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"Creating an AI course for business leaders so they can speak the same language as their engineers is challenging, but working with a variety of companies to understand the practical, technical, and commercial hurdles was incredibly insightful. Now, these learnings are available to all leaders who want to understand more about how to leverage Artificial Intelligence to advance their business."
Erik Brynjolfsson, Professor of Management at MIT Sloan & Director of MIT’s Initiative on Digital Economy
To optimize your chances of success in this Executive Program, we recommend prior exposure to statistics and probability, as well as experience in business decision-making in an IT or technical environment.See detailed requirements.
Understand how to apply probabilistic reasoning to machine learning, and gain a working knowledge of the key terms and components involved in machine learning approaches, such as: algorithm, model, training, feature, test set, training set, and ground truth dataset. Then, develop ideas for machine learning and AI use cases for a business, and evaluate them for feasibility and impact.
Understand how critical data attributes can affect a machine learning model, and distinguish the differences between classification, regression, optimization, and simulation in ML/AI applications. Become familiar with the applications of deep learning and how it can be applied to predictive modeling, reinforcement learning models, and optimization.
Understand the importance, applications, and components of machine learning model architecture including classifiers, regressors, optimizers, simulators, policy learners, and segmenters. Differentiate between the capabilities of natural language processing, voice/speech processing, and computer vision. Finally, build machine learning model architectures for a digital channel chatbot, negotiation engine, and visual classifier.
Learn how to label data for supervised learning. Understand the fundamental requirements of AI infrastructure, and how to overcome common implementation hurdles. Assess the feasibility of AI use cases in a range of business scenarios by evaluating data readiness.
Define the parameters for designing machine learning models including accuracy, underfitting and overfitting of data, and ethical frameworks.
Learn how to build surveys and conduct interviews to solicit feedback on model prototypes. Identify key stakeholders inside and outside an organization to provide feedback in an iterative design process. Analyze the results of feedback from stakeholders to inform evaluation and prioritization of business use cases.
Learn how to begin implementing AI use cases with small learning experiments, and build a roadmap deploying machine learning applications that strategically complement one another. Finally, create a proposal that integrates key use cases into a transformational business story.
Draw on all of the skills learned throughout the lessons to create an ML/AI strategy that is technically achievable and highly impactful on your business based on the evaluation of various AI-enabled use cases.Project Details
Founder, Product Manager, & Corporate Development Leader
William Ross is an experienced investor in AI and ML, and previously worked with IBM's Watson group managing a variety of PM and corporate dev teams. Today, he is the co-founder of a Silicon Valley-based AI startup. He attended Stanford's Graduate School of Business.
AI Engineer at Apple
Luis was formerly a Machine Learning Engineer at Google. He holds a PhD in mathematics from the University of Michigan, and a Postdoctoral Fellowship at the University of Quebec at Montreal.
Data Scientist at Nerd Wallet
Josh has been sharing his passion for data for nearly a decade at all levels of university, and as Lead Data Science Instructor at Galvanize. He's used data science for work ranging from cancer research to process automation.
from industry experts
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93% of high growth companies with double digit organic growth plan to implement AI into their business within the next one to three years, but 94% of enterprises struggle to understand how to implement AI in their organizations.
This program is designed for business executives who want to understand the foundational concepts of Artificial Intelligence and be able to implement machine learning technology into their business processes. You’ll learn about the broad foundations of Artificial Intelligence including predictive modeling, machine learning, deep learning, supervised and unsupervised learning, and then traverse a series of business case studies that will train learners in how to find optimal applications of AI for particular business scenarios.
This Executive Program teaches the technical foundations of machine learning and practical business applications of artificial intelligence in the 21st century. It is intended for business leaders and managers who are responsible for making strategic decisions regarding these technologies, and want to equip themselves to formulate and evaluate proposals involving machine learning and artificial intelligence technologies to impact their business.
This program is designed to train business leaders tasked with determining the strategic decisions to equip their company with the latest advancements in the fields of machine learning and artificial intelligence.
Read in detail about how companies like Amazon, Facebook, Google, Salesforce, Microsoft, and more are successfully implementing AI technology to develop cutting-edge products that enable them to win in the competitive business landscape. With the AI for Business Leaders Executive Program, you can be positioned to do the same in your organization.
Applicable business and leadership experience could include professionals who have been tasked with increasing operational efficiency and decreasing costs, deciding how many products to release in a certain time frame, or how to increase customer satisfaction/experience, and more. Professionals in roles that involve high-level strategic roadmapping are well prepared to excel in this Executive Program.
Executive Programs are intensive, strategically-focused programs that empower business leaders to rapidly understand complex and technical concepts, like Artificial Intelligence, and apply these concepts to high-stakes decision-making in real-world business scenarios.
An Executive Program is focused on teaching how to weigh implications related to strategic decision making that affect an entire organization or department. Unlike a Nanodegree program, which goes much deeper on the technical execution of using a specific technology, Executive Programs focus on the fundamentals of a particular technology, like Artificial Intelligence, and go deep into the key questions business executives should be considering around the application of those technologies, and the strategic implications that these technologies have at a corporate level.
Every Executive Program includes career services including a personal career coach, project reviews from industry professionals, technical mentor support so you can get help when you need it, and a flexible learning plan so you can learn at your own pace.
No application is necessary. This Executive Program accepts all applicants regardless of experience and specific background.
This program is intended for students who have spent time in a business setting, had exposure to business decision making, and have potentially worked on technical or IT projects.
In addition, a well-prepared learner will have:
The AI PM Nanodegree program is meant for product managers that are responsible for building and deploying AI products. Unlike the AI for Business Leaders Executive Program, the AI PM Nanodegree program is focused on the hands-on tasks of scoping a data set, training a model, and evaluating the performance of the model.
On the other hand, the AI for Business Leaders Executive Program is meant for people in management that make organizational or department-wide strategic decisions on what, where, and how to embed AI within a company.
Unlike the AI PM Nanodegree program, the AI for Business Leaders Executive Program focuses on the high-level strategic framework to evaluate the architectural design and technical implications of new business opportunities that leverage AI, and the process to enable adoption of AI within an organization. Moreover, it trains students to apply this strategic process to real-world business contexts.
The AI for Business Leaders Executive Program is meant for people in the organization who will define in which opportunities AI Product Managers should be responsible for owning products.
The AI for Business Leaders Executive program is comprised of content and curriculum to support one capstone project. Once you enroll in a Executive program, you will have access to the content and services for the length of time specified by your subscription. We estimate that learners can complete the program in four to six weeks, working approximately five hours per week.
The Capstone project will be reviewed by the Udacity reviewer network. Feedback will be provided, and if you do not pass the project, you will be asked to resubmit the project until it passes.
The AI for Business Leaders Executive Program can be completed in 4-8 weeks, working 5 hours per week. Two full months of access to the learning environment is included in your enrollment in the Executive Program.
Please see the Udacity Program FAQs for policies on enrollment in our programs.
The AI for Business Leaders Executive Program takes 4-6 weeks to complete, and costs $1599 (variable if purchased during a promotion) for two months access to the program. If you don’t finish the program before your two months of access are over, you will shift over to a monthly subscription plan, which will be $399 per month if you purchased the program at full-price, and a variable amount if you purchased during a promotional period.
You will use Google Sheets and Google Slides, or similar spreadsheet and slides software, and Google Forms to facilitate more practical exercises in the lessons and Capstone project. Jupyter Notebooks, which are embedded in the Udacity classroom, are used for some exercises and short explorations into code.
You will not be asked to write code in this course, so you will not need to have a Jupyter Notebook on your own computer.