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Last Date
10 Nov 2025
Course Duration
10 Days / 80 Hours
Language
English
Course Details

The AWS Certified AI Practitioner program is a 10-days / 80-hours training designed in English to help Costa Rica’s aspiring professionals and graduates break into AI, ML, and Generative AI roles. This online mentor-led course blends expert instruction, hands-on training, and real-world projects, ensuring participants are fully prepared for the AWS AIF–C01 certification exam.

  • Mode: Daily 4-hour Online Mentor-led sessions + Practice Labs
  • Certification Prep: AWS Certified AI Practitioner (AIF–C01)
  • Deliverables: Certificate of Completion, Hands-on Projects, Learner Report, Self-paced video library
  • Moneyback: Get a 50% Moneyback on 5 Successful Referrals

Throughout this course, participants will:

  • Learn core concepts of Artificial Intelligence (AI) and Machine Learning (ML).
  • Understand Generative AI and foundation models, including their applications and limitations.
  • Explore AWS AI services and tools to design and deploy AI solutions efficiently.
  • Gain practical skills in prompt engineering, embedding techniques, and retrieval-augmented generation (RAG).
  • Learn to apply Responsible AI practices, including fairness, explainability, security, and governance.
  • Prepare to confidently attempt the AIF–C01 certification exam through hands-on exercises, case studies, and mentor guidance.

Get in touch with us for financial assistance and more details.

By the end of the program, participants will be able to identify the right AI/ML approach for business problems, use AWS AI services effectively, and ensure responsible AI deployment, making them well-prepared for the AWS Certified AI Practitioner certification and real-world AI applications.

*Batches will begin once the minimum registrations are met.

What You Will Learn by the End of This Course:
  • Master AI, Machine Learning, and Generative AI fundamentals
  • Build industry-ready AI projects to strengthen your portfolio
  • Gain hands-on experience with AWS SageMaker, Bedrock, Rekognition, Comprehend
  • Be fully prepared to clear the AWS AIF–C01 Certification Exam
  • Understand Responsible AI & Governance in practice
Course Features
  • Online Mentor-led training from certified AWS AI experts
  • Live Q&A support during sessionss
  • Hands-on projects & labs with real-world datasets
  • Interactive quizzes & demos for active learning
  • Flexible access: live classes + self-paced resources
  • Global certification recognized by employers worldwide
AWS Certified AI Practitioner (AIF-C01) – Syllabus

  • 1.1 Introduction to AI, ML, and Deep Learning
  • 1.2 Types of Machine Learning (Supervised, Unsupervised, Reinforcement Learning)
  • 1.3 ML Lifecycle (Data, Training, Evaluation, Inference)
  • 1.4 Model Evaluation Metrics (Accuracy, Precision, Recall, F1, Confusion Matrix)
  • 1.5 Data Preparation and Feature Engineering (Basics)
  • 1.6 Transfer Learning and Fine-Tuning
  • 1.7 Common AI/ML Use Cases

  • 2.1 What is Generative AI – Core Concepts
  • 2.2 Types of Generative Models (LLMs, Diffusion, GANs, etc.)
  • 2.3 Prompt Engineering Techniques (Zero-shot, Few-shot, Chain-of-Thought)
  • 2.4 Retrieval-Augmented Generation (RAG)
  • 2.5 Applications of Generative AI (Text, Image, Audio, Video)
  • 2.6 AWS Services for Generative AI (Amazon Bedrock, SageMaker JumpStart, etc.)
  • 2.7 Model Output Evaluation (BLEU, ROUGE, BERTScore, etc.)

  • 3.1 Understanding Foundation Models
  • 3.2 Adapting Foundation Models (Fine-tuning, Customization)
  • 3.3 Prompt Chaining and Decomposition
  • 3.4 Hybrid AI Solutions (RAG + Foundation Models)
  • 3.5 Embeddings and Vector Databases
  • 3.6 Semantic Search & Knowledge Retrieval
  • 3.7 Practical Use Cases & Architectures

  • 4.1 Principles of Responsible AI
  • 4.2 Bias and Fairness in AI Models
  • 4.3 Explainability and Transparency
  • 4.4 Data Privacy and Protection
  • 4.5 Safe AI Practices and Fallback Strategies
  • 4.6 Ethical AI Use Cases and Best Practices

  • 5.1 Security Fundamentals in AI Systems
  • 5.2 IAM, Access Control, and Role Management
  • 5.3 Data Encryption & Key Management (KMS)
  • 5.4 Secure Model Hosting & Network Controls
  • 5.5 Logging, Monitoring, and Auditing AI Applications
  • 5.6 Compliance Considerations for AI (Regulatory Standards)
  • 5.7 Governance Frameworks for AI

  • 6.1 AWS Exam Guide Overview
  • 6.2 Question Types (Multiple Choice, Multiple Response, Matching, Ordering, Case Study)
  • 6.3 Exam Strategy & Time Management
  • 6.4 Practice Questions & Mock Exams
  • 6.5 Case Study Scenarios (Industry Use Cases)
  • 6.6 Final Review & Readiness Checklist

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Frequently Ask Questions

The AWS Certified AI Practitioner (AIF-C01) course is a 10-days, online mentor-led online program designed to teach the fundamentals of Artificial Intelligence (AI), Machine Learning (ML), and Generative AI. It also prepares participants for the AWS Certified AI Practitioner exam.

There are no strict prerequisites. However, basic knowledge of cloud computing concepts and familiarity with general programming or data analytics will be helpful.

Yes. The course includes online mentor-led sessions with hands-on exercises and real-world case studies to apply AI and ML concepts using AWS services.

The course is delivered via online mentor-led sessions, with access to guided practice, labs, and self-paced video resources.

Participants will explore key AWS AI and ML services such as Amazon SageMaker, Amazon Bedrock, Amazon Comprehend, and other tools that support AI solution deployment and Generative AI applications.

This course is ideal for IT professionals, software developers, data analysts, students, and anyone interested in gaining foundational knowledge in AI and ML and pursuing AWS certification in AI.

You can reach out to us on info@datafynovac.com and we will guide you through the process

Absolutely. The course is specifically designed to prepare you for the Certified AI Practitioner (AIF-C01) exam, covering all exam domains and providing practical examples to boost confidence.

The course spans 10 days, with online sessions led by expert mentors. Each session includes lectures, hands-on labs, and interactive discussions.

Yes. Participants will receive a course completion certificate.