How To Build AI / Machine Learning Startups | Sramana Mitra

How To Build AI / Machine Learning Startups | Sramana Mitra, available at $84.99, has an average rating of 4.58, with 51 lectures, based on 339 reviews, and has 3578 subscribers.

You will learn about How to identify AI startup opportunities through in-depth interviews with successful founders in the AI / Machine Learning space. What the trends, new innovations and best business models are for ArtificiaI Intelligence / Machine Learning startups. When to bring on a team while building an AI startup. When to start raising funds for a Machine Learning startup. How to scale a Machine Learning / AI startup. What the exit options are for an Artificial Intelligence / Machine Learning startup. This course is ideal for individuals who are Ambitious entrepreneurs who want to pursue innovation by building their own startup. or Engineers who want to turn their AI knowledge into multi-million dollar revenue businesses by becoming startup founders rather than remaining employees. or Aspiring founders who want to increase their chances of getting accepted into a top startup accelerator such as Y Combinator, Techstars, or 500 Startups. or Any entrepreneur who wants to learn from successful entrepreneurs who have done it before, and from the investors who have supported them. or Professors teaching technology entrepreneurship courses anywhere in the world. It is particularly useful for Ambitious entrepreneurs who want to pursue innovation by building their own startup. or Engineers who want to turn their AI knowledge into multi-million dollar revenue businesses by becoming startup founders rather than remaining employees. or Aspiring founders who want to increase their chances of getting accepted into a top startup accelerator such as Y Combinator, Techstars, or 500 Startups. or Any entrepreneur who wants to learn from successful entrepreneurs who have done it before, and from the investors who have supported them. or Professors teaching technology entrepreneurship courses anywhere in the world.

Enroll now: How To Build AI / Machine Learning Startups | Sramana Mitra

Summary

Title: How To Build AI / Machine Learning Startups | Sramana Mitra

Price: $84.99

Average Rating: 4.58

Number of Lectures: 51

Number of Published Lectures: 51

Number of Curriculum Items: 51

Number of Published Curriculum Objects: 51

Original Price: $84.99

Quality Status: approved

Status: Live

What You Will Learn

• How to identify AI startup opportunities through in-depth interviews with successful founders in the AI / Machine Learning space.
• What the trends, new innovations and best business models are for ArtificiaI Intelligence / Machine Learning startups.
• When to bring on a team while building an AI startup.
• When to start raising funds for a Machine Learning startup.
• How to scale a Machine Learning / AI startup.
• What the exit options are for an Artificial Intelligence / Machine Learning startup.

Who Should Attend

• Ambitious entrepreneurs who want to pursue innovation by building their own startup.
• Engineers who want to turn their AI knowledge into multi-million dollar revenue businesses by becoming startup founders rather than remaining employees.
• Aspiring founders who want to increase their chances of getting accepted into a top startup accelerator such as Y Combinator, Techstars, or 500 Startups.
• Any entrepreneur who wants to learn from successful entrepreneurs who have done it before, and from the investors who have supported them.
• Professors teaching technology entrepreneurship courses anywhere in the world.

Target Audiences

• Ambitious entrepreneurs who want to pursue innovation by building their own startup.
• Engineers who want to turn their AI knowledge into multi-million dollar revenue businesses by becoming startup founders rather than remaining employees.
• Aspiring founders who want to increase their chances of getting accepted into a top startup accelerator such as Y Combinator, Techstars, or 500 Startups.
• Any entrepreneur who wants to learn from successful entrepreneurs who have done it before, and from the investors who have supported them.
• Professors teaching technology entrepreneurship courses anywhere in the world.