<span data-i18n data-en="Beginner" data-bn="বিগিনার">Beginner</span>

Python Programming from Beginner to Practical Projects

Build practical, job-relevant capability in Python Programming from Beginner to Practical Projects through guided practice, projects and a capstone.

9 chapters 57 lessons 19 hours

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Career track 04

Technology & Data Learning Path

Develop job-ready data, coding and cybersecurity capability through practical projects.

Jobs this leads to Data analysis, BI, software/web development and cybersecurity pathways

8 courses · 158 hours · ~6 months See the path

Why take this course?

Starts with Python setup, syntax, variables and control flow and progresses toward production-style Python project

Includes 9 focused chapters and 57 guided lessons with practice and review

Built around practical Python Programming from Beginner to Practical Projects workflows rather than generic theory or income promises

What you will be able to do

✓ Explain and apply the core concepts of Python Programming from Beginner to Practical Projects
✓ 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

9 chapters · 57 lessons

▶ Concepts: Python setup, syntax, variables and control flow 10m FREE
▶ Setup: Python setup, syntax, variables and control flow 16m FREE
🔒 Guided start: Python setup, syntax, variables and control flow 22m
🔒 Practice: Python setup, syntax, variables and control flow 22m
🔒 Common mistakes: Python setup, syntax, variables and control flow 16m
🔒 Checkpoint: Python setup, syntax, variables and control flow 20m

▶ Concepts: Functions, modules and clean code 12m FREE
🔒 Setup: Functions, modules and clean code 18m
🔒 Guided start: Functions, modules and clean code 18m
🔒 Practice: Functions, modules and clean code 24m
🔒 Common mistakes: Functions, modules and clean code 18m
🔒 Checkpoint: Functions, modules and clean code 16m

🔒 Principles: Collections, comprehensions and data handling 16m
🔒 Tools: Collections, comprehensions and data handling 16m
🔒 Guided build: Collections, comprehensions and data handling 22m
🔒 Applied exercise: Collections, comprehensions and data handling 28m
🔒 Troubleshoot: Collections, comprehensions and data handling 16m
🔒 Quality review: Collections, comprehensions and data handling 20m
🔒 Checkpoint: Collections, comprehensions and data handling 20m

🔒 Principles: Files, exceptions and input validation 12m
🔒 Tools: Files, exceptions and input validation 18m
🔒 Guided build: Files, exceptions and input validation 24m
🔒 Applied exercise: Files, exceptions and input validation 24m
🔒 Troubleshoot: Files, exceptions and input validation 18m
🔒 Quality review: Files, exceptions and input validation 22m
🔒 Checkpoint: Files, exceptions and input validation 16m

🔒 Project brief: Object-oriented programming fundamentals 12m
🔒 Plan: Object-oriented programming fundamentals 20m
🔒 Hands-on build: Object-oriented programming fundamentals 28m
🔒 Real scenario: Object-oriented programming fundamentals 28m
🔒 Review: Object-oriented programming fundamentals 22m
🔒 Checkpoint: Object-oriented programming fundamentals 16m

🔒 Project brief: Working with APIs and JSON 14m
🔒 Plan: Working with APIs and JSON 16m
🔒 Hands-on build: Working with APIs and JSON 30m
🔒 Real scenario: Working with APIs and JSON 30m
🔒 Review: Working with APIs and JSON 18m
🔒 Checkpoint: Working with APIs and JSON 18m

🔒 Advanced concepts: Testing, debugging and virtual environments 14m
🔒 Workflow: Testing, debugging and virtual environments 20m
🔒 Case study: Testing, debugging and virtual environments 26m
🔒 Advanced practice: Testing, debugging and virtual environments 26m
🔒 Edge cases: Testing, debugging and virtual environments 20m
🔒 Optimise: Testing, debugging and virtual environments 24m
🔒 Checkpoint: Testing, debugging and virtual environments 16m

🔒 Advanced concepts: Automation and data-processing mini projects 16m
🔒 Workflow: Automation and data-processing mini projects 22m
🔒 Case study: Automation and data-processing mini projects 22m
🔒 Advanced practice: Automation and data-processing mini projects 28m
🔒 Edge cases: Automation and data-processing mini projects 22m
🔒 Optimise: Automation and data-processing mini projects 20m
🔒 Checkpoint: Automation and data-processing mini projects 18m

🔒 Capstone brief: production-style Python project 14m
🔒 Plan: production-style Python project 16m
🔒 Build: production-style Python project 38m
🔒 Professional review: production-style Python project 24m
🔒 Present and reflect: production-style Python project 16m

Course guidance

AlinLearning Technology & Data Course Team

Technical foundations, projects and quality review

Lessons progress from concepts and setup into projects, troubleshooting and advanced practice.

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.

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Microsoft Learn

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Python documentation

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OWASP Top 10

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.