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Quick Facts

Medium Of InstructionsMode Of LearningMode Of Delivery
EnglishSelf Study, Virtual ClassroomVideo and Text Based

Courses and Certificate Fees

Certificate AvailabilityCertificate Providing Authority
yesMIT Cambridge

The Syllabus

  • Identify the design stages and their purposes 
  • Find the right AI technology to improve a business purposes 
  • Appraise the technical as well as business requirements for a product 
  • Identify the long-term advantages and limitations of a product
  • Analyze the three types of AI cancers and how they affect an AI process or product

  • Differentiate between various machine learning algorithms and their uses 
  • Maximize the advantages of training, validation, and testing sets 
  • Run and analyze the results from Bayesian machine learning algorithms 
  • Learn to compare machine learning algorithms and identify the ones suitable for application

  • Explore the applications that use deep learning algorithms
  • Run implementations on convolutional, deep, and recurrent neural network algorithms 
  • Use neural network simulations to draw conclusions 
  • Run an implementation of a single- and a multilayer perceptron in Python 
  • Explore the structure and components of an artificial neuron

  • Assess the accuracy of an AI model 
  • Understand the approval processes of the Committee on the Use of Humans as Experimental Subjects (COUHES) and various institutional review boards (IRBs) for AI models 
  • Formulate crowdsourcing data strategies 
  • Review the superhuman intelligence used in an AI product or service 
  • Explore the advantages and disadvantages of using an AI technology

  • Understand the ins and outs of the framework 
  • Identify the various uses, advantages, and disadvantages of ingestible robots 
  • Develop an idea for an ingestible robot to solve a healthcare problem 
  • Study the crowdsourcing data strategies that exceed the limitations of AI

  • Identify the mechanisms involved in developing prosthetics for the human body and the communication gaps that occur in a given scenario
  • Study the developments in proprioception research and how it has evolved over the course of history 
  • Understand how communication plays a key role in developing prosthetics 
  • Learn the advantages of using exoskeletons

  • Recognize how data needs to be managed and the importance of flexibility and adaptability while creating an AI product
  • Identify the problem of model drift and how to overcome its challenges 
  • Study the advantages of silo work 
  • Hypothesize an AI product or service to solve a healthcare problem

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