Introduction:
Society and organizations are generating enormous amounts of data. Artificial intelligence (AI) helps harness this data to improve well-being, increase revenue, and reduce costs. Through the application of AI, internal and external, structured and unstructured data unveil new capabilities, enhance predictions, and streamline decision-making processes, augmenting human capabilities and improving company performance.
This artificial intelligence (AI) for business professionals course is brimming with new terminologies and technologies in the field, and it is not just about handling vast datasets or underlying mechanisms. A successful deployment of AI in business requires scaling from isolated proofs of concept to a strategic, organization-wide approach. It demands a vision to pinpoint the best opportunities for incorporating AI, a structural framework to identify necessary improvements and an implementation strategy that specifies actionable steps.
Participants in this artificial intelligence (AI) for business professionals course will gain the AI literacy needed to lead their organizations' AI endeavors, understand AI concepts, use their analytical insights to create an informed AI strategy and develop an organization ready to embrace and benefit from AI.
Targeted Groups:
- Individuals who recognize continuous improvement and innovation are intrinsic to business success and are eager to harness AI's benefits.
- Managers aim to understand AI's potential for their operations and drive digital transformation without necessarily delving into technical methodologies.
Course Objectives:
At the end of this artificial intelligence (AI) for business professionals course, participants will be able to:
- Explain the concept of AI and its myriad applications.
- Apply different AI techniques across the business value chain.
- Demonstrate an understanding of the underlying technologies and algorithms powering AI.
- Apply best practices for executing AI projects and overseeing their activities.
- Assess the necessary skills and competencies for AI adoption.
- Engage with business and data specialists on AI-related topics at a qualified level.
- Formulate and implement an AI development strategy to cultivate an AI-ready organization.
Targeted Competencies:
Upon the end of this artificial intelligence (AI) for business professionals training, participants competencies will be able to:
- Explore proficient application of AI best practices.
- Understand effective change management within the AI context.
- Translate business needs into AI business intelligence opportunities.
- Manage AI projects adeptly.
Why is Artificial Intelligence (AI) Becoming Important?
Organizations can optimize their operations by understanding AI systems, techniques, tools, and solutions, tap into new marketing strategies, and instill robust business processes powered by intelligent algorithms. A solid introduction to artificial intelligence is imperative for professionals who wish to keep up with the rapid pace of digital transformation.
Incorporating artificial intelligence (AI) in business has become essential to fostering innovation, ensuring continuous improvement, and driving digital transformations forward. This course will equip business professionals with the necessary skills and knowledge to leverage AI to enhance business intelligence, processes, and solutions.
Course Content:
Unit 1: Introduction to Artificial Intelligence (AI), Machine Learning (ML), and Data Science
- Know the historical context of AI and combinatorial technologies.
- Overview of AI concepts, including narrow and general AI.
- Explore the various forms of AI.
- Understand AI's capabilities in sensing, reasoning, and acting.
- Grasp the concept of Machine Learning within the AI paradigm.
Unit 2: Advanced Analytics vs Artificial Intelligence:
- Reflect on the evolution of data analytics.
- Learn about the four types of data analytics.
- Analytics value chain.
Unit 3: Algorithms but without technical jargon:
- Understand the breakdown of supervised, unsupervised, and reinforcement learning.
Unit 4: Data as Fuel for AI:
- Differentiate structured from unstructured data.
- Learn about the five vital characteristics of data (the 5 Vs).
- Understand the importance of data governance and its implementation.
Unit 5: The Data Engineering Platform:
- A cursory overview is sufficient to understand data architecture.
- Know the architecture of extensive data systems.
- Three categories of data utilization.
Unit 6: AI Opportunity Matrix:
- Identify successful use cases within Porter's value chain.
- Explore primary activities.
- Support activities.
Unit 7: Successful Use Cases by Technology:
- Overview of Natural Language Processing (NLP).
- Introduce image recognition technologies.
- Know about Machine learning and its applicability.
Unit 8: Ideation of AI Projects:
- Know the AI funnel process for generating ideas.
- Various approaches for idea generation.
- Strategies for prioritizing AI projects.
- Utilize the AI project canvas for project conceptualization.
Unit 9: How to Transform into an AI-ready Organization:
- Implement the AI strategy cycle.
- Charts are laying out the dimensions of an AI framework.
- Explain a pragmatic approach to gauging an organization's AI maturity.
- Understand effective organizational structures for AI adoption.
- Explore the role and benefits of establishing an AI Center of Excellence.
- Learn about essential skills and competencies for AI readiness.
Unit 10: AI and Ethics:
- Understand the risks associated with AI.
- Establish ethical guidelines for AI usage.
- Ensure the realization of trustworthy AI systems.
