Nanodegree key: nd054
Version: 1.0.0
Locale: en-us
Formulate and evaluate proposals grounded in first principles when assessing opportunities to embed machine learning and artificial intelligence into a corporate strategy.
Content
Part 01 : Welcome to the AI for Business Leaders Executive Program
Welcome! You'll learn all about Udacity and what to expect while you work through your program.
-
Module 01: Welcome to the AI for Business Leaders Executive Program
-
Lesson 02: Introduction to AI for Business Leaders
This lesson provides an overview of the AI for Business Leaders Executive Program, and outlines its content. We introduce our instructors, and hear from AI experts on the importance of this program.
-
Lesson 03: Nanodegree Career Services
The Careers team at Udacity is here to help you move forward in your career - whether it's finding a new job, exploring a new career path, or applying new skills to your current job.
Part 02 : AI for Business Leaders
The AI for Business Leaders program is designed for those looking to deepen their understanding of Artificial Intelligence and the innovations in the field of Machine Learning that have driven its recent progress. The program is designed to arm students with a deep but approachable knowledge of how these systems work and what it takes to put them into practice. Throughout the program, we’ll follow a fictitious retailer in order to gain practice in making discriminating judgements on what AI use cases might be best for a given business at a given point in time. In the final project, students will replicate this experience, applying a similar series of exercises to a business of their choosing.
-
Module 01: AI for Business Leaders
-
Lesson 01: The Paradigm Shift
We’ll begin studying machine learning and artificial intelligence. You’ll develop an understanding of their potential and the language to talk about AI and ML with your team, and build your first model!
- Concept 01: Lesson Overview
- Concept 02: What are AI and ML?
- Concept 03: Use Cases in Business
- Concept 04: Probabilistic Reasoning
- Concept 05: First Experience with ML
- Concept 06: Building your Intuition with ML
- Concept 07: Checking for Understanding
- Concept 08: Introducing our Case Study
- Concept 09: Using Storyboards to Analyze Use Cases
- Concept 10: Practice Storyboarding with Use Cases
- Concept 11: Lesson Wrap-Up
-
Lesson 02: The Math Behind The Magic
This lesson will take a deeper dive into AI and ML techniques using a data-first perspective. We’ll also explore the mathematical underpinnings of how ML models learn.
- Concept 01: Lesson Overview
- Concept 02: Thinking about Data
- Concept 03: Using 5Vs to Assess Feasibility
- Concept 04: Branches of ML
- Concept 05: Basics of Predictive Modeling
- Concept 06: Prediction: Regression
- Concept 07: Prediction: Classification
- Concept 08: Basics of Optimization
- Concept 09: Deep Learning for Prediction
- Concept 10: Reinforcement Learning for Optimization
- Concept 11: Continuing Our Case Study
- Concept 12: Practice
- Concept 13: Lesson Wrap-Up
-
Lesson 03: Architectures of AI Systems
This lesson focuses on capabilities and architectures commonly used in ML/AI systems, and develops student skills with building these architectures, including the data, capabilities, and user layers.
- Concept 01: Lesson Overview
- Concept 02: Importance of Architecture
- Concept 03: Generic Capabilities
- Concept 04: Generic Capability: Segmenters
- Concept 05: Business Rules
- Concept 06: Natural Language Processing
- Concept 07: Voice/Speech Processing
- Concept 08: Computer Vision
- Concept 09: Building Simple Architectures
- Concept 10: Continuing Our Case Study
- Concept 11: Lesson Wrap-Up
-
Lesson 04: Working with Data
Machine Learning is a data-hungry process. In this lesson, we’ll talk about some of the more operational elements of building ML and AI systems, namely data labeling and infrastructure management.
-
Lesson 05: Accuracy, Bias, and Ethics
What does it mean for a model to be useful? In this lesson, we’ll explore topics like accuracy and precision as well as model overfit and underfit, to figure out ways to assess a model’s usefulness.
-
Lesson 06: Gathering Feedback
Building support for an AI/Machine Learning project is an important part of the journey. We’ll talk about best practices for clearly understanding the priorities of your business and communicating how AI/ML can help to advance them.
-
Lesson 07: Thinking Bigger
Many times, progress with ML/AI requires a business to execute several projects in parallel. In this lesson, we’ll talk about how to bring use cases together to form a greater whole.
-
Lesson 08: Delivering an ML/AI Strategy
In this project, you will apply all the skills you’ve learned in the lessons to develop a strategic ML/AI roadmap. You may choose to work on your own business, or in a fictitious context we provide.
-