This 3-day workshop offers a beginner-friendly, hands-on introduction to Artificial Intelligence and Generative AI, designed for non-techies, enthusiasts, and programmers alike. Participants will explore core AI concepts and real-world applications, including text, image, audio, and video generation using tools like ChatGPT, DALL·E, and Whisper via Python APIs. The workshop also demonstrates how to use Microsoft Copilot to enhance productivity in Microsoft 365. Attendees will gain practical experience, learn ethical best practices, and avoid common pitfalls in deploying AI models. A comprehensive list of add-on modules is also available to extend the workshop beyond the core curriculum.
Duration: 3 Days
Course Code: BDT481
Learning Objectives:
By the end of this workshop, participants will be able to:
| Topics | Brief Overview |
|---|---|
| Introduction to Artificial Intelligence | An accessible introduction to Artificial Intelligence, its core technologies, and real-world applications. |
| Introduction to Generative AI | A hands-on introduction to Generative AI, focusing on creating and applying models that generate new content. |
| Generative AI Model Overview | A hands-on introduction to OpenAI’s generative models, including DALL-E and Whisper, using the Python API. |
| Prompt Engineering Techniques | A hands-on course that teaches practical techniques to design effective prompts for optimizing the performance of generative AI models like ChatGPT. |
| Introduction to MS Copilot | Leverage Microsoft Copilot to boost productivity, automate tasks, and enhance decision-making within Microsoft 365 applications. |
| Dos and Don’ts of Gen AI | A concise session on best practices, common pitfalls, and ethical considerations in training and deploying generative AI models. |
This session offers a friendly introduction to Artificial Intelligence (AI), breaking down its key concepts, including Machine Learning, Deep Learning, and neural networks. Participants will explore how machines learn, the critical role of data, and see AI in action through a guided demonstration. The session dives into how machines learn, the pivotal importance of data, and the differences between shallow and deep neural networks. It also introduces advanced concepts like Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), along with their practical use cases. The session also highlights real-world AI use cases and helps identify opportunities for applying AI within your organization.
List of Topics Covered
This session introduces participants to the fascinating world of Generative AI, where machines can create images, text, and other forms of data. Learners will explore core generative models like GANs and VAEs, understand their architectures, and engage in hands-on exercises to build and train these models. The session also covers creative applications, ethical considerations, and emerging trends in this rapidly evolving field.
Building upon foundational AI knowledge, this session delves into Generative AI—a branch of AI focused on enabling machines to generate new and original content. Participants will learn about the architectures and working principles of key generative models, such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs). The session offers practical sessions on training GANs for image generation and VAEs for data synthesis. Real-world applications across creative industries, ethical challenges of generative content, and future advancements in the field will also be discussed, empowering learners to explore innovative use cases and understand the broader impact of Generative AI.
List of Topics Covered
This session offers a practical overview of Generative AI using OpenAI’s powerful models. Participants will learn how to access and work with the OpenAI Python API, explore image generation with DALL-E, and convert audio to text using Whisper. The session provides hands-on coding experience, enabling participants to generate creative outputs and understand the broader applications of these models.
The training introduces participants to OpenAI’s generative ecosystem, emphasizing practical use of the OpenAI Python API. Learners will explore the capabilities of key models, including DALL-E for image generation and Whisper for audio-to-text conversion. Through guided coding sessions, participants will gain experience in setting up the API, configuring essential parameters, and generating creative content programmatically. The session also highlights the significance of OpenAI’s models within the broader landscape of Generative AI, providing learners with the skills to kickstart their journey into developing applications using these state-of-the-art tools.
This session introduces participants to Microsoft Copilot, showcasing how AI is transforming work inside Microsoft 365 apps like Word, Excel, Outlook, Teams, and PowerPoint. Through hands-on exercises, learners will explore Copilot’s capabilities in content generation, data analysis, and communication enhancement. The session also emphasizes best practices, ethical considerations, and real-world applications to maximize Copilot’s impact in daily workflows.
This hands-on session focuses on integration across the Microsoft 365 ecosystem to automate workflows and enhance productivity. Participants will learn how Copilot elevates tasks in Word, Excel, Outlook, Teams, and PowerPoint by streamlining document creation, automating data analysis, assisting in email management, and enhancing presentations. Real-world scenarios and interactive exercises will equip learners to use Copilot effectively for report generation, meeting notes, data insights, and professional presentations. The session also covers best practices for integrating Copilot into daily workflows, understanding its limitations, and ensuring ethical and secure usage of AI-powered tools.
List of Topics Covered
This session equips participants with practical knowledge on the dos and don’ts of training generative AI models. It emphasizes critical success factors, pitfalls to avoid, and ethical responsibilities when working with generative AI systems. Through real-world case studies, participants will learn to make informed decisions and ensure responsible AI practices in their projects.
This session includes a focused exploration of best practices and common mistakes in training generative AI models, addressing key factors like prompt engineering, high-quality data, model selection, and robust evaluation techniques. Participants will gain insights into common pitfalls such as overfitting, underfitting, and biases that can undermine AI model performance and fairness. The session also covers ethical considerations and responsible AI guidelines to ensure transparency, fairness, and accountability. Real-world case studies and industry examples will help participants contextualize these lessons, while a look into emerging trends and future challenges will prepare them for evolving demands in generative AI development.
List of Topics Covered
