Data and AI

Building AI Agents and Workflows

Build AI systems that take genuine multi-step actions and use tools, not just answer single-turn questions

18h4 lessonsTier 2 hireabilityTier 2 certificate

What you'll be able to do

You can design and build a genuine AI agent that plans multi-step tasks, calls external tools/functions correctly, and handles genuine failure and looping risks safely.

Job titles this qualifies you for

AI Automation SpecialistAI Implementation Consultant
Market intelligence
Demand
High
Remote
80% remote roles
Nigeria salary
Not a primary local hiring category for employed roles; consulting engagement income is highly variable
Remote (USD)
AI Prompt Engineer roles average $116,200-$140,324/year (25th-75th percentile $116,238-$172,544); AI/Automation Specialist roles average $127,500/year remote ($115,000-$140,000 range) — job title alone can shift reported pay significantly, with 'specialist' titles sometimes paid notably less than 'engineer' titles for comparable work

Lessons

Stage 1 — Foundation
1
What Makes an Agent Genuinely Different from a Prompt
30 min
2
Designing and Implementing Tool Calling
35 min
Stage 2 — Applied
1
Planning and Multi-Step Task Decomposition
35 min
2
Preventing Loops and Managing Agent Failure Safely
25 min
Tier 2 Proof Submission

Building AI Agents and Workflows Portfolio

Demonstrate genuine agent-vs-prompt architectural judgement, tool-calling design, multi-step planning, and safe failure/guardrail design.

1.An agent-necessary vs simple-prompt scenario comparison
2.A tool description and a parameter-validation explanation
3.A dependent multi-step task with a ReAct adaptation example
4.Iteration/cost-ceiling safeguards and a human-confirmation justification
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