Advanced AI Tool Mastery

Designed for professionals who already use AI and want to apply advanced tools, workflows, and automation with greater reliability. By the end, learners will be able to select the right AI tools, design sophisticated prompts and workflows, work with multimodal and data-driven systems, build lightweight automations and agents, and evaluate results safely.

Course Objectives

Design multi-step AI workflows that combine models, tools, data, and human review.
Select AI tools and model configurations against capability, cost, privacy, and reliability requirements.
Create reusable prompts, structured outputs, and evaluation methods for dependable results.
Automate operational tasks with appropriate safeguards, monitoring, and escalation paths.
Analyze AI outputs for quality, bias, security, and business relevance.
Develop and defend an implementation plan for an advanced AI-enabled workflow.

12 sections · 81 lessons · 7h 57m

Open the course on Coursebox

5.000,00 LE

Sorumlu	Rehaf Foula
Son Güncelleme	18.10.2026
Tamamlanma Zamanı	8 saat 6 dakika
Üyeler	1

Kurs
Şartlar

1. Advanced AI Landscape

1Dersler · 6 dk.
- 1.1 Welcome
  
  Yeni
2. Tool Selection Strategy

3Dersler · 18 dk.
- 2.1 Define the Use Case
  
  Yeni
- 2.2 Compare Tool Capabilities
  
  Yeni
- 2.3 Tool Selection Check
  
  Yeni
3. Prompt Systems

6Dersler · 36 dk.
- 3.1 Engineer Reusable Instructions
  
  Yeni
- 3.2 Control Context Windows
  
  Yeni
- 3.3 Generate Structured Outputs
  
  Yeni
- 3.4 Use Examples Strategically
  
  Yeni
- 3.5 Prompt System Build
  
  Yeni
- 3.6 Prompt Quality Check
  
  Yeni
4. Workflow Orchestration

10Dersler · 1 sa.
- 4.1 Model the AI Workflow
  
  Yeni
- 4.2 Sequence Tool Calls
  
  Yeni
- 4.3 Route Tasks by Capability
  
  Yeni
- 4.4 Manage State and Memory
  
  Yeni
- 4.5 Design Human Handoffs
  
  Yeni
- 4.6 Handle Workflow Failures
  
  Yeni
- 4.7 Orchestration Blueprint
  
  Yeni
- 4.8 Test the Workflow
  
  Yeni
- 4.9 Optimize Workflow Costs
  
  Yeni
- 4.10 Orchestration Review
  
  Yeni
5. AI Research Systems

10Dersler · 1 sa.
- 5.1 Frame Complex Research
  
  Yeni
- 5.2 Search Across Sources
  
  Yeni
- 5.3 Retrieve Relevant Evidence
  
  Yeni
- 5.4 Verify AI Citations
  
  Yeni
- 5.5 Synthesize Conflicting Findings
  
  Yeni
- 5.6 Build a Research Brief
  
  Yeni
- 5.7 Use Multimodal Evidence
  
  Yeni
- 5.8 Protect Research Integrity
  
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- 5.9 Research System Build
  
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- 5.10 Research Reliability Check
  
  Yeni
6. Generative Production

6Dersler · 36 dk.
- 6.1 Plan AI-Assisted Production
  
  Yeni
- 6.2 Direct Text Generation
  
  Yeni
- 6.3 Create Visual Assets
  
  Yeni
- 6.4 Production Workflow Check
  
  Yeni
- 6.5 Edit for Audience Fit
  
  Yeni
- 6.6 Measure Creative Quality
  
  Yeni
7. Data and Analysis

9Dersler · 54 dk.
- 7.1 Prepare Data for AI
  
  Yeni
- 7.2 Choose an Analysis Method
  
  Yeni
- 7.3 Explore Data with Models
  
  Yeni
- 7.4 Build Analytical Prompts
  
  Yeni
- 7.5 Interpret Model Findings
  
  Yeni
- 7.6 Check Statistical Reasoning
  
  Yeni
- 7.7 Visualize Decision Signals
  
  Yeni
- 7.8 Analytical Decision Brief
  
  Yeni
- 7.9 Analysis Reliability Check
  
  Yeni
8. Agentic AI Systems

10Dersler · 1 sa.
- 8.1 Understand Agent Patterns
  
  Yeni
- 8.2 Define Agent Boundaries
  
  Yeni
- 8.3 Connect External Tools
  
  Yeni
- 8.4 Manage Agent Memory
  
  Yeni
- 8.5 Design Agent Plans
  
  Yeni
- 8.6 Add Approval Gates
  
  Yeni
- 8.7 Evaluate Agent Behavior
  
  Yeni
- 8.8 Recover from Agent Errors
  
  Yeni
- 8.9 Deploy an Agent Prototype
  
  Yeni
- 8.10 Agent System Review
  
  Yeni
9. Automation and Integration

10Dersler · 1 sa.
- 9.1 Identify Automation Leverage
  
  Yeni
- 9.2 Map Existing Systems
  
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- 9.3 Design Trigger Logic
  
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- 9.4 Transform Data Between Tools
  
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- 9.5 Automate Repetitive Decisions
  
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- 9.6 Add Operational Safeguards
  
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- 9.7 Monitor Automated Runs
  
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- 9.8 Estimate Automation Value
  
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- 9.9 Automation Implementation Plan
  
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- 9.10 Automation Readiness Check
  
  Yeni
10. Quality and Reliability

9Dersler · 54 dk.
- 10.1 Define Output Quality
  
  Yeni
- 10.2 Build Evaluation Datasets
  
  Yeni
- 10.3 Test Prompt Variants
  
  Yeni
- 10.4 Measure Factual Accuracy
  
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- 10.5 Assess Bias and Fairness
  
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- 10.6 Run Adversarial Tests
  
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- 10.7 Monitor Production Drift
  
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- 10.8 Create a Quality Dashboard
  
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- 10.9 Reliability Improvement Plan
  
  Yeni
11. Governance and Security

6Dersler · 36 dk.
- 11.1 Classify AI Risks
  
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- 11.2 Protect Sensitive Data
  
  Yeni
- 11.3 Defend Against Prompt Attacks
  
  Yeni
- 11.4 Assign Human Accountability
  
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- 11.5 Governance Control Plan
  
  Yeni
- 11.6 Governance Knowledge Check
  
  Yeni
12. Capstone Implementation

1Dersler · 6 dk.
- 12.1 Key Takeaways
  
  Yeni