Using AI in business is no longer about getting a competitive advantage. Now, it's about staying in the game.
This leading-edge course will teach you fundamental AI skills that you can put to work right away solving challenges in your business, product, or field — no previous coding experience required.
Now, the ability to understand and use advanced technologies is the expectation for a growing number of non-technical positions. In live classes and workshops, IBM's Director of Data Science and AI Elite will teach you practical AI skills and empower you to leverage data dynamically and own innovation in your role.
This course is packed with hands-on practice, live labs, and feedback sessions. Why? Because your business doesn't run on "theory". You'll learn and practice converting your data into a source of AI and hear from two accomplished guest speakers on how they innovate and implement AI projects in business.
Learn how to build an AI-ready culture at your organization, from the man bringing AI to businesses globally as a head of IBM's AI Elite. Armand will coach you on how to work effectively with Machine Learning Engineers and provide clarity into practical concerns when hiring for these roles.
Armand will get you comfortable with common development tools and concepts used in data analytics and AI-assisted products. You'll train your first basic neural network, master the art of visualizing and interpreting data, and get access to insights and cheat sheets for bringing your own AI project to production.
You'll ideate a use case for your own organization and prepare a strategy for a 3-month AI project. Define your project scope, success markers, and more, working from a template used by world-class organizations. Then, you'll refine your strategy with valuable feedback from your peers and Armand.
Everybody wants to do AI but nobody knows where to start. Today, we're starting. You will learn about what AI is, its business applications and use cases, and set terminology and definitions.
Assignment 01: Give three use cases of AI implementation for your current industry. How would you explain its value to your boss or other decision makers to justify the investment, without using technical terms?
The foundation of AI is simple: data. In this class, you will learn how to get data ready for use - training AI. I will give you a lay of the land in terms of big data, management, and infrastructure, and then we will prepare a dataset together using a free online tool.
Assignment 02: In the provided use case, you will have to access a retail dataset and get it ready to train a model. You will be asked to connect to the dataset, extract and understand important features, and merge it with other related datasets that will be provided for the exercise.
We will start to get our hands dirty by training a linear regression model. But first, I will introduce you to three simple but powerful machine learning techniques and share insights into choosing the best one for a project.
Assignment 03: We will train an AI model with the dataset that you prepared in Assignment 2 and get predictions using an online tool.
Today, we're getting technical. In this class, you will learn core concepts about deep learning & neural networks, which will serve you as you coordinate projects with Data Scientists. Then, we will train our first neural network together in class.
Assignment 04: In this assignment, you will learn how to create a deep learning model to classify cars by brand. Then, you will do the same with a model that classifies text reviews as positive, neutral, or negative.
Storytelling is as important in data as in any other business pitch. In this class, I'll show you how to choose the most effective visuals for your data set, how to shape data into meaningful narratives, and I'll demo a data visualization tool you can use on your own team.
Assignment 05: Record a short, compelling video telling a story about the results in the dashboard we built in class (3 min max).
What kind of AI tools will serve you best in a given project? In this class, I'll give you an AI Tools Cheat Sheet and help you understand how to choose the best one for your use case and skills. Then, we'll use IBM Watson Studio to solve a use case end-to-end.
Assignment 06: Continue writing queries on your own which modify existing data by renaming variables and changing data types. Perform within-query calculations to create new variables.
In this class, I will show you how to put everything you're learning into production and into life. We will talk about why most AI systems never make it to production, what makes it so difficult, and how to overcome those obstacles. Then, we will deploy our first AI model using the data and systems we've developed so far.
Assignment 07: Build on the model we've moved towards production in today's workshop. Create an end-point that can be integrated into an application to make it smarter.
If we're building something that's going to be impacting many people, we need to make sure it's ethical and it's something we can trust. This class focuses on designing AI projects to be ethical, transparent, and trustful.
Assignment 08: Continue using OpenScale and to trust the model built in previous assignments.
How can you enable the culture shift needed for AI in your current business role? In this class, we'll take a look at use cases from several industries in which organizations were able to successfully make that shift.
Assignment 09: Knowledge check quiz.
Carrying out an AI project is a lot like any other kind of project planning. It's vital to create order, to understand the investment, and to know who is who and the responsibilities of each role. We will learn holistic strategies for managing these questions and I will share with you a template you can use to set your own implementation plan and success metrics.
Assignment 10: Select a use case for your industry and plan its execution and success, using the project template.
When you're ready to bring Data Scientists on board, what do you need to know to maximize your investment? In this class, we'll learn about data talent management from hiring to retention and effective communication.
Assignment 11: Using the template you received in class, deliver an AI strategy for your role that is achievable within 90 days.
Our last class is training for one of the most important parts of successful projects: giving feedback. I will share tips for how to be precise in your feedback. Then, you will present your 90-day AI plan and get feedback from your peers and me.
"Instructor is very knowledgeable and provides relevant information."
"I really appreciate all the examples and use case shared, as well as the demos - connecting theory to practice."
"This is a cutting edge topic and the instructor has a lot of perspective and real world experience."
N Brereton Medical Technologies, LLC
"The quick and relevant feed back along with the flexibility."
"Armand is really informative"