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Certified AI Developer (CAID) Certification Course by Tonex

Certified AI-Driven Cyber Threat Intelligence Analyst (CAICTIA) Certification Course by Tonex

The Certified AI Developer (CAID) certification by Tonex equips participants with in-depth knowledge of machine learning algorithms, deep learning, natural language processing (NLP), generative AI, and retrieval-augmented generation (RAG).

The program emphasizes AI model deployment, ethical AI considerations, risk management, and lifecycle governance. Participants will gain hands-on experience in building, deploying, and managing AI solutions while adhering to ethical principles. This certification prepares professionals for real-world AI challenges, enhancing their ability to drive innovation and maintain responsible AI practices.

Learning Objectives:

  • Understand core machine learning and deep learning concepts.
  • Master NLP, generative AI, and retrieval-augmented generation techniques.
  • Learn AI model deployment and lifecycle management.
  • Apply ethical principles and manage AI risks.
  • Design AI solutions aligned with governance standards.
  • Prepare for CAID certification exam with confidence.

Audience:

  • AI developers and engineers.
  • Data scientists and machine learning practitioners.
  • Software architects and developers.
  • Technology managers and strategists.
  • IT professionals exploring AI integration.
  • Enthusiasts aiming for AI expertise.

Program Modules:

Module 1: Machine Learning Fundamentals

  • Supervised learning basics.
  • Unsupervised learning techniques.
  • Reinforcement learning overview.
  • Feature engineering strategies.
  • Model evaluation and metrics.
  • Applications in real-world scenarios.

Module 2: Deep Learning Essentials

  • Neural network architectures.
  • Convolutional neural networks (CNNs).
  • Recurrent neural networks (RNNs).
  • Transfer learning approaches.
  • Hyperparameter tuning techniques.
  • Deployment in production environments.

Module 3: Natural Language Processing and Generative AI

  • NLP foundational concepts.
  • Transformers and BERT/GPT models.
  • Text summarization techniques.
  • Sentiment analysis and classification.
  • Generative AI applications.
  • Retrieval-augmented generation (RAG).

Module 4: AI Model Deployment and Management

  • Deployment strategies and pipelines.
  • Monitoring AI model performance.
  • Scaling AI models.
  • Model retraining and updates.
  • AI tools and platforms overview.
  • Continuous integration in AI systems.

Module 5: Ethical AI and Risk Management

  • Principles of ethical AI.
  • Bias detection and mitigation.
  • AI risk management frameworks.
  • Privacy and data protection in AI.
  • Legal and compliance aspects.
  • Trust and transparency in AI systems.

Module 6: AI Governance and Lifecycle

  • Governance frameworks for AI.
  • AI lifecycle stages overview.
  • Decision-making in AI projects.
  • Collaboration across teams.
  • Standards and best practices.
  • Future trends in AI governance.

Exam Domains:

  • Machine learning concepts.
  • Deep learning architectures.
  • NLP and generative AI techniques.
  • AI deployment and scaling.
  • Ethics and risk management in AI.
  • AI governance and lifecycle management.

Course Delivery:

The course is delivered through a combination of lectures, interactive discussions, hands-on workshops, and project-based learning, facilitated by experts in the field of AI Development. Participants will have access to online resources, including readings, case studies, and tools for practical exercises.

Assessment and Certification:

Participants will be assessed through quizzes, assignments, and a capstone project. Upon successful completion of the course, participants will receive a certificate in AI Development.

Question Types:

  1. Multiple Choice Questions (MCQs)
  2. True/False Statements
  3. Scenario-based Questions
  4. Fill in the Blank Questions
  5. Matching Questions (Matching concepts or terms with definitions)
  6. Short Answer Questions

Passing Criteria:

To pass the Certified AI Developer (CAID) Training exam, candidates must achieve a score of 70% or higher.

Enhance your expertise as a Certified AI Developer (CAID) with Tonex. Gain cutting-edge skills, stay ahead in AI innovation, and demonstrate your commitment to ethical AI practices. Enroll today and take the next step in your AI career!

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