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AlinLearning AI & Automation Course Team
AI workflows, automation and applied practiceThis course is maintained as a practical learning path with guided workflows, review checkpoints and responsible-use notes.
<span data-i18n data-en="Beginner" data-bn="বিগিনার">Beginner</span>
AI Agents for Beginners
Build practical, job-relevant capability in AI Agents for Beginners through guided practice, projects and a capstone.
Career track 01
AI & Automation Learning Path
Build practical AI capability from everyday use to automation, agents and multimodal workflows.
Jobs this leads to
AI-enabled operations, automation support, productivity and content workflows
Why take this course?
1
Starts with What agents are and when not to use them and progresses toward build a bounded task agent
2
Includes 8 focused chapters and 50 guided lessons with practice and review
3
Built around practical AI Agents for Beginners workflows rather than generic theory or income promises
What you will be able to do
- ✓ Explain and apply the core concepts of AI Agents for Beginners
- ✓ Use the current tools and workflows used in real projects
- ✓ Complete guided exercises and troubleshoot common problems
- ✓ Produce a portfolio-ready or application-ready capstone
- ✓ Evaluate quality, risk, ethics and professional best practices
Full curriculum
8 chapters · 50 lessons- ▶ Concepts: What agents are and when not to use them 14m FREE
- ▶ Setup: What agents are and when not to use them 14m FREE
- 🔒 Guided start: What agents are and when not to use them 20m
- 🔒 Practice: What agents are and when not to use them 26m
- 🔒 Common mistakes: What agents are and when not to use them 14m
- 🔒 Checkpoint: What agents are and when not to use them 18m
- ▶ Concepts: Agent loop, goals, tools, memory and context 10m FREE
- 🔒 Setup: Agent loop, goals, tools, memory and context 16m
- 🔒 Guided start: Agent loop, goals, tools, memory and context 22m
- 🔒 Practice: Agent loop, goals, tools, memory and context 22m
- 🔒 Common mistakes: Agent loop, goals, tools, memory and context 16m
- 🔒 Checkpoint: Agent loop, goals, tools, memory and context 20m
- 🔒 Principles: Tool calling and structured actions 14m
- 🔒 Tools: Tool calling and structured actions 20m
- 🔒 Guided build: Tool calling and structured actions 20m
- 🔒 Applied exercise: Tool calling and structured actions 26m
- 🔒 Troubleshoot: Tool calling and structured actions 20m
- 🔒 Quality review: Tool calling and structured actions 18m
- 🔒 Checkpoint: Tool calling and structured actions 18m
- 🔒 Principles: Knowledge retrieval and grounded responses 16m
- 🔒 Tools: Knowledge retrieval and grounded responses 16m
- 🔒 Guided build: Knowledge retrieval and grounded responses 22m
- 🔒 Applied exercise: Knowledge retrieval and grounded responses 28m
- 🔒 Troubleshoot: Knowledge retrieval and grounded responses 16m
- 🔒 Quality review: Knowledge retrieval and grounded responses 20m
- 🔒 Checkpoint: Knowledge retrieval and grounded responses 20m
- 🔒 Project brief: Planning, delegation and multi-step workflows 10m
- 🔒 Plan: Planning, delegation and multi-step workflows 18m
- 🔒 Hands-on build: Planning, delegation and multi-step workflows 32m
- 🔒 Real scenario: Planning, delegation and multi-step workflows 26m
- 🔒 Review: Planning, delegation and multi-step workflows 20m
- 🔒 Checkpoint: Planning, delegation and multi-step workflows 20m
- 🔒 Project brief: Guardrails, permissions and human approval 12m
- 🔒 Plan: Guardrails, permissions and human approval 20m
- 🔒 Hands-on build: Guardrails, permissions and human approval 28m
- 🔒 Real scenario: Guardrails, permissions and human approval 28m
- 🔒 Review: Guardrails, permissions and human approval 22m
- 🔒 Checkpoint: Guardrails, permissions and human approval 16m
- 🔒 Advanced concepts: Evaluation, observability and failure recovery 18m
- 🔒 Workflow: Evaluation, observability and failure recovery 18m
- 🔒 Case study: Evaluation, observability and failure recovery 24m
- 🔒 Advanced practice: Evaluation, observability and failure recovery 30m
- 🔒 Edge cases: Evaluation, observability and failure recovery 18m
- 🔒 Optimise: Evaluation, observability and failure recovery 22m
- 🔒 Checkpoint: Evaluation, observability and failure recovery 20m
- 🔒 Capstone brief: build a bounded task agent 10m
- 🔒 Plan: build a bounded task agent 18m
- 🔒 Build: build a bounded task agent 40m
- 🔒 Professional review: build a bounded task agent 20m
- 🔒 Present and reflect: build a bounded task agent 18m
Course guidance
Official reference anchors
Curriculum references used for maintenance
These links are reference sources for course maintenance. They do not imply certification, endorsement or guaranteed outcomes. Platform rules and requirements can change.
Common questions
Is this course pre-recorded?
The delivery format is shown inside the course. Available lessons, videos, reading material and activities can be completed at your own pace unless a live session is specifically stated.
How long do I keep access?
Course access remains available according to the access terms shown at purchase.
What if the course is not right for me?
Check the current published Refund Policy before purchase.
Do I get a completion record?
The platform can show course completion and certificate-verification features where enabled.