Ripotek Technologies Inc.
Design. Engineer. Deliver.
Calgary, Alberta
www.ripotek.com
training@ripotek.com
Prompt Engineering
Professional Training Program Syllabus
Program Overview
Duration
12 Weeks (2 sessions per week)
24 total sessions, 72 instructional hours
Investment
CAD $700
Flexible payment plans available
Schedule
Monday/Wednesday
6:00 PM - 9:00 PM Mountain Time
Certification
Ripotek Prompt Engineer
Industry credential
Program Description
Master the art and science of prompt engineering for large language models. Learn to design effective prompts, chain reasoning tasks, evaluate outputs, and build AI workflows.
Work with GPT-4, Claude, and other LLMs. Build practical applications and understand model limitations. Prepare for high-demand prompt engineering roles.
Learning Outcomes
Upon completion, you will be able to:
Design effective prompts for various tasks
Chain prompts for complex workflows
Evaluate and refine outputs
Understand model capabilities and limits
Implement zero-shot and few-shot learning
Build AI-powered applications
Apply advanced techniques (CoT, ReAct)
Manage context windows effectively
Implement safety guardrails
Optimize for cost and performance
Work with multiple LLM providers
Create prompt libraries and templates
12-Week Curriculum
Week 1: LLM Fundamentals
- How LLMs work
- Tokenization basics
- Temperature and sampling
- Model comparison
Week 2: Prompt Design Basics
- Instruction writing
- Context provision
- Role assignment
- Output formatting
Week 3: Advanced Techniques
- Chain-of-Thought (CoT)
- Few-shot learning
- ReAct framework
- Self-consistency
Week 4: Prompt Chaining
- Sequential prompts
- Parallel prompting
- Workflow design
- Error handling
Week 5: Evaluation Methods
- Output assessment
- Quality metrics
- A/B testing prompts
- Regression testing
Week 6: Domain Applications
- Code generation
- Content creation
- Data analysis
- Customer service
Week 7: Safety and Ethics
- Bias mitigation
- Jailbreak prevention
- Content filtering
- Responsible AI
Week 8: API Integration
- OpenAI API
- Azure OpenAI
- Anthropic Claude
- Error handling
Week 9: RAG Systems
- Vector databases
- Document retrieval
- Context injection
- Hybrid search
Week 10: Optimization
- Cost optimization
- Latency reduction
- Caching strategies
- Batch processing
Week 11: Production Deployment
- Monitoring
- Logging
- Version control
- CI/CD for prompts
Week 12: Capstone Project
- End-to-end application
- Presentation
- Portfolio development
- Career planning
Career Services
Typical Roles:
- Prompt Engineer
- AI Product Manager
- GenAI Specialist
- LLM Application Developer
$75K+
Average Starting Salary