How To Build AI / Machine Learning Startups | Sramana Mitra

סקירה כללית

The 1Mby1M Methodology is based on case studies. In this course, Sramana Mitra shares the tribal knowledge of tech entrepreneurs by giving students the rare seat at the table with the entrepreneurs, investors and thought leaders who provide the most instructive perspectives on how to build a thriving business.

Through these conversations, students gain access to case studies exploring the alleys of entrepreneurship. Sramana’s synthesis of key learnings and incisive analysis add great depth to each discussion.

סילבוס

• Introduction to AI/ML Startups
Overview of 1Mby1M Methodology
Importance of case studies in entrepreneurship education
• Case Studies in AI/ML
Key case studies of successful AI/ML startups
Learnings from entrepreneurs and their journeys
• Building an AI/ML Startup
Identifying market opportunities
Defining your value proposition
• Funding and Investment
Understanding the investment landscape
Pitching to investors in AI/ML
Strategic partnerships and alliances
• Technology Development
Selecting the right AI/ML technologies
Building and scaling tech teams
• Business Model Development
Exploring scalable business models
Revenue generation strategies
• Go-to-Market Strategy
B2B vs B2C approaches
Customer acquisition channels
• Team and Culture
Building a cohesive and innovative team
Fostering an entrepreneurial culture
• Legal and Ethical Considerations
Navigating legal aspects in AI/ML
Addressing ethical concerns in AI/ML development
• Global Perspectives on AI/ML Startups
Case studies from different regions
Adapting strategies to local markets
• Conclusion and Synthesis
Lessons learned from case studies
Final reflections on building AI/ML startups
• Additional Resources
Recommended readings and podcasts
Networking opportunities and forums

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נלמד על ידי

Sramana Mitra

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נושאים

Business