Artificial Intelligence ML Startup Casestudy w/Sramana Mitra

Artificial Intelligence (AI) and Machine Learning (ML) Startup Lessons from the Trenches

Free tutorial

Created by Sramana Mitra

English

Table of Contents

What you’ll learn

How an impactful Artificial Intelligence startup has been built.
How a significant AI startup can be built.
How to build an ML startup.
How a notable Machine Learning startup has been built.

Requirements

None.

Description

The 1Mby1M Methodology is based on case studies. In each 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.

Udemy has over six million students who are learning Machine Learning on the platform. Many of these students are aspiring entrepreneurs.

Here is a list of Udemy entrepreneurship courses based on the 1Mby1M methodology that would help them put one foot before the other to get a startup strategy figured out.

I believe, strongly, that entrepreneurship and entrepreneurial capitalism can be democratized, and wealth can be created in the middle of the pyramid using capitalistic principles. In the next 2-3 decades, the potential for distributed capitalism is very high and the outcome should be extremely positive around the world. That is the mission upon which my current work with One Million by One Million is based. Artificial Intelligence, Big Data and Machine Learning are going to be at the forefront of this immense burst of energy.

Let’s talk about the field of medicine. If you think about what a doctor needs to do to diagnose an illness, she needs to consider all the symptoms, take into account all the test results, consider all the treatment options, factor in all the side-effects of various medications and their interplay with other medications the patient is already taking.

This is, effectively, a multivariate optimization problem that a doctor has to do in her head. And, she needs to keep up with all the new research and advances in medical science, and factor those in as well. The field of medicine is full of incorrect diagnosis and mistreatment of illnesses. Now, if you replace this whole process with software, which IBM is trying to do with their Watson supercomputer, medical diagnosis becomes a truly scientific, deterministic process.

I can tell you, if I have the option of being diagnosed by software versus a human doctor, I would always prefer software. It would be far more accurate.

Let’s get started!

Who this course is for:

Tech entrepreneurs building or aspiring to build Artificial Intelligence ML starutps.

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Course content

3 sections • 8 lectures • 1h 43m total lengthCollapse all sections