This course is part of the AI for IT Professionals Training program.
Artificial intelligence (AI) is rapidly transforming the information technology (IT) landscape. This course helps IT professionals, technical managers and business analysts stay ahead by providing a clear, practical understanding of AI technologies and their real-world applications in IT, finance and operations.
Designed for practitioners—not researchers or developers—this course focuses on how to evaluate, integrate and discuss AI solutions within your organization. You will also explore key ethical, operational and business implications, including data privacy, bias, and sustainability.
By the end of this course, you will be able to:
- AI fundamentals & business relevance
- Understand key AI and machine learning concepts
- Identify common AI approaches, including discriminative and generative models
- Identify the right tools and assess their value for business processes
- Explore AI applications across IT, finance and operations
- Data & ethics
- Grasp AI data requirements and privacy considerations
- Evaluate ethical concerns: bias, fairness, transparency, sustainability and environmental impact
- Practical application & integration
- Identify opportunities to integrate AI into workflows
- Apply AI to solve real-world problems
- Discuss AI confidently with stakeholders and technical teams
- Generative AI (GenAI) essentials
- Understand the principles of GenAI and when to use it
- Explore and implement generative modeling approaches (e.g., GANs, VAEs, transformers) using popular frameworks
- Implement GenAI for text, image, video and music generation
- Analyze the ethical and societal impact of GenAI
- Emerging trends & workforce impact
- Stay current with AI innovations including large language models and regression theory
- Explore embedded, bespoke, platform and individual AI, and their roles in enhancing user experience and streamlining business operations
- Examine how AI impacts employees in their daily work
Course Outline
Week 1
- Module 1: AI & ML Fundamentals for Organizations
- Module 2: AI Toolkits: Platforms, APIs & Frameworks
- Module 3: Data Foundations for AI & Privacy
- Module 4: AI in Action: Applications Across Industries
- Module 5: Responsible AI: Bias, Fairness & Impact
- Module 6: Four Prevalent Principles of AI Ethics
- Module 7: Getting Started with Generative AI
- Module 8: Generative AI Models and Applications
- Module 9: Creating with AI: Text, Image, and Beyond
- Module 10: GenAI Ethics: Risks and Responsibilities
- Module 11: AI at Work: Impact on Daily Tasks
Week 2
- Final Module: Mini-Capstone Project & Course Wrap-Up
How am I assessed?
You’re assessed on successfully completing weekly activities, quizzes, including your contributions to discussion posts and a mini-capstone project. These activities are marked using a proficiency scale, and your instructor provides you informal feedback in the live sessions.
While you’re not assessed on your attendance of the live sessions, we encourage you to attend these classes, so you don’t miss the opportunity to learn and interact with your instructor and other participants. All sessions are recorded in case you miss one.
Expected effort
Expect to spend approximately 12-14 hours per week per course completing all learning activities, including attending live sessions online.
Technology requirements
To take this course, you’ll need access to:
- an email account
- a computer, laptop or tablet, using Windows or macOS
- the latest version of a web browser (or previous major version release)
- a reliable internet connection
- a video camera and microphone
Requisites
n/a
Course format
This 100% online part-time course consists of instructor-supported real-time classes combined with independent study. All sessions are recorded in case you miss one.
Course activities include quizzes, case studies, group discussions, and a capstone project, supported by self-paced materials such as readings, instructional videos, podcasts and real-world scenarios.