Learn Forward Deployed Engineering (AI FDE), Generative AI, Agentic AI, AI Agents, Artificial Intelligence (AI/ML), Data Science, Machine Learning, Deep Learning, Gen AI Testing, and Agentic AI Testing through real-time training and practical projects in San Francisco, San Jose, Seattle, New York City, Boston, Austin, Dallas, Houston, Los Angeles, San Diego, and Chicago.
Build practical skills in Full Stack AI Forward Deployed Engineering (AI FDE), Generative AI, Agentic AI, AI Agents, Artificial Intelligence, Machine Learning, Data Science, Deep Learning, RAG, LLMs, Gen AI Testing, and Agentic AI Testing. The training focuses on real-time projects, AI application development, enterprise AI solutions, deployment, and modern AI engineering practices.
Training Format
- Instructor-led, hands-on training with live demonstrations and coding exercises.
- Real-time project work covering LLM applications, RAG, AI agents, APIs, and production-oriented AI workflows.
- Full-stack approach: Python, backend/API development, AI/ML integration, databases, cloud/deployment concepts, and frontend integration.
- AI FDE focus: translating business requirements into AI solutions, building prototypes, integrating enterprise data/tools, testing, and deploying AI applications.
- Practical assessments and projects designed to demonstrate applied skills rather than only theoretical knowledge.
- Certification: completion certificate based on the provider’s stated requirements.
Expected Outcomes
By completing the training, learners should be able to:
- Build and integrate Generative AI and Agentic AI applications.
- Develop RAG/LLM-based solutions and connect them to enterprise data.
- Create AI-powered APIs and full-stack applications.
- Apply Gen AI and Agentic AI testing techniques.
- Work with machine-learning and deep-learning concepts relevant to AI applications.
- Understand the responsibilities of a Forward Deployed AI Engineer, including requirements analysis,
Forward Deployed AI Engineer Training – Course Content@+91 9542701987,7993762900
- AI & Software Engineering Foundations
- Python programming
- Data structures and algorithms
- Git & GitHub
- REST APIs and JSON
- SQL and databases
- Software development best practices
- Machine Learning & Deep Learning
- ML fundamentals
- Supervised and unsupervised learning
- Model evaluation
- Neural networks
- Deep learning fundamentals
- Model integration into applications
- Generative AI & LLMs
- LLM fundamentals
- Prompt engineering
- Open-source and commercial LLMs
- Embeddings and tokenization
- Structured outputs
- LLM API integration
- RAG – Retrieval-Augmented Generation
- RAG architecture
- Document processing
- Chunking and embeddings
- Vector databases
- Semantic search
- Retrieval optimization
- Enterprise knowledge-base applications
- Agentic AI & AI Agents
- AI agent architecture
- Tool calling and function calling
- Agent workflows
- Multi-agent systems
- Planning and reasoning patterns
- Memory and context management
- Agentic automation
- Full-Stack AI Application Development
- Python/FastAPI
- Backend development
- Frontend integration
- Streamlit
- Authentication and APIs
- Database integration
- AI-powered web applications
- Forward Deployed Engineering
- Understanding customer/business requirements
- Translating business problems into AI solutions
- Rapid prototyping
- Customer-facing technical consulting
- Enterprise system integration
- Solution architecture
- Iterative development and deployment
- AI Testing & Evaluation
- LLM testing
- RAG evaluation
- AI agent testing
- Prompt and response evaluation
- Accuracy, reliability and safety testing
- Automated evaluation workflows
- Cloud & AI Deployment
- Docker
- Cloud fundamentals
- CI/CD concepts
- API deployment
- Model/application deployment
- Monitoring and logging
- Production AI workflows
- Enterprise AI & LLMOps
- AI security fundamentals
- Data privacy considerations
- Observability
- Model monitoring
- Cost and performance optimization
- LLMOps concepts
- Real-Time AI Projects
- Enterprise RAG chatbot
- AI customer-support agent
- Multi-agent automation system
- Document intelligence application
- AI-powered business assistant
- Full-stack GenAI application
- End-to-end AI deployment project
- Career & FDE Skills
- AI solution presentation
- Technical documentation
- Client communication
- Architecture discussions
- Project demonstrations
- Portfolio development
- Forward Deployed AI Engineer interview preparation
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