AI Lead Auditor

image

Access comprehensive training programs led by experienced AI experts and earn certification as an AI Maturity Model Trainer or Lead Auditor.

Course Objective:

  • Benefit from the expertise of our seasoned AI professionals with a track record of delivering tangible results.
  • Receive ongoing support and guidance to ensure the success of your AI-driven initiatives
  • The course is divided into 8 Modules.

Target Audience:

  • Seasoned Experts
  • Tangible Outcomes
  • Continuous Guidance
  • Initiative Success

image

Course Modules

Explore our detailed course modules to gain insights into the topics covered, learning objectives, and the structured curriculum of our cutting-edge AI training programs.

Module 1 gives an overview of Cognitive Science and its importance to Brain Computer Interfaces. It also discusses the History and the invention of the first BCI.

  1. BCI fundamentals
  2. Cognitive Science and concepts

Module 2 shares a case study about wireless telemetry in monitoring the vitals of the post-acute patients and how to develop a Provider Command Centre where Doctors can monitor the vitals of their patients from remote using a wearable device to be placed in the body of the patients. This is the introduction to the wearable device for monitoring the brain signals using Electroencephalograph.

It also talks about development of Robotic based Rehabilitation for children affected by AD/HD Syndrome (Attention Deficiency/ Hyperactive Disorder Syndrome) and how it helps in improving their Cognitive skills. 

  1. Developing the Future Provider Command and Control Centre
  2. Development of Robotic Rehabilitation

Module 3 explains the Architecture of the Brain Computer Interface and the details of how the brain signals from Electroencephalograph are acquired through SSVEP (Steady State Visually Evoked Potentials), how the relevant features are extracted from SSVEP and how the features are translated to a relevant output that are understandable and communicated as actionable inputs to various external devices.

  1. Signal Acquisition
  2. Features Extraction
  3. Features Translation

Module 4 talks about how the brain signals are measured using the electrodes and the classifications of various frequencies of the sub bands of the EEG rhythms. IT talks about the relation between the brain activity of interest and the neuroimaging method to employ for its detection. 

  1. Measuring the Electrical Brain Activity
  2. Measured Brain Signals

Module 5 explains how the acquisition part of the BCI is treated by considering four common trends in the market which are the electrode types, portability, and non-invasiveness and cost effectiveness.

  1. Acquisition System
  2. Electrodes

Module 6 discusses various Channel selection strategies for getting the best accuracy levels for guaranteeing the acceptance and performance. Also various privacy issues to be considered from moving away from the lab to daily life instruments.

  1. Channel Minimization Strategies
  2. Characterization of Low cost EEGs
  3. Cybersecurity and Privacy Issues

Module 7 focusses on the fundamentals of reactive BCI. In particular, BCI based on SSVEP are analysed. The main issues concern the detection of the SSVEPs and the requirements for implementing a daily-life BCI (i.e., wearability, user friendliness, low cost).

  1. Detection of SSVEP
  2. Statement of the metrological problem.

Module 8 deals with the realization of a SSVEP -BCI system. In particular, design, prototype and performance of the system are analysed.

  1. Prototype Design
  2. Performance

Assessment & Certification

Participants will be assessed through online quizzes, assignments, and a final project. A QCI-approved certificate of completion will be awarded to participants who successfully fulfill course requirements.