AI & Generative AI Training
& Certification Programs

Rapidly Evolving AI Landscape

The AI and generative AI landscape evolves weekly — new models, frameworks, and capabilities emerge constantly. Teams need structured training to build durable AI skills that remain relevant as the technology evolves.

Enterprise AI Adoption Complexity

Deploying AI in enterprise environments requires understanding data governance, security, compliance, cost management, and integration with existing systems — far beyond basic model usage.

AI Security & Governance

Enterprise AI deployments require robust security controls, prompt injection prevention, data privacy compliance, model governance, and responsible AI frameworks that most teams lack expertise in.

LLM Selection & Optimization

Choosing between OpenAI GPT-4, Azure OpenAI, OCI AI, AWS Bedrock, Google Gemini, and open-source models requires deep understanding of capabilities, costs, latency, and enterprise deployment options.

RAG & Vector Database Complexity

Building Retrieval-Augmented Generation systems requires expertise in vector databases, embedding models, chunking strategies, retrieval optimization, and enterprise knowledge base integration.

AI Application Development

Building production-grade AI applications with LangChain, LlamaIndex, or custom frameworks requires software engineering skills combined with AI/ML knowledge that most development teams lack.

AI & Generative AI Fundamentals

Foundation training covering AI concepts, machine learning basics, generative AI models, LLMs, transformer architecture, and enterprise AI adoption frameworks.

Prompt Engineering

Advanced prompt engineering training covering prompt design patterns, chain-of-thought, few-shot learning, system prompts, and enterprise prompt library development.

LLM Platforms & APIs

Hands-on training with OpenAI GPT-4, Azure OpenAI, OCI Generative AI, AWS Bedrock, and Google Gemini for enterprise AI application development.

RAG & Vector Databases

Retrieval-Augmented Generation training covering vector databases (Pinecone, Weaviate, pgvector), embedding models, chunking strategies, and enterprise knowledge base integration.

AI Agents & Multi-Agent Systems

AI agent training covering autonomous agents, multi-agent orchestration, tool use, function calling, ReAct patterns, and enterprise AI workflow automation.

AI Security & Governance

Enterprise AI security training covering prompt injection prevention, data privacy, model governance, responsible AI frameworks, and compliance for regulated industries.

AI Application Development

LangChain and LlamaIndex training for building production-grade AI applications, chatbots, document Q&A systems, and enterprise AI workflows.

MLOps & AI Infrastructure

MLOps training covering model deployment, monitoring, drift detection, A/B testing, and AI infrastructure on cloud platforms for production AI systems.

Understand transformer architecture, attention mechanisms, LLM training, fine-tuning, and the capabilities and limitations of modern generative AI models for enterprise applications.

Design effective prompts using chain-of-thought, few-shot learning, and structured output techniques; build enterprise prompt libraries; and implement prompt optimization workflows.

Design and implement Retrieval-Augmented Generation systems with vector databases, implement semantic search, optimize retrieval quality, and integrate enterprise knowledge bases.

Build autonomous AI agents with tool use and function calling, implement multi-agent orchestration with LangChain/LlamaIndex, and design enterprise AI workflow automation systems.

Implement prompt injection defenses, configure data privacy controls, establish AI governance frameworks, and ensure compliance for AI deployments in regulated enterprise environments.

Deploy AI applications on cloud platforms (OCI AI, Azure OpenAI, AWS Bedrock), implement MLOps pipelines, monitor model performance, and manage AI infrastructure costs.

Software Developers

Developers building AI-powered applications who need hands-on training with LLM APIs, LangChain, RAG systems, and AI agent frameworks for production deployments.

Data Scientists & ML Engineers

Data professionals transitioning to generative AI who need training on LLMs, fine-tuning, RAG, and MLOps for deploying production generative AI systems.

Cloud Architects

Architects designing enterprise AI platforms who need deep knowledge of cloud AI services (OCI AI, Azure OpenAI, AWS Bedrock, Vertex AI) and AI infrastructure patterns.

Product Managers

Product leaders building AI-powered products who need to understand AI capabilities, limitations, prompt engineering, and enterprise AI governance for informed product decisions.

Security Engineers

Security professionals implementing AI security controls, prompt injection defenses, data privacy frameworks, and responsible AI governance for enterprise AI deployments.

Business Leaders

Executives and business leaders who need to understand generative AI capabilities, enterprise use cases, ROI frameworks, and strategic AI adoption for organizational transformation.

• AI/ML Concepts
• Transformer Architecture
• LLM Capabilities
• Generative AI Models
• Enterprise AI Adoption

• Prompt Design Patterns
• Chain-of-Thought
• Few-Shot Learning
• System Prompts
• Structured Outputs

• OpenAI GPT-4 API
• Azure OpenAI Service
• OCI Generative AI
• AWS Bedrock
• Google Gemini API

• Vector Embeddings
• Vector Databases
• Chunking Strategies
• Semantic Search
• RAG Optimization

• Agent Architecture
• Tool Use & Function Calling
• LangChain Agents
• Multi-Agent Systems
• ReAct Patterns

• LangChain Framework
• LlamaIndex
• Document Q&A
• Chatbot Development
• AI Workflow Automation

• Prompt Injection Defense
• Data Privacy
• Model Governance
• Responsible AI
• Compliance Frameworks

• Model Deployment
• AI Monitoring
• Drift Detection
• A/B Testing
• AI Cost Management

AI Fundamentals Bootcamp

3-day AI and generative AI fundamentals training covering LLMs, prompt engineering, RAG, and enterprise AI adoption with hands-on labs.

AI Developer Workshop

Focused 3-day developer workshop covering LangChain, RAG systems, AI agents, and production AI application development with hands-on coding labs.

Enterprise AI Strategy Workshop

Executive 1-day AI strategy workshop covering generative AI capabilities, enterprise use cases, governance frameworks, and AI transformation roadmap planning.

Corporate AI Program

Customized enterprise AI training aligned to your industry, use cases, cloud AI platform, and organizational AI maturity level.

Design and test prompts using chain-of-thought, few-shot learning, and structured output techniques with OpenAI GPT-4 and Azure OpenAI APIs for enterprise use cases.

Build a complete RAG system: ingest documents, generate embeddings, store in a vector database (pgvector), implement semantic search, and integrate with an LLM for document Q&A.

Build an AI agent with LangChain using tool use and function calling, implement a ReAct reasoning loop, and create a multi-step enterprise workflow automation agent.

Configure OCI Generative AI service, deploy Cohere Command models, implement RAG with OCI Search, and build an enterprise AI application on Oracle Cloud Infrastructure.

Test prompt injection attacks, implement input validation and output filtering defenses, configure content safety filters, and implement AI governance controls for enterprise deployments.

Build a production-ready AI application with LangChain covering document loading, text splitting, vector store integration, conversational memory, and streaming responses.

Azure AI Engineer Associate (AI-102)

Azure AI certification covering Azure OpenAI, Cognitive Services, and AI solution development.

OCI AI Foundations Associate

OCI AI certification covering OCI AI services and generative AI on Oracle Cloud.

AWS Machine Learning Specialty

AWS ML certification covering machine learning, AI services, and MLOps on AWS.

Google Professional ML Engineer

Google Cloud ML certification covering Vertex AI, MLOps, and AI solution design.