use cases for AI-based solutions. AI Consultants must also be able to provide advice on how to integrate AI-based solutions into existing systems and processes.

[Education Paths]
1. Bachelor of Science in Artificial Intelligence: This degree program provides students with a comprehensive understanding of the fundamentals of AI, including machine learning, natural language processing, computer vision, and robotics. Students will also gain an understanding of the ethical implications of AI and its applications in the business world. This degree is ideal for those looking to pursue a career in AI-related fields, such as data science, software engineering, and machine learning.

2. Master of Science in Artificial Intelligence: This degree program provides students with a deeper understanding of AI and its applications in the business world. Students will learn advanced topics such as deep learning, reinforcement learning, and neural networks. They will also gain an understanding of the ethical implications of AI and its applications in the business world. This degree is ideal for those looking to pursue a career in AI-related fields, such as data science, software engineering, and machine learning.

3. Doctor of Philosophy in Artificial Intelligence: This degree program provides students with a comprehensive understanding of the fundamentals of AI, including machine learning, natural language processing, computer vision, and robotics. Students will also gain an understanding of the ethical implications of AI and its applications in the business world. This degree is ideal for those looking to pursue a career in AI-related fields, such as data science, software engineering, and machine learning.

4. Master of Business Administration with a Concentration in Artificial Intelligence: This degree program provides students with a comprehensive understanding of the fundamentals of AI, including machine learning, natural language processing, computer vision, and robotics. Students will also gain an understanding of the ethical implications of AI and its applications in the business world. This degree is ideal for those looking to pursue a career in AI-related fields, such as data science, software engineering, and machine learning.

Course Syllabus

Differentiate between how the five “V’s” of data (velocity, volume, variety, veracity, value) affect a ML model

Understand how information about the five “V’s” of data impacts the potential and feasibility of an ML/AI use case

Distinguish between classification, regression, optimization, and simulation in ML/AI applications

Understand the basics of predictive modeling and the differences between classification and regression

Understand the basics of optimization and the relationship between optimization and simulation

Become familiar with key terms and concepts of deep learning, and how it can be applied to predictive modeling

Learn how reinforcement learning models can be applied to the most complex optimization scenarios

Course Provider

Provider Udacity's Stats at AZClass

This executive program provides business leaders with the knowledge and skills to effectively leverage artificial intelligence in their organizations. This course will help learners understand the fundamentals of probabilistic reasoning and its application to machine learning. Learners will understand key terms and components involved in machine learning methods such as algorithms, models, training, features, test sets, training sets, and ground truth datasets. They will also develop machine learning and AI use case ideas for the enterprise and create before and after storyboards to assess the feasibility and impact of ML/AI use cases. Through this course, learners will gain the knowledge and skills to apply artificial intelligence and machine learning to business and make informed decisions.