Skip to Content

Available AI Courses

Entry-level AI Engineering Courses

  • AI Engineer

  • Applied AI Developer

4 months
Apply Now

• What is an LLM

• Tokens, Latency & Cost mechanics

• Context window

• Hallucinations

• Temperature and determinism

• Prompt anatomy

• Role-based prompting

• Structured output (JSON)

• Few-shot prompting

• Prompt guardrails

• Calling OpenAI / Anthropic APIs

• Handling responses & errors

• JSON parsing

• What are embeddings

• Vector databases

 • Similarity search

• FastAPI basics & API endpoints

• Request / Response handling

• Connecting LLM to backend

 

Advanced AI System Design Courses

  • Agentic Systems Specialist

  • RAG Developer

5 months
Apply Now

• Vector databases

• Document chunking Strategy

• Retrieval pipeline

• Tool calling

• Function calling

• Multi-step agents

• Agent memory

• Workflow orchestration

• Async and Concurrency

• Rate limiting & Caching

• Cost tracking & Token budgeting

• User isolation & Tenant isolation

• Per-user vector DB

• Usage tracking

• API retry logic and Timeout handling

• Cloud deployment (on GCP)

• Environment variables

• Secrets handling

• Basic monitoring

 

Corporate

Custom
Apply Now

• Prompt injection

• Data leakage prevention

• Input validation

• API security

• Production deployment

• Concurrency scaling

• Worker scaling

• Performance monitoring

• When to use fine-tuning

• RAG vs fine-tuning decision

• Cost comparison

• No hands-on training

 

Frequently Asked Questions

✔ Graduates wanting to move into AI

✔ Software developers wanting to move into AI

✔ Engineers building AI products

✔ Backend developers learning LLM systems

✔ Professionals transitioning into AI engineering

The program follows a structured learning format designed for consistent progress and hands-on practice.

  • Daily sessions: 1 hour 30 minutes of instructor-led classroom training.

  • Weekly schedule: Approximately 8 hours per week.

  • Theory sessions: Around 4 hours per week focused on core AI engineering concepts.

  • Hands-on practice: Around 4 hours per week dedicated to building and implementing real AI systems.

This balanced approach ensures students understand the concepts and immediately apply them through practical implementation.

Most AI courses focus on tools and prompts. Modern AI products require engineers who understand RAG systems, agent orchestration, and deployment.

SilverDew was created to train engineers to build production AI systems.

Not a prompt engineering course.

Not a tool tutorial.

Learn how to design, build, and deploy AI systems.

Please refer to this page, Refund Policy for more details.

Structured, Employment-focused, Training Programs designed around Real AI Hiring Expectations, for Students and Professionals.

Apply Now