Applied Graduate Certificate in AI Driven Business Intelligence

Unlocking the Value of Data and AI for Your Organization

Most organizations are aware of the need to utilize data from their operations to gain insights into performance and support decision-making. They recognize the power of artificial intelligence (AI) to automate data analysis and generate insights. However, knowing where and how to start can be challenging. Hiring tech specialists is not enough. Organizations also need skilled leaders who can connect the technology to real-world business activities and strategies.

For employers across all sectors, the window to develop or recruit people with these critical skills is right now. For current employees or potential new hires with specialist or working knowledge of key technologies, there is an opportunity to widen your skill set to harness the technology for the benefit of the hiring organization. This program will address the skill sets you need to step up to this challenge.

The Canadian Government has identified a critical shortage of skilled labor in diverse sectors such as energy generation, public utilities, finance, retail, and manufacturing, particularly in the skills needed to adopt and apply these technologies. The opportunity is now to distinguish yourself from others with a program that gives you the credentials and skills required to perform and get noticed.

This is a 6-month program taught over 3 terms (8 weeks per term) to help participants build up the 3 core competencies that are most important for future business challenges: data analytics, project management, and communication strategies. Our program offers real-world knowledge and expertise to help you turn data into valuable insights and communicate in a powerful and engaging way. Upon completion, graduates will earn an Applied Graduate Certificate (AGC) and be recognized as highly sought-after professionals.

Develop your future-ready skills today.

1: GenAI: Overview

This module offers a comprehensive overview of Generative AI (GenAI), covering its business case, capabilities, and future potential. Participants will explore how GenAI compares to standard artificial intelligence (AI), what passing human-designed tests like the Bar exam really means for its real-world abilities, and common issues like hallucinations. The module also addresses future trends, including the impact of AI on jobs and what to expect as GenAI continues to evolve.

2: GenAI: LLMs

This module introduces participants to using large language models (LLMs) for parsing PDFs with tools like LlamaParse. Participants will learn to automate data extraction, especially from tables, gaining practical experience in turning unstructured data into useful insights.

3: GenAI: RAG

In this module, participants will learn to build a GenAI system on Google Cloud Platform (GCP) using large language models (LLMs) for reading and writing tasks. The session covers LLM limitations, efficient prompting, summarization, proofreading, and cost estimation for LLM-based applications.

4: GenAI: Image & Sound

In this module, participants will use Teachable Machine to apply no-code machine learning to image, video, and sound tasks. They will learn to collect data from webcams and microphones for sound classification and human pose estimation, gaining practical experience without needing to code.

5: Descriptive Analytics – Visualizing Data Relationships

This module introduces the fundamental concepts of descriptive analytics, including measurement principles, data types, descriptive statistics, and data visualization. Participants will learn how to summarize and visualize data effectively, providing a strong foundation for more advanced analytics techniques. Participants will work with a provided dataset using Python to apply the concepts and develop their skills.

6: Predictive Analytics Part 1 – Building a Regression Model

Participants will learn how to explore relationships between variables using correlation analysis and build predictive models using linear regression. This module focuses on equipping participants with the skills to build and evaluate models that can predict future outcomes based on historical data. Participants will carry out regression model development using Python and a provided dataset.

7: Predictive Analytics Part 2 – Making Predictions

This module introduces how to make predictions using the regression model developed previously. Techniques to estimate values for input variables account for uncertainty in predictive models. Participants will learn how to use Monte Carlo simulation to make more robust predictions, providing a deeper understanding of potential outcomes. Participants will carry out hands-on predictions, analysis, and visualization using Python.

8: Prescriptive Analytics – Providing Insight to Guide Actions

This module focuses on using clustering techniques to guide prescriptive decision-making. Participants will learn how to generate and analyze data clusters and develop targeted business actions, translating analytical insights into practical, actionable strategies.

1: Reinforcing Project Principles

Learn how to create and manage an implementation plan with best practices in project management.

2: Integrating AI with Project Tools

Learn to work with end users of the applications to identify specific needs and new workflows. Work with tech specialists to implement the technologies to address goals and needs.

3: Managing Project Finances

Discover how to apply financial practices to project management and present project success.

4: Building the Right Space for Collaboration

Practice your best active listening skills and foster a workspace that favours diversity of thought.

5: Making Decisions as a Team

Articulate the vision of the project to motivate and align the team. Re-enforce the roles and tasks of each team member.

6: Setting the Stage for Change

Partner with stakeholder groups from initial planning. Constant re-enforcement of the organizational and project goals.

7: Implementing New Processes

Apply change as both a process and a skill.

8: Reporting on Change and its Effectiveness

Measure change and effectiveness. Report findings and present to senior leaders.

1: Great Communication Strategies

Develop your personal communication style and find the right strategies to help you communicate better.

2: Storytelling Techniques

Use storytelling techniques to make your communication more engaging.

3: Practicing Impactful Communication

Put into practice various skills and techniques that make communicators persuasive and impactful.

4: Communicating Through Problem Solving & Get Positive Attention

Learn strategies to capture and maintain positive attention. Master techniques to grab interest and trust through powerful introductions and emphasizing the value proposition of your message.

5: Resolving Conflicts

Enhance your problem-solving aptitude by embracing conflict as an opportunity. Practice clear communication to reduce confusion and enhance understanding, even in ambiguous contexts.

6: Communicating to Senior Leaders

Understand the differences between horizontal communication and “communicating up.” Learn to accurately analyze the business-political landscape to better achieve your objectives.

7: Managing Optics and Perceptions

Discover ways to build a strategic network of relationships, and how to further opportunities by facilitating conversations between unconnected parties.

8: Integrated Communication Strategies

Create a comprehensive communication plan for a real or hypothetical scenario, incorporating storytelling, conflict resolution, and strategic messaging.

Individuals seeking to build a strong foundation in data-driven and artificial intelligence (AI) business intelligence will benefit from practical learning experiences and a prestigious credential that enhances their employability.​

Team leaders aiming to improve their project management and communication skills can learn to lead data-driven decision-making processes and drive impactful changes within their teams.​