8 AI & Business: What’s the Link?

^{Note. Retrieved from https://www.msemilylyons.com/harnessing-ai-in-entrepreneurship/}

By: Omar Alsari (O.A), Chimgozirim Anierobi (C.A), Nicolas Campanano (N.C), Ethan Clark (E.C), Yazan El Merini (Y.M), Isaac Ishimwe (I.I), Avik Joshi (A.J), Mirella Khayalieva (M.K), Joseph Li (J.L), Renaud Leroy (R.L), Kyle Lim (K.L), Owen Lor (O.L)., Malaika Loveys (M.L), Jisoo Moon (J.M), Alexandra Morozov (A.M), Faith Muluila (F.M), Devang Singh (D.S), Dylan Tang (D.T), Ekaterina Tkachenko (E.T), Shaista Karim Sadrudin Jaffer (S.K.J)

May 10, 2024 / University of Ottawa – Telfer School of Business Management

The FinTech Explorer: A Comprehensive Guide

AI & Business: What’s the Link – M.K, M.L, S.J

Imagine entering a world where business meets the cutting-edge technology of Artificial Intelligence (AI). This isn’t just a possibility—it’s what a group of middle-school students explored during a one-week course at the University of Ottawa. This course wasn’t merely about lectures; it was a hands-on journey into the intersection of business skills and AI technologies, offering them a unique opportunity to see how AI is reshaping the business landscape.

This chapter is authored by middle school students who participated in a mini-course specifically designed for young learners across the Ottawa-Carleton School Board. Held at the University of Ottawa, this program provided an immersive experience into the dynamic world of business and artificial intelligence, tailored to spark curiosity and foster understanding among students at an early age. The 19 students contributed to this chapter, outlining the course structure, activities, topics covered and much more!

The connection between business and artificial intelligence is deep and multifaceted. AI, which imitates human intelligent processes by machines, can revolutionize various aspects of business operations including decision-making, customer service, product development, marketing, and operations management. This course gave the students an excellent chance to develop and learn more about the transformative capabilities of business and AI.

As they embarked on this one-week journey, the students were asked to fill out a detailed survey. The responses revealed diverse levels of understanding among the students—ranging from novices in AI and business concepts to those with a modest foundation. This initial benchmark was crucial for tailoring the course content to ensure all students could engage meaningfully and grow from their unique starting points.

The course dove into how AI mimics human intelligence and transforms business operations. The adventures went beyond just understanding AI; the students were asked to apply what they had learned through activities like programming, data analysis, and even creating their own mini-businesses. This hands-on approach made the complex patterns of AI construction more understandable and engaging.

Each day followed a structured pattern filled with interactive educational experiences. It began with an innovative attendance check that quizzed students on their previous day’s learning, leading into group projects that simulated real-world business problems. These projects weren’t just theoretical—they required the students to apply their newly-developed AI knowledge in practical scenarios, helping them understand how AI tools like data analytics and machine learning could solve actual business challenges.

AI’s influence extends across various sectors, improving efficiency and effectiveness. It enhances areas like:

• Customer Service and Sales: Automating and personalizing customer interactions
• Marketing: Targeting and tailoring marketing campaigns
• Supply Chain Management: Optimizing logistics and predicting inventory needs
• Financial Services: Streamlining operations and risk management in banking

These examples illustrate AI’s role in not just augmenting existing processes but also in creating new ways to conduct business.

By the end of the week, the student felt empowered and knowledgeable, equipped to discuss AI and business topics comfortably and share their insights with others. This course not only educated them on AI’s current applications but also inspired them to think about their future role in driving innovation.

As they step back into their daily lives, they now carry with them a profound understanding of how AI can be a powerful tool in business. The knowledge gained has ignited their curiosity to learn more and keep up with AI as it evolves. Who knows? Maybe one day, they’ll be the ones leading the charge in using AI to solve the world’s big problems, blending their newfound knowledge with their youthful creativity to make a difference.

A Day in the AI and Business Course: A Structured Journey of Learning and Interaction – O.A, Y.M, S.J

The journey through the AI and Business course at the University of Ottawa was meticulously structured to maximize both learning and engagement. Each six-hour day was carefully planned to ensure a blend of instruction, application, and reflection.

1. Morning Engagement: Attendance with a Twist

Each day began with an innovative approach to attendance that set the tone for active participation. Instead of a simple roll call, the instructor engaged the students directly by asking questions related to the previous day’s lessons or challenges that were found to be intriguing. This method not only ensured that the students were attentive from the start but also reinforced their learning and prepared them for the day ahead.

2. Interactive Lectures: Multimedia Learning

Following the engaging start, a 30-minute lecture on various topics was given. These sessions were far from traditional; they included a PowerPoint presentation that detailed the day’s topic comprehensively, supplemented by carefully selected videos. These multimedia elements were not just supportive but were pivotal in enhancing the students’ understanding and making the learning process enjoyable and effective.

3. Collaborative Learning: Group Projects

After the lecture, the students were placed in groups to work on various projects. These were not mere academic exercises; they were real-world applications of the concepts that had been learned. Whether they were paired up or grouped by the project’s demands, the activities were designed to foster teamwork and practical application of theoretical knowledge. This part of the day was crucial for experiencing the intersection of AI and business first-hand, challenging the students to implement solutions in simulated business scenarios.

4. Recharging: Lunch Break

At noon, the students took a well-deserved hour-long break. This time was their own—to relax, eat, socialize, and enjoy the university’s scenic environment. It offered them a perfect midway pause to refresh and ready themselves for the afternoon sessions.

5. Afternoon Sessions: Review and Presentations

Post-lunch, the instructor again conducted a mini-lecture, recapping the morning’s content to refresh memories and align everyone for the afternoon activities. Subsequently, the focus shifted to group presentations. Each group had about 45 minutes to prepare before showcasing their findings to the class. During these presentations, the students engaged in an innovative feedback process using QR codes linked to a Google Form, ensuring that the feedback was constructive and unbiased. This required the students to be attentive during their classmates’ presentations and to ask questions freely through a digital platform.

The structure of the course was designed not just to impart knowledge but to cultivate skills and enthusiasm for AI and business. From the start of the day with a thought-provoking attendance routine to the end with leisurely peer interactions, each element was crafted to contribute to a holistic educational experience. This structure ensured that the students could engage deeply with the material, apply it practically, and leave each day enriched and excited for the next.

Comprehensive Overview of the Topics Covered in Our AI and Business Mini-Course – A.M, K.T, S.J

Various topics were covered throughout the five-day course, giving students an insight into the landscape of AI used in various businesses and industries. By participating in the lectures and participating in the group activities, the students were able to get a first-hand experience in being able to apply the basic tools to solve complex real-world problems.

Topic #1: Business analytics 

Business analytics is the science of using data to identify trends and solve business problems. This field encompasses various techniques such as sales forecasting, which analyzes historical sales data to predict future trends, and fraud detection, which scrutinizes data patterns to identify anomalies indicative of fraudulent activities.

Topic #2: Big data

Big data refers to extremely large data sets that traditional data processing software cannot handle effectively. It is characterized by the four Vs: volume, velocity, variety, and veracity. Big data spans multiple domains such as social media, finance, and healthcare, comprising structured, unstructured, and semi-structured data that continually expands over time.

Topic #3: Artificial intelligence

Artificial intelligence, a cornerstone of modern computer science, focuses on creating machines capable of performing tasks that typically require human intelligence. This includes developing AI-powered personal assistants that perform a variety of services and tasks based on voice commands or typed instructions.

Topic #4: Programming

Programming involves writing, testing, and maintaining code that allows software programs and applications to function. The primary programming languages include Python, Java, and C++, with programmers ensuring that software operates efficiently, updates continually, and performs optimally against new data inputs.

Topic #5: Data management 

Data management is the practice of organizing and maintaining data processes to ensure the accuracy, availability, and security of data within an organization. This field involves a comprehensive set of disciplines, from the creation of policies and governance to the deployment of technologies that support data collection, storage, and access.

Topic #6: Machine learning

Machine learning, a subset of AI, involves algorithms that enable software applications to become more accurate in predicting outcomes without being explicitly programmed. There are three types of machine learning: supervised learning, which trains on labeled data; unsupervised learning, which operates on unlabeled data; and reinforcement learning, where algorithms learn to react to an environment dynamically.

A survey was conducted on the first day to gauge the students’ baseline knowledge of AI and business concepts. This survey aimed to identify their starting points, with questions ranging from basic definitions to more nuanced applications of AI in various sectors. The intention was to dynamically tailor the course content, ensuring that each lesson was accessible yet challenging, fostering a productive learning environment for all participants.

The results of this survey highlighted a wide spectrum of understanding among the students, ranging from beginners who were just encountering the concepts of AI and data analytics to those who had some prior exposure to basic programming and business principles. Of the 19 students in the course, 53% were age 13, 37% were age 14 and 10% were age 15. 89% of them were in Grade 8 and 11% were in Grade 9. The insights gained from the survey were invaluable for the instructor, who adapted the course modules to address these gaps and build on the existing knowledge, setting a solid foundation for the advanced topics introduced later in the week. The summary of survey results are shown in the figures below.

The exploration of these topics throughout the mini-course has profoundly enhanced the students’ comprehension of the interplay between AI and business processes. The course was not only informative but also exceedingly enjoyable, providing them with insights and tools that can be applied in real-world scenarios.

Reflecting on the survey from the first day, the progress made became evident during a pop quiz mid-week. The 20-question quiz, covering key concepts from AI to big data management, showcased a significant uplift in the comprehension and confidence of the students. Questions that had once seemed daunting were now met with thoughtful and accurate responses, reflecting their deepened understanding. For example, one question on the quiz asked which programming language is commonly used for data analysis and developing AI applications and all 19 students accurately selected “Python.” Other questions asked what the relationship is between AI and business analytics, definitions of AI, ML, NLP and Big Data, examples of each of the topics covered and basic Python syntax. The class average was 88.9% which shows an exceptional improvement over just the first few days of the course!

However, it was not solely the quiz and survey that measured the students’ success; the daily activities themselves played a crucial role. These activities demanded critical thinking and an analytical mindset, as students were required to manually perform tasks that AI could typically execute more swiftly and efficiently. This hands-on approach allowed students to appreciate the tangible benefits of integrating AI into business processes, providing a clear perspective on how technology can enhance traditional methods. The detailed exploration of these daily activities, and their impact on the students’ learning outcomes, will be further discussed in the following sections.

Dynamic Learning Activities in the AI and Business Mini-Course – I.I, J.M, R.L, S.J

Day 1: Introduction to Business Analysis through AI

The course kicked off with an engaging activity where students were asked to fill out a survey to better understand their level of knowledge about the topics to be covered throughout the one-week course. The students then tackled real-world business scenarios by analyzing provided data sets to identify and propose improvements. This exercise showcased the significant time-saving potential of AI in business analysis, highlighting its necessity in efficiently managing multiple business divisions.

Day 2: Deep Dive into Machine Learning and Coding

The second day began with an intriguing discussion, where a seemingly simple question about prioritizing hospital patients sparked diverse responses, emphasizing the subjective nature of decision-making in healthcare. Later, the focus shifted to machine learning concepts and the students were introduced to coding in Python. The instructor prepared a Google Colab Notebook to ease the process of running and modifying existing code. A simple exercise at the end of the notebook allowed students to develop short and quick codes in response to a given task. The progress was noticeable—tasks that seemed daunting on the first day felt more manageable, demonstrating our rapid adaptation and growing comfort with AI and business concepts.

Day 3: Debating AI’s Role in the Future of Work

The students engaged in a spirited debate on whether AI would eventually replace human jobs. This discussion broadened their understanding of AI as a tool that, while enhancing efficiency, is unlikely to replace human roles entirely but rather integrate them into professional lives. A quick quiz later in the day reaffirmed the learning progress, as the students answered questions more confidently and swiftly than on the first day.

Day 4: Hands-On Stations and Real-World Applications

The fourth day featured multiple interactive stations focusing on practical AI applications:

• Image Classification: Students manually categorized images into seven distinct groups, identifying images that could fit multiple categories.
• Business Review Analysis: Students analyzed customer reviews and assessed the performance of food businesses, as well as strategized improvements.
• Sports Success Prediction: The students were also tasked to develop criteria to predict the success of athletes in basketball and hockey based on data analysis.

Each station was designed to reinforce the understanding of AI’s versatility and its transformative impact across different industries.

Through a series of structured and creative activities, the students explored various facets of AI, including programming, chatbots, data management, and business analytics. The exercises not only deepened their knowledge but also ignited a passion for AI and business among many of the students. These activities, tailored to simulate real-world challenges, equipped them with insights and skills crucial for their own future endeavors in technology and business.

An Insight into Programming – E.C, S.J

On the second day of the mini-course, the students embarked on an in-depth exploration of programming, a foundational skill set in the AI landscape. Programming is not just about writing code; it’s about creating algorithms that enable machines to perform tasks autonomously. Various programming languages were discussed such as Python, C++, R, and JavaScript, highlighting their roles in developing AI solutions.

To apply their theoretical knowledge, the students engaged in practical programming exercises using Google Colab, a platform that facilitates coding in an interactive environment. Here’s what was accomplished during these activities:

• Basic Operations: The students started with elementary programming exercises such as performing arithmetic operations and printing text to the console, which provided them with a solid understanding of Python syntax and basic functions.
• Data Visualization: The students then created and modified scatter plots, which helped to visualize data in meaningful ways, enhancing their ability to interpret and analyze information.
• Data Manipulation: Utilizing Excel documents prepared by the instructor, the students practiced manipulating lists and extracting data, skills crucial for handling and analyzing large datasets in real-world applications.

Throughout this session, several tools were utilized to enhance the learning experience and efficiency:

• Google Colab: This platform allowed the students to write and execute Python code seamlessly, providing an intuitive interface for learning programming.
• ChatGPT: Students explored how AI can assist in coding by using ChatGPT to understand coding queries and generate coding snippets.
• Excel Documents: These were used to provide practical examples of data that could be manipulated and analyzed through programming.
• Online Tutorials and APIs: Additional resources such as online tutorials and Google Colab’s API creator were discussed as means to further our understanding and capabilities in programming.

Students learned that programmers play a crucial role in the AI ecosystem. They are responsible for designing algorithms that not only process and analyze data but also learn from it to make predictions or decisions autonomously. This session illuminated how integral programming is to AI, providing the tools for machines to mimic human decision-making processes.

This programming session equipped the students with the basic skills and understanding necessary to delve deeper into the technical aspects of AI. It underscored the importance of programming in the modern world, particularly in how AI applications are developed and deployed. With the foundational knowledge gained, the students are encouraged to further our programming skills through additional courses and self-study, enabling them to better understand and contribute to the evolving field of AI.

By grasping these programming fundamentals, they can engage in more informed discussions about AI, appreciate the complexities of AI systems, and envision future innovations in technology. The insights from this exercise have not only enhanced our technical acumen but also sparked a curiosity to explore how programming continues to transform their interactions with technology in daily life.

Deep Dive into Machine Learning: Understanding Through Practical Exercises – C.A, F.M, S.J

Students were also taught the foundational types of machine learning: supervised, unsupervised, and reinforcement learning. These concepts formed the bedrock of how AI systems learn from and interact with data. Supervised learning involved models learning from labeled data, unsupervised learning from unlabeled data, and reinforcement learning from the consequences of decisions made by the model.

Practical Exercises in Machine Learning:

1. Image Classification:

• Objective: The students manually categorized a set of 66 images into seven distinct groups: scenery, landmarks, animals, insects, natural phenomena, machinery and tools, and transportation.
• Process: Through group discussions, they worked collaboratively to understand and assign each image to the appropriate category. This exercise was not only about identifying the category but also about engaging in critical thinking when images could fit into multiple categories.
• Challenges: Some images were straightforward, while others required more in-depth analysis and discussion, highlighting the complexities of image classification tasks in machine learning.

2. Predictive Modeling for Sports Analytics:

• Objective: Using simple datasets for basketball and hockey players, the task was to predict the success of players based on various attributes.
• Basketball Analysis: Students considered factors like years of experience, points per game, and player age. Their analysis concluded that successful basketball players often had more than three years of experience, scored more than 10 points per game, and were older than 21.
• Hockey Analysis: For hockey, attributes such as shot accuracy, weight, and agility were pivotal. Successful players typically had a shot accuracy higher than 70%, weighed over 180 lbs, and had an agility score of at least 6.8.

3. Sentiment Analysis:

• Objective: The students analyzed customer reviews for four companies, classifying each review as positive, negative, or neutral.
• Process: Keywords were identified that linked to the sentiments expressed in the reviews. This exercise helped them understand how sentiment analysis could be used to gauge customer satisfaction and areas for improvement.
• Analysis: For instance, one particular group noted that Company C received neutral to negative feedback primarily concerning food quality. They suggested improvements such as enhancing training for food preparation staff or hiring more skilled personnel.

Each of these activities not only reinforced their understanding of machine learning concepts but also provided practical experience in applying these concepts to real-world data. The hands-on approach helped solidify their knowledge and boosted their confidence in discussing and utilizing AI and machine learning in various contexts.

By the end of these exercises, the students were better equipped to understand the implications of machine learning in different sectors and the potential of AI to transform industries. This day was particularly enlightening, as it bridged the gap between theoretical knowledge and practical application, showing them the powerful impact of AI in business and beyond.

Mastering AI and Business Concepts Through Student Presentations – N.C, A.J, S.J

During the week-long course, the students had the opportunity to dive deep into the practical aspects of AI and business through structured presentations. These presentations were not just about sharing what they had learned; they were a chance to apply their knowledge to real-world scenarios and explore innovative solutions.

Crafting these presentations was both challenging and exhilarating. Students tackled topics across AI, machine learning, business analytics, big data, and data management. The process encouraged them to synthesize information and think critically about how to present complex subjects in an understandable and engaging manner. This hands-on approach helped solidify their understanding and allowed them to explore the practical implications of theoretical knowledge

The presentations became a showcase of creative and practical applications of AI in various fields:

• Food Production Enhancement: One group explored how AI could optimize agricultural practices to boost food production. Their proposal aimed at using predictive analytics to enhance crop yields and reduce waste, addressing global food security concerns.
• AI-Powered Travel Recommendations: Another group focused on the tourism industry, presenting a system that uses AI to tailor travel suggestions to individual preferences and current trends. This project highlighted AI’s potential to personalize experiences and improve customer satisfaction in the service sector.

The presentations were a critical component of our educational journey. They provided a platform for the students to express their ideas and solutions, fostering a dynamic learning environment. They not only improved their presentation skills but also deepened their understanding of how AI can be leveraged to solve complex problems in business and beyond.

The presentations culminated in a final project where each group developed a business idea that leveraged the tools they learned throughout the week. They were tasked with thinking critically about their business workflow, potential implementation strategies, and the expected impact of their ideas:

• Cyber-Bullying: One team proposed using AI to detect harmful speech and content on social media platforms to combat cyberbullying. Their system would block inappropriate content and notify parents or guardians, enhancing online safety for minors.
• Protecting the Environment with AI: Another group focused on environmental conservation, using sensors and drones alongside historical data to predict and mitigate potential threats to wildlife and natural habitats before they could cause harm.
• Education.Poverty.AI: This initiative aimed to tackle educational disparities by providing AI-powered online tutoring for students in impoverished regions. The system would offer personalized learning experiences in multiple languages, adapting content to fit individual learning styles and needs.
• Travel.AI: The winning team developed a business that used AI and ML algorithms to analyze business reviews and locations from platforms like Google Maps and TripAdvisor. Their service would generate personalized travel itineraries based on a user’s budget and preferences, such as beachside stays or food experiences.

These innovative projects showcased the students’ ability to apply AI in solving significant issues across various domains. The presentations provided a dynamic platform for students to express their ideas and solutions, fostering a collaborative and engaging learning environment. Not only did they enhance their presentation skills, but they also deepened their understanding of how AI can be leveraged to address complex problems in business and society.

The presentation sessions proved invaluable, enriching the educational experience by allowing students to actively engage with the material and each other. These activities demonstrated the power of AI and business analytics to drive innovation and offer solutions to real-world challenges, laying a foundation for future exploration and application in the fields of technology and business.

Reflections on AI and Business: Student Perspectives and Insights – J.L, K.L, S.J

The AI and Business course at the University of Ottawa provided a transformative experience for all participants. Over just five days, the understanding of artificial intelligence and its applications in business deepened significantly. This section compiles the diverse opinions and reflections from the class, capturing the essence of their collective learning journey. Here are some of the thoughts shared by students about the course:

• Jisoo: “I loved the course. It was very interesting to learn about the business side of AI.”
• Roy: “It was very interesting, and I learned things that I can use in the future.”
• Isaac: “I enjoyed this course and learned about big data.”
• Faith: “The course was fun. I learned about big data.”
• Ella: “It was a really fun course. The activities were fun and engaging. During the debate about if AI would take over the world, I made a good point: ‘Just because we made AI, it doesn’t mean we can control it. Your parents made you but they can’t control you.'”
• Ethan: “I enjoyed this course. Also, I liked learning about the large gap between analyzing data manually versus how efficient it is when AI does it.”
• Alexandra: “I enjoyed this course, I learned about artificial intelligence and how to program.”
• Mirella: “I enjoyed this course and learned about how to use AI and ML.”
• Owen: “It was alright, I learned what big data is and how to use it in your daily life.”
• Devang: “I think it’s good, the most interesting thing is Python programming and AI.”
• Nicolas: “The course was fun and I met very fun and amazing people. I learned AI and how to use it for business.”
• Avik: “It was good, I learned about ML.”
• Malaika: “Now I feel more comfortable to talk about this subject. I learned how AI can help us in many ways.”
• Dylan: “I learned a bit about AI, and now know how to use it. It was fun.”
• Omar: “I learned how to make business decisions using AI and learned how to program in Python. It’s really good, one of the best courses because in the future you can use the knowledge to make a lot of money.”
• Kyle: “I LOVED this course. SO many new and amazing people! I learned a lot about ChatGPT and how to do interesting things!”
• Joseph: “I found this course very helpful for my future aspirations. I learned a lot about how businesses can be modeled using ML and AI. I feel more comfortable now to talk about these types of topics.”
• Yazan: “I learned a lot about what chatbots are, and how they can make better business decisions. This course is very important because business is important.”
• Kate: “I really like this course, and I learned about analyzing a business dataset and inferring it.”
• Ms. Jaffer: “I think that this class did exceptionally well this semester. I’m really happy with the progress and I’m actually really impressed with how much the students learned based on how they performed in their presentations, and what kind of knowledge they were able to share based on what they found in their findings in class.”

In summary, the AI and Business course not only educated the students but also sparked a deeper interest in technology and entrepreneurship. As they move forward, the insights and skills they’ve acquired here will undoubtedly influence their future endeavors.

“A special thanks to Ms. Jaffer for her dedication and for providing such invaluable lessons.” – J.L

Conclusion – O.L, D.S, S.J

The four-day course at the University of Ottawa provided an enlightening exploration into the realms of business and artificial intelligence. This educational adventure taught participants not only the foundational concepts of Business Analytics, Big Data, AI, Programming, Machine Learning, and Data Management but also their practical applications in real-world scenarios.

Each topic introduced was coupled with examples of how these technologies are being employed to foster advancements and solve problems across various sectors. The course brilliantly outlined both the benefits, such as efficiency and innovation, and the potential drawbacks, including ethical dilemmas and the high costs associated with technology deployment.

To solidify their understanding, the course was structured around interactive activities that mirrored real business challenges. For instance, participants crafted a workflow chart for a machine learning project, following all essential steps from data gathering to model monitoring. They tackled exercises that required making informed business decisions based on data analysis and explored the role of Big Data in industry-specific contexts.

A significant portion of the learning was devoted to programming, particularly Python, which is pivotal in developing machine learning models. Participants experienced firsthand how to build simple AI systems, like chatbots, enhancing their appreciation for the technology’s accessibility and potential.

The final challenge was to synthesize all they had learned by devising a comprehensive business plan, which was evaluated by experts in the field. This not only tested their newfound knowledge but also boosted their confidence in applying these concepts.

As the course concluded, participants realized that their initial apprehension about complex topics like AI and business analytics had tranformed into confident understanding. It was eye-opening to discover that many professionals in the field might not fully grasp these concepts despite their expertise, highlighting the value of their educational experience. The course concluded with a case competition where participants applied all the concepts learned to create innovative business solutions. Judged by industry experts, their final presentations scored highly, with feedback highlighting their advanced understanding and creative application of AI in business scenarios. This was a testament to not only their hard work but also the effectiveness of the educational journey they embarked upon.

This course proved to be an exceptional starting point for anyone, regardless of prior exposure to the subjects. It demystified the essential elements of AI and business, making them accessible and engaging. This experience has equipped participants with the knowledge to potentially apply these powerful tools in their future careers and daily lives.

Participants left the course not just with deeper knowledge but with genuine enthusiasm for the future of AI and business. They are eager to see how each of them might use what they’ve learned to innovate and lead in their future endeavors. A heartfelt thank you goes to all the instructors and peers who made this journey not just educational but truly transformative.