Course Modules
Module 1: Foundation Model Selection and Deployment Strategies
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FM Assessment: Performance benchmarks, capability analysis, and business use case alignment.
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Advanced Deployment: Implementing SageMaker AI for fine-tuned models and parameter-efficient techniques (LoRA and Adapters).
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System Resilience: Implementing circuit breaker patterns and Cross-Region Inference for high availability.
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Hands-on Lab: Deploying a specialized model via SageMaker Model Registry and configuring multi-region failover.
Module 2: Multimodal Ingestion and Data Validation
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Complex Data Pipelines: Handling text, image, audio, and tabular data for multimodal FMs.
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Quality Gateways: Data validation using AWS Glue Data Quality and custom Lambda functions.
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Data Formatting: Structuring requests for Amazon Bedrock APIs and SageMaker endpoints.
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Hands-on Lab: Building a pipeline that processes audio (Transcribe) and images for multimodal inference.
Module 3: Advanced Vector Store Architectures
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Index Design: Sharding strategies and vector index types (HNSW, IVF) in Amazon OpenSearch.
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Metadata Frameworks: Designing systems for high-precision semantic retrieval and domain classification.
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Data Maintenance: Implementing incremental updates and real-time synchronization for vector stores.
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Hands-on Lab: Configuring an OpenSearch Serverless cluster with the Neural plugin and metadata enrichment in DynamoDB.
Module 4: Advanced Retrieval and FM Augmentation
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Sophisticated Chunking: Implementing hierarchical, structure-based, and custom Lambda-based segmentation.
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Retrieval Optimization: Using Reranker models, Query Expansion, and Query Decomposition.
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Hybrid Search: Combining keyword (Lexical) and vector (Semantic) search for maximum accuracy.
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Hands-on Lab: Implementing a RAG system that uses a Reranker to significantly reduce hallucinations.
Module 5: Prompt Engineering, Flows, and Governance
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Advanced Prompting: Chain-of-Thought, ReAct patterns, and output format specifications.
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Amazon Bedrock Prompt Management: Parameterized templates, versioning, and approval workflows.
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Complex Orchestration: Building sequential chains and conditional branching with Amazon Bedrock Prompt Flows.
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Hands-on Lab: Creating a versioned prompt library with automated A/B testing for performance evaluation.
Module 6: Agentic AI and Model Context Protocol - MCP
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Agent Orchestration: Building autonomous systems with AWS Agent Squad and Strands Agents.
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Tool Integration: Implementing stateless and stateful MCP (Model Context Protocol) servers on Lambda and ECS.
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Memory Management: Handling state and long-term conversation history in agentic workflows.
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Hands-on Lab: Developing an AI Agent that uses an MCP server to interact with legacy enterprise systems.
Module 7: Enterprise Integration and Developer Productivity
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Event-Driven GenAI: Loosely coupled architectures using Amazon EventBridge and API Gateway.
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Accelerated Development: Leveraging Amazon Q Developer for code generation, refactoring, and troubleshooting.
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Hybrid and Edge AI: Integration with AWS Outposts and Wavelength for data sovereignty.
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Hands-on Lab: Using Amazon Q to optimize inference code and deploying a GenAI UI via AWS Amplify.
Module 8: AI Safety, Security, and Governance
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Input/Output Safety: Implementing Amazon Bedrock Guardrails for prompt injection and jailbreak protection.
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Privacy Controls: PII detection with Macie/Comprehend and network isolation via VPC Endpoints.
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Compliance & Lineage: Programmatic Model Cards, data tracking with Glue, and CloudTrail Lake for auditing.
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Hands-on Lab: Implementing a "Defense-in-Depth" safety layer to redact sensitive data in real-time.
Module 9: Operational Efficiency and Cost Optimization
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Token Efficiency: Prompt compression, Context Pruning, and response size limiting.
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Cost Optimization: Implementing Semantic Caching, tiered FM usage, and price-to-performance balancing.
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Resource Scaling: Managing Provisioned Throughput and auto-scaling for GenAI traffic patterns.
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Hands-on Lab: Building a semantic caching layer to reduce costs and latency for redundant queries.
Module 10: Testing, Validation, and Troubleshooting
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Evaluation Frameworks: LLM-as-a-judge patterns and systematic model evaluations.
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Advanced Observability: Performance tracing with AWS X-Ray and log analysis with CloudWatch Insights.
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Monitoring: Automated detection of bias drift, hallucinations, and policy violations.
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Final Capstone: Deploying an end-to-end, secure, and optimized Agentic RAG system ready for production.
Current process description
This professional-level program is designed for developers seeking to lead the implementation of Generative AI solutions in production environments using AWS technologies. The course validates and deepens the ability to integrate Foundation Models (FMs) into business workflows, mastering Retrieval Augmented Generation (RAG) architectures, vector databases, and Agentic AI solutions. Participants will learn to optimize applications to maximize business value while ensuring security, governance, and Responsible AI practices, comprehensively preparing the student to achieve the AWS Certified Generative AI Developer - Professional (AIP-C01) certification.
Objectives
At the end of the course, participants will be able to:
- Implement RAG workflows with intelligent chunking and high-precision semantic retrieval
- Develop AI Agents using reasoning patterns (ReAct) and tool use/function calling
- Configure Amazon Bedrock Guardrails to mitigate prompt injections and hallucinations
- Integrate FMs into enterprise workflows through API Gateway, Lambda, and event-driven architectures
- Evaluate and compare models based on quality metrics, latency, and cost-per-token
- Pass the AIP-C01 exam, mastering all 5 domains of the AWS professional blueprint
Prerequisites
To participate in this training, attendees must meet the following requirements:
- AWS Experience: Minimum of 2 years of experience building and deploying production-grade applications on AWS, with a strong understanding of compute, storage, and networking services
- GenAI Experience: At least 1 year of hands-on experience implementing Generative AI solutions (LLM consumption, prompt design, or foundation model integrations)
- Programming: Advanced proficiency in Python and experience using the AWS SDK (Boto3) to interact with cloud services
- Infrastructure and Security: Solid knowledge of AWS IAM (roles and policies), deployment via Infrastructure as Code (IaC), and CI/CD workflows for modern applications
What Does This Course Include?
| Our Value Proposition | Benefit for Participant or Company |
|---|---|
| AWS Certified Generative AI Developer - Professional (AIP-C01) International Certification | 40 hours |
| • E-learning reinforcement topics and exclusive materials and simulators | • Complementary platform with digital resources, study guides, support recordings and exam simulators. |
| • Flexible educational model (in-person or live remote) | • Possibility to choose modality without losing human interaction and teaching support. |
| • Focus on employability and professional performance and exam preparation. | • Preparation oriented to certification, job performance and professional scaling based on practice, enhanced with AI support. |
| • Integration of Artificial Intelligence in learning | • Students use AI tools to reinforce understanding, practice exams and enhance their productivity. |
| • International Certification included | • Official endorsement with global recognition. Includes certification exams and access to the partner platform. |
| • Laboratories in real learning environments. | • Unlimited practical experience with real lab accounts and access to professional cloud infrastructure. |
| • Live classes with certified expert instructors. | • Guided and personalized training with direct real-time support, not offline. Recorded classes only for review. |
| • Personalized attention, small groups. | • Individual tracking, progress evaluations and technical support during training. AI-proctored performance examiner. |
| • Post-certification support and extended access to resources | • Post-assistance, access to materials for and continuous updates. |
| • Practical methodology and real and/or simulated projects. | • Applied learning from day one: simulations, business cases, projects and real cloud environments. |
| • Certificates of Approval and/or participation. | • International Certification by AWS ACADEMY MEMBER INSTITUTION
• Infinity Training Institute USA: International Certification Diploma in English • Aula Matriz IETDH Colombia - Certificate of participation |
Why choose Infinity Training Institute?
All our courses are Internationally certified:
- Infinity Training Institute USA: International Certification Diploma in English.
- International Certification from our partners Microsoft, Oracle, Certitalents, AWS, PMI, Cisco, etc.
2. We are not an automatic platform, nor self-study through videos
We are a unique model, in-person or Remote modality (with live instructor). Technology + pedagogy + AI + expert instructors + real practice — not self-study or outdated content.
3. Training designed for today's job market
Experience applicable immediately in interviews, technical tests and real work environments.
4. Real or simulated projects with international standards
Students access real environments such as Azure, AWS, Google Cloud, Oracle Cloud, develop real or simulated projects, building a demonstrable technical portfolio depending on the type of course or certification they have chosen.
5. A unique combination in Latin America and the USA
Certification + real practice + AI + continuous support + dual diploma.
6. Proven results
More than 95% of our graduates obtain official certification and improve professionally in less than six months.
7. Competency level guarantee
If the student during the practical training process does not reach a minimum performance level of 75%, they must repeat the course if the instructor determines so, and the student has shown the commitment and minimum class attendance required by the model.
Your professional future starts here
At Infinity Training Institute we boost your growth with an innovative, flexible model focused on real learning and performance evaluation. Certified instructors, intensive practice, integrated AI and constant support: world-class training.
Learning Methodology
At Infinity Training Institute, we apply a comprehensive, ever-evolving methodology centered on practical learning, powered by Artificial Intelligence, enabling personalized instruction, performance assessment, and optimized preparation for international certifications with certified instructors, real labs, simulators, and e-learning platforms. Participants learn by doing, developing technical and professional skills in small groups, with personalized follow-up and pre and post-certification support. Infinity Training Institute: Learn. Apply. Get Certified. Transcend.
Current process description
This professional-level program is designed for developers seeking to lead the implementation of Generative AI solutions in production environments using AWS technologies. The course validates and deepens the ability to integrate Foundation Models (FMs) into business workflows, mastering Retrieval Augmented Generation (RAG) architectures, vector databases, and Agentic AI solutions. Participants will learn to optimize applications to maximize business value while ensuring security, governance, and Responsible AI practices, comprehensively preparing the student to achieve the AWS Certified Generative AI Developer - Professional (AIP-C01) certification.
Objectives
At the end of the course, participants will be able to:
- Implement RAG workflows with intelligent chunking and high-precision semantic retrieval
- Develop AI Agents using reasoning patterns (ReAct) and tool use/function calling
- Configure Amazon Bedrock Guardrails to mitigate prompt injections and hallucinations
- Integrate FMs into enterprise workflows through API Gateway, Lambda, and event-driven architectures
- Evaluate and compare models based on quality metrics, latency, and cost-per-token
- Pass the AIP-C01 exam, mastering all 5 domains of the AWS professional blueprint
Prerequisites
To participate in this training, attendees must meet the following requirements:
- AWS Experience: Minimum of 2 years of experience building and deploying production-grade applications on AWS, with a strong understanding of compute, storage, and networking services
- GenAI Experience: At least 1 year of hands-on experience implementing Generative AI solutions (LLM consumption, prompt design, or foundation model integrations)
- Programming: Advanced proficiency in Python and experience using the AWS SDK (Boto3) to interact with cloud services
- Infrastructure and Security: Solid knowledge of AWS IAM (roles and policies), deployment via Infrastructure as Code (IaC), and CI/CD workflows for modern applications
What Does This Course Include?
| Our Value Proposition | Benefit for Participant or Company |
|---|---|
| AWS Certified Generative AI Developer - Professional (AIP-C01) International Certification | 40 hours |
| • E-learning reinforcement topics and exclusive materials and simulators | • Complementary platform with digital resources, study guides, support recordings and exam simulators. |
| • Flexible educational model (in-person or live remote) | • Possibility to choose modality without losing human interaction and teaching support. |
| • Focus on employability and professional performance and exam preparation. | • Preparation oriented to certification, job performance and professional scaling based on practice, enhanced with AI support. |
| • Integration of Artificial Intelligence in learning | • Students use AI tools to reinforce understanding, practice exams and enhance their productivity. |
| • International Certification included | • Official endorsement with global recognition. Includes certification exams and access to the partner platform. |
| • Laboratories in real learning environments. | • Unlimited practical experience with real lab accounts and access to professional cloud infrastructure. |
| • Live classes with certified expert instructors. | • Guided and personalized training with direct real-time support, not offline. Recorded classes only for review. |
| • Personalized attention, small groups. | • Individual tracking, progress evaluations and technical support during training. AI-proctored performance examiner. |
| • Post-certification support and extended access to resources | • Post-assistance, access to materials for and continuous updates. |
| • Practical methodology and real and/or simulated projects. | • Applied learning from day one: simulations, business cases, projects and real cloud environments. |
| • Certificates of Approval and/or participation. | • International Certification by AWS ACADEMY MEMBER INSTITUTION
• Infinity Training Institute USA: International Certification Diploma in English • Aula Matriz IETDH Colombia - Certificate of participation |
Why choose Infinity Training Institute?
1. Internationally guaranteed certificationsAll our courses are Internationally certified:
- Infinity Training Institute USA: International Certification Diploma in English.
- International Certification from our partners Microsoft, Oracle, Certitalents, AWS, PMI, Cisco, etc.
2. We are not an automatic platform, nor self-study through videos
We are a unique model, in-person or Remote modality (with live instructor). Technology + pedagogy + AI + expert instructors + real practice — not self-study or outdated content.
3. Training designed for today's job market
Experience applicable immediately in interviews, technical tests and real work environments.
4. Real or simulated projects with international standards
Students access real environments such as Azure, AWS, Google Cloud, Oracle Cloud, develop real or simulated projects, building a demonstrable technical portfolio depending on the type of course or certification they have chosen.
5. A unique combination in Latin America and the USA
Certification + real practice + AI + continuous support + dual diploma.
6. Proven results
More than 95% of our graduates obtain official certification and improve professionally in less than six months.
7. Competency level guarantee
If the student during the practical training process does not reach a minimum performance level of 75%, they must repeat the course if the instructor determines so, and the student has shown the commitment and minimum class attendance required by the model.
Your professional future starts here
At Infinity Training Institute we boost your growth with an innovative, flexible model focused on real learning and performance evaluation. Certified instructors, intensive practice, integrated AI and constant support: world-class training.
Learning Methodology
At Infinity Training Institute, we apply a comprehensive, ever-evolving methodology centered on practical learning, powered by Artificial Intelligence, enabling personalized instruction, performance assessment, and optimized preparation for international certifications with certified instructors, real labs, simulators, and e-learning platforms. Participants learn by doing, developing technical and professional skills in small groups, with personalized follow-up and pre and post-certification support. Infinity Training Institute: Learn. Apply. Get Certified. Transcend.