Working in an interactive learning environment, led by our engaging AI expert, you will: 

• Learn which data is most useful to collect now and why it's important to start collecting that data as soon as possible 
• Understand the intersection between big data, data science and AI (Machine Learning / Deep Learning) and how they can help you reach your business goals and gain a competitive advantage. 
• Understand the factors that go into choosing a data science and AI driven systems including whether to go with a cloud-based solution 
• Explore common tools and technologies to aid in making informed decisions 
• Gain the skills required to build your data science, AI and machine learning teams 

This introductory-level course is geared for a mix of business stakeholders who are either directly involved in or impacted by AI-driven initiatives within their organization. This includes C-suite executives, business unit leaders, product managers, and innovation strategists eager to gain a working knowledge of AI's capabilities and applications in a business context. Professionals in roles such as data analysts, IT managers, and project managers who collaborate with data science teams will find this course instrumental in bridging gaps and facilitating effective communication across departments. 

Please note that this list of topics is based on our standard course offering, evolved from typical industry uses and trends. We'll work with you to tune this course and level of coverage to target the skills you need most. Topics, agenda and labs are subject to change, and may adjust during live delivery based on audience skill level, interests and participation. 

Introduction to AI in Business 

• Explore the relevance and potential impact of AI technologies in modern businesses. 
• What is AI and Why Does It Matter 
• The ROI of AI Adoption 
• Case Studies: AI Transformations 
• AI Ethics and Regulation 
• AI's Role in Different Business Units 
• Quick overview of businesses successfully adopting AI  

Data: The Bedrock of AI  

• Identify the types of data most pertinent to AI applications in business. 
• Types of Data: Structured vs Unstructured 
• Importance of Data Collection 
• Data Storage Solutions 
• Data Security and Compliance 
• Data Integration Strategies 
• Evaluating databases suited for AI applications  

Big Data, Data Science, and AI – The Power Trio  

• Explore how Big Data, Data Science, and AI synergize for business advantage. 
• The Big Data Ecosystem 
• Data Science Methodologies 
• Machine Learning vs Deep Learning 
• Business Cases for Data Science and AI 
• Tools for Analytics and Data Processing 

Cloud-Based vs On-Premise Solutions 

• Make informed decisions on cloud-based vs. on-premise AI solutions. 
• Factors for Choosing a Platform 
• Cloud-Based Pros and Cons 
• On-Premise Pros and Cons 
• Cost Implications 
• Security Considerations 

Selecting Tools and Technologies  

• Explore various tools and technologies to facilitate AI adoption. 
• Popular AI Frameworks 
• Visualization Tools 
• Data Cleaning and Preprocessing Tools 
• Analytical Platforms 
• APIs and Libraries 
• Quick tour through a suite of cutting-edge AI tools  

Building Your Data Science and AI Teams  

• Explore the key skills and roles to consider when forming a data science/AI team. 
• Core Team Roles 
• Required Skill Sets 
• Training vs Hiring 
• Collaboration Tools 
• Team KPIs and Performance Metrics 
• Leveraging tech for remote collaboration  

Generative AI: A New Paradigm for Business  

• Understand how Generative AI can redefine content creation, design, and decision-making in business. 
• What is Generative AI? 
• Applications in Marketing and Design 
• Generative AI in Product Development 
• Ethical and Legal Concerns 
• Generative AI in Business Strategy 
• Auto-Generated Content: See how Generative AI can automatically produce marketing copy and design elements  

Emerging Trends in Data & AI for Business  

• Stay ahead of the curve by understanding upcoming trends that will shape the future of AI in business. 
• Federated Learning and Edge AI 
• AI for Sustainability and Social Good 
• AI in Cybersecurity 
• Reinforcement Learning in Business 
• Explainable AI (XAI) 
• Explore the impact of new trends on different business sectors  

Next Steps and Action Plan  

• Develop a roadmap to start or advance AI implementation in your organization. 
• Setting Short-term and Long-term Goals 
• Budget and Resource Allocation 
• Scaling AI Projects 
• Ongoing Training and Skills Update