This three-day intensive programme provides delegates with the knowledge, skills, and abilities required to:

• Apply foundational ethical principles
• Follow industry-standard frameworks
• Identify and mitigate risks
• Navigate ethical organizational governance
• Devise and maintain ethical, trusted, and inclusive data-driven technologies

Key Topics Covered:

The Certified Ethical Emerging Technologist™ (CEET) course and exam cover the following five core areas:

• Fundamental Concepts for Data-Driven Technology Ethics
• Ethical Frameworks
• Risk Identification and Mitigation
• Communication
• Organizational Policy and Governance

Certification & Exam:

This course fully equips delegates to successfully sit for the CertNexus Certified Ethical Emerging Technologist (CEET) exam and earn the accompanying certification.

Cost: 2999 USD

Duration: 3 Days

This five-day intensive programme equips participants with the knowledge, skills, and abilities required to achieve the globally recognized Certified Artificial Intelligence Practitioner certification from CertNexus. The course covers four core domains essential for mastering AI and machine learning applications in business.

Key Topics Covered:

The Certified Artificial Intelligence Practitioner™ (CAIP) course and exam cover the following four key areas:

1. Understanding the Artificial Intelligence Problem

• Describe how artificial intelligence and machine learning are used to solve business (including commercial, government, public interest, and research) problems
• Analyze the use cases of ML algorithms to rank them by their success probability
• Research Learning Systems [Identify business case for image recognition; NLP; Speech recognition; Predictive & recommendation systems; Discovery & diagnostic systems; Robotics and autonomous systems]
• Analyze machine learning system use cases
• Communicate with stakeholders
• Identify potential ethical concerns

2. Engineering Features for Machine Learning

• Recognize relative impact of data quality and size to algorithms
• Explain data collection/transformation process in ML workflow (transformations include standardization; normalization; log, square-root, and logit transformations)
• Work with textual, numerical, audio, or video data formats
• Transform numerical and categorical data
• Address business risks, ethical concerns, and related concepts in data exploration/ feature engineering

3. Training and Tuning ML Systems and Models

• Design machine and deep learning models [Differentiate types of ML algorithms; differentiate types of DL algorithms; design for pattern recognition in predictive models]
• Optimize the algorithm (, structure, run time, tuning hyperparameters)
• Train, validate, and test data subsets
• Evaluate the model
• Address business risks, ethical concerns, and related concepts in training and tuning

4. Operationalizing ML Models

• Deploy a model
• Secure a pipeline (includes maintenance)
• Maintain the model postproduction
• Address business risks, ethical concerns, and related concepts in operationalizing the model

Certification & Exam:

This course fully prepares participants to successfully sit for the CertNexus Certified Artificial Intelligence Practitioner exam and earn the accompanying certification.

Classes are delivered as live online, instructor-led tuition.

Cost: 1999 USD

Duration: 5 Days