Developers: Boost your performance with AI
Satisfaction rate
4.8
Success rate
4.8
The target audience for training
- Developers,
- CISO
- Anyone in charge of IS projects.
What you will learn
At the end of the course, trainees will be able to use artificial intelligence (AI) to
a development assistant.
Training programme
- Duration: 2 days
Day 1
Day 1 - Morning: Introduction and fundamentals of AI for developers
- Understanding the role of AI in software development: uses and case studies.
- Overview of generative AI tools for developers (GitHub Copilot, ChatGPT, CodeWhisperer, etc.).
- How language models work and their limitations in a development context.
- Demonstration: simple code generation with an AI assistant.
- Interactive quiz (30 min) on LMS with group correction to validate and consolidate what has been learnt.
Day 1 - Afternoon: Integrating AI into the development workflow
- Automation of repetitive tasks (unit tests, documentation, code snippets).
- Using AI for code review and error detection.
- Optimising productivity with AI extensions in development environments.
- Practical exercise: setting up a mini-workflow with an AI assistant integrated into a real project.
- Interactive quiz (30 min) on LMS with group correction to validate and consolidate what has been learnt
Day 2
Day 2 - Morning: Cybersecurity and risks associated with generative AI
- Identify the risks associated with the use of AI in development: leakage of sensitive data,
technological dependency, errors or biases generated by AI. - Good cyber security practice in the use of AI tools.
- Confidentiality and management of organisational data.
- Practical exercise: simulating an audit of code produced by AI.
- Interactive quiz (30 min) on LMS with group correction to validate and consolidate what has been learnt.
Day 2 - Afternoon: Further study and advanced case studies
- Secure development with AI: integrating OWASP and Secure by Design recommendations.
- Case study: using AI to improve an existing application project (optimisation, refactoring, security).
- Drawing up internal guidelines for the responsible use of AI in IS projects.
- Workshop: drafting an internal charter on AI and secure development.
- Interactive quiz (30 min) on LMS with group correction to validate and consolidate what has been learnt.
Intersession: virtual classroom (2 hours, 2 weeks after the course)
- Feedback from participants: integration of AI assistants (Copilot, ChatGPT, CodeWhisperer, etc.) into their projects since the training course.
- Collaborative workshop: collective correction of AI-generated code (error detection, security flaws, optimisation).
- Practical recommendations for responsible and secure use of AI in the development workflow.
- Closing and final assessment.
- Attendance certificates are handed out and participants evaluate the course.
Trainer profile
Expert consultant-trainer in artificial intelligence, whose technical, professional and teaching skills have been rigorously assessed and validated as part of our internal selection procedures.
Teaching methods and resources
The course is based on a balanced combination of theoretical and practical approaches, guaranteeing both the acquisition of knowledge and its operational application:
- Structured theoretical input, illustrated by practical examples tailored to the participants' professional context.
- Practical exercises at each stage to help you assimilate the knowledge you have acquired.
- A case study linking the different skill blocks.
- Strong interaction between trainers and trainees, making exchanges more concrete and in correlation with trainees' expectations.
- Full educational documentation, supplied in paper or digital format.
- Course evaluation questionnaire at the end of the course, analysed by our teaching team.
- Certificate of acquired skills sent to the trainee at the end of the course.
- End-of-training certificate sent at the same time as the invoice to the company or funding organisation, confirming that the trainee has fully attended the session.
Training objectives
- Integrate artificial intelligence (AI) tools into their development workflow
- Automate certain development tasks using AI assistants
- Assessing the risks associated with the use of generative AI in a secure development context
- Applying good cyber security practices when using AI tools (sensitive data, code confidentiality).
Assessment method
- Practical exercises at every stage of the course.
- A case study linking the different skill blocks.
- Quiz at the end of each day's training.
- Self-assessment of knowledge acquired by trainees via a questionnaire
Training prerequisites
Basic knowledge of programming and application design.
- Language : French
- Level : Fundamental
- Certification body : ACG CYBERACADEMY
- Certification: No
- Accessibility : Yes
- Duration: 2 days
Important information:
Our courses are not registered with the Répertoire National des Certifications Professionnelles (RNCP), but they do comply with the requirements of the Répertoire Spécifique (RS).