By the end of this course, participants will:

• Understand key AI concepts and how they apply to business development.
• Learn how AI enhances decision-making, marketing, sales, operations, and customer engagement.
• Gain hands-on experience using AI tools for data analysis, automation, and business intelligence.
• Develop a practical AI strategy for business growth.

Topics Covered

• What is AI? Understanding Machine Learning, Deep Learning, and Generative AI
• Evolution of AI and its impact on businesses
• AI-powered business transformation across industries
• Case studies: Google, Amazon, and Tesla

Practical Exercise

• Explore AI-powered business tools (Google AI, IBM Watson, ChatGPT for business)
• Analyze a business case study where AI transformed operations

Key Takeaways

• AI basics and terminology
• Identifying AI opportunities in business

Topics Covered

• AI-driven consumer behavior analysis
• AI in market trend prediction
• Sentiment analysis and customer segmentation
• Tools: Google Trends, IBM Watson, ChatGPT for market research

Practical Exercise

• Conduct AI-powered sentiment analysis on customer reviews using free AI tools
• Use AI-based market research tools to identify industry trends

Key Takeaways

• Leveraging AI for data-driven customer insights
• Understanding AI-powered market research techniques

Topics Covered

• AI-powered content marketing & SEO (ChatGPT, Jasper, Copy.ai)
• AI-driven lead generation & CRM automation (HubSpot, Salesforce AI)
• Personalized customer experiences with AI (chatbots, recommendation engines)

Practical Exercise

• Implement an AI chatbot for customer service
• Use an AI-driven tool to generate a marketing campaign

Key Takeaways

• How AI automates and enhances sales and marketing
• Hands-on experience with AI marketing tools

Topics Covered

• AI-powered data analytics and visualization (Power BI, Tableau)
• AI in financial forecasting and risk management
• AI bias, fairness, and ethical considerations

Practical Exercise

• Analyze business data using AI-driven analytics tools
• Evaluate ethical considerations in AI business applications

Key Takeaways

• AI for data-driven business strategy
• Responsible AI implementation

Topics Covered

• AI-driven process automation (RPA, workflow automation)
• AI in supply chain & logistics (predictive maintenance, smart warehouses)
• AI-powered inventory & demand forecasting

Practical Exercise

• Implement an AI-based automation workflow in business operations
• Use an AI tool to optimize a supply chain process

Key Takeaways

• How AI enhances efficiency and reduces costs
• Hands-on implementation of AI process automation

Topics Covered

• How to develop an AI strategy for your business
• Choosing the right AI tools and platforms
• Overcoming AI adoption challenges
• Future trends: AI, blockchain, and IoT for business

Practical Exercise

• Develop a business AI strategy proposal
• Group presentation: AI-powered business case study

Key Takeaways

• Practical steps for AI adoption
• Understanding the future of AI in business

• Students create and present an AI implementation plan for a business.
• The project will integrate knowledge from all modules, demonstrating AI's impact on decision-making, automation, and growth.

• AI Tools: ChatGPT, Google AI, IBM Watson, Power BI, Tableau, HubSpot AI, Salesforce AI, Jasper
• Books:
  • AI Superpowers by Kai-Fu Lee
  • The AI Advantage by Thomas H. Davenport
  • Prediction Machines: The Simple Economics of Artificial Intelligence by Ajay Agrawal
• Online Platforms for AI Learning: Google AI Learning Lab, SIMI Swiss, Swiss Diploma, Swiss Polytechnic, MIT AI Business Strategy