Who It Is For
Built for AI Developers
This certification is designed for AI developers, forward-deployed engineers, and technical builders who need more than theory. It focuses on the workflows, tools, and architecture decisions used in real client delivery and internal product teams.
DeepsoftAI created this program to help learners move from classroom concepts to industry execution with confidence. The curriculum is practical, current, and aligned to the demands of enterprise AI implementation.
Course Syllabus
A focused, industry-relevant syllabus covering the platforms, frameworks, and case studies needed to build modern AI systems in production.
Generative AI
Core concepts, model behavior, prompting patterns, and practical implementation foundations.
Agentic AI
Planning, tool use, orchestration, memory, and multi-step autonomous workflows.
Cloud AI Service
How managed AI services accelerate deployment, governance, and enterprise adoption.
AWS Sagemaker
Model development, training pipelines, deployment workflows, and operational best practices.
AWS Bedrock
Foundation model access, managed integrations, and secure enterprise GenAI deployment patterns.
AWS AgentCore
Agent-oriented architecture concepts and implementation approaches for scalable AI systems.
GCP Vertex
Vertex AI workflows for experimentation, model management, and production integration.
AZURE openai
Azure OpenAI capabilities, enterprise controls, and deployment patterns for business use cases.
Advanced Topics
Hands-On Delivery Topics
The program continues beyond platform fundamentals into the tools and case studies that prepare developers for real project execution.
Azure Databricks
Data and AI workflow integration for scalable experimentation, analytics, and model operations.
MCP Server Case Study
A practical case study showing how model context protocols and tool-connected systems are applied in delivery scenarios.
Claude Code
AI-assisted engineering workflows for faster development, review, and implementation support.
Antigravity
Emerging concepts, experimentation patterns, and applied thinking for next-generation AI delivery.