A 6-week program combining live classes, real-world projects, and case studies. Be ready to tackle complex and strategic AI projects that can transform businesses.
Harness the transformative power of artificial intelligence for your company, and your career.
Artificial Intelligence is revolutionizing the way business is done across industries, and becoming one of the fastest-growing segments of the tech industry. According to IDC, corporate investment in AI is expected to hit $500 billion by 2024 for an annual growth rate of 16.4%. It’s vital for leaders to understand how to make use of the power of AI to achieve competitive advantage and avoid disruption. But it’s not all about technology, but also about ensuring you’re solving the right problems and that the project is set up for success.
After taking this course, you will be able to make a convincing case to your company to embark on an AI project, determine what problems AI can solve for your business, and leverage the best practices from cutting-edge companies to ensure your AI project succeeds.
If you want to lead an AI project at your company, or are currently working on one, this course is for you.
|Cohort Name||Class Period||Registration Deadline||Total Seats|
|Jan 22, 22 - Mar 12, 22||Fri - Jan 22, 21 - 5:00 PM UTC||35|
Class PeriodJan 22, 22 - Mar 12, 22
Registration DeadlineFri - Jan 22, 21 - 5:00 PM UTC
Typical week in the cohort
Communication and networking are core components of the ClasspertX course experience. In this course, you will be part of a global learning community. In order to accommodate all participants, we have designed much of the course experience to take place asynchronously, with a synchronous class session that occurs weekly on Saturdays
Reading from the book
Includes a free copy of the book
This course is centered around Implementing AI Systems: Transform Your Business in 6 Steps which will be used as a supplementary material for the classes
- Students will be prompted to submit questions during the week, and the instructor should choose questions to answer for students during the weekend sessionSync Sessions on Zoom~ 2 hours of lectures and exercises on the weekend
- Q&A with the instructor
- Additional demos / examples of key topics
- Group practice - students break out to work on an exercise
- Group discussion
- Review some of the basics of AI - definitions and concepts
- Look at the reasons for this course and the opportunities for the industry
- A brief history of AI
- Learn about supervised learning, unsupervised learning and reinforcement learning
- Understand the fundamentals of machine learning (look at algorithms like regression, support vector machines, random forest, etc)
- Look at deep learning and concepts like backpropagation
- Learn about newer approaches like GANs
- Review natural language processing (NLP)
- Identify the problem to be solved with AI
- How to evaluate off-the-shelf AI systems
- Understand the factors for AI projects (ROI, data availability, business goals)
- Look at case studies of AI (Intuit, Halliburton, Lex Machina)
- Understand how to build an AI team (data scientists, business analysts, data engineers, AI testers)
- Understand the basics of database technologies (data warehouses, relational systems, NoSQL, cloud platforms)
- Learn about effective ways to collect and evaluate data sources
- Understand how to clean up data
- Understand data labeling
- Learn about data simulation
- Understand the available AI tools (open source and proprietary systems)
- Learn how to select an AI model
- Understand how to train a model
- Look at how to do feature engineering
- Understand the different ways to measure the accuracy of a model
- Understand the types of ways to deploy AI
- Learn about the use of MLOps
- Show how to test and monitor the model
- Look at how to use security
- Understand strategies for change management
What you'll learn
- Make a convincing case to your company to embark on an AI project
- Leverage the best practices from cutting-edge companies
- Learn about the core foundations of AI, including machine learning, deep learning and natural language processing (NLP)
- Determine what problems to first address with AI and not be distracted by common dead-ends
- Know when to buy an off-the-shelf solution
- Show how to build the right AI team, such as with data scientists, data engineers, and testers.
- Learn various techniques for locating and preparing data sets
- Look at how to create the right models
- See how to effectively deploy AI, such as with real-time updates, monitoring and security
Who this course is for
Who this course is forTarget Audience
- Managers of mid-size or large organizations who want to take on an AI project or are currently working on one.
- Non-technical people who need to have a high-level understanding of AI technology
- Founders of tech startups and software developers who want to get a better understanding of the topics involved in AI
- There are no prerequisites for this course.
Tom Taulli is an advisor/board member to startups and the author of Implementing AI Systems: Transform Your Business in 6 Steps and Artificial Intelligence Basics: A Non-Technical Introduction. He also writes a column for Forbes.com, where he covers topics like AI and RPA. Besides his writings, Tom has founded several high-tech companies. They include WebIPO, BizEquity and Hypermart.net, which was sold to InfoSpace.
- Author of Implementing AI Systems: Transform Your Business in 6 Steps
- Author of Artificial Intelligence Basics: A Non-Technical Introduction
- Columnist for Forbes.com
- Founder of several tech startups
If you are a CEO of a MNC with AI and digital transformation as part of your roadmap, the founder of a tech startup, a software developer or someone who wants to get a better understanding of the topics involved in AI, the book is a must read for you.
Tom has provided the reader with a clear breakdown of the past, present, and future of artificial intelligence. The case studies are especially useful as a resource and strategic guide for decision-makers to understand all of the important criteria for implementing AI systems.
This is an up-to-date primer on the value of AI and a real-world look at what it really takes to execute AI projects successfully.