1. COURSE OVERVIEW

The Applied Artificial Intelligence & Python course introduces learners to practical AI development through Python. Learners move from basic programming and responsible AI use to building a simple chatbot, intelligent FAQ, automation or other business-oriented prototype for a real client.

2. PRACTICAL INFORMATION

3. OBJECTIVE

By the end of the course, the learner should be able to write basic Python programs, manipulate simple data, interact with AI services or models through guided code, build a small applied AI prototype and test its outputs for accuracy, usefulness and confidentiality.

4. PRACTICAL CLASS 1 – PYTHON BASICS & AI FOUNDATIONS

• Set up the Python working environment
• Use variables, data types, conditions, loops and functions
• Read and write simple files or data
• Understand what generative AI can and cannot do
• Write effective instructions/prompts and verify outputs
• Apply basic privacy and responsible-use rules

Practical Assignment: Create the first Python components required for the client use case.

5. PRACTICAL CLASS 2 – DATA, AI INTERACTION & AUTOMATION

• Structure simple data for an AI use case
• Use Python libraries and reusable functions
• Connect guided code to an AI service or model when appropriate
• Send instructions and process returned results
• Create a simple question-answer, classification or automation workflow
• Handle errors and validate outputs

Practical Assignment: Build the first working version of the client AI workflow.

6. PRACTICAL CLASS 3 – CHATBOT/FAQ PROTOTYPE & TESTING

• Define the user need and conversation flow
• Build a simple chatbot, intelligent FAQ or business assistant prototype
• Prepare the information or knowledge used by the prototype
• Test common and difficult user questions
• Add safeguards, fallback responses and human review points
• Document installation, use and limitations

Practical Assignment: Test the client prototype and prepare a list of corrections before presentation.

7. PROFESSIONAL IMMERSION

Work with a developer, digital professional or organisation on a real need involving automation, data handling or an AI-assisted workflow, under supervision.

8. PROFESSIONAL PROJECT & CLIENT PRESENTATION

Finalise the applied AI prototype, demonstrate it to the client or supervisor, collect feedback, improve reliability and prepare simple user documentation.

9. ASSESSMENT & VALIDATION

Complete a practical Python/AI assessment, submit the final code and working prototype and receive the certificate after skills validation.

10. PRACTICAL ASSIGNMENTS BETWEEN CLASSES

The practical assignments are directly linked to the real client project. During the week, the learner advances the work, submits it online, receives instructor feedback and makes corrections before the next Saturday.

Registration and contacts