Free Download AI Secure Coding Course Online
Learn how to secure AI-generated code with free video classes. Download now to explore top AI risks, secure practices, and real case studies.
AI Risk & Security – Secure Coding Overview:
This premium video course is completely free and offers expert training on secure AI code generation. You will explore the top 10 AI-generated code risks expected in 2025. The course teaches you how to use AI tools like GitHub Copilot while avoiding security pitfalls. With practical examples and expert-led guidance, this program prepares you to develop AI-driven software that remains secure, reliable, and compliant.
You will learn how to identify biases, outdated practices, and security issues in AI-generated code. Through real-world examples and guided exercises, the course explains how to evaluate AI code using essential metrics like MTTF and cyclomatic complexity. You will also explore prompt engineering, secure coding in frameworks like React, and effective ways to prevent data leaks, privacy violations, and code breaches.
This course helps you master secure AI-assisted development and avoid critical software vulnerabilities.
What You’ll Learn in AI Risk & Security – Secure Coding:
- Understand the top 10 risks in AI-generated code for 2025.
- Use GitHub Copilot securely in software development.
- Identify and address issues like bias and outdated coding practices.
- Apply secure coding principles in AI prompt engineering.
- Evaluate AI-generated code using metrics like MTTF and MTTR.
- Understand how AI language models work in development.
- Analyze secure vs. insecure AI-generated code with real examples.
- Learn security best practices using ethical AI development.
- Avoid GPL-license violations in AI-generated outputs.
- Implement React secure coding methods like CSRF protection and validation.
Course Highlights:
- AI risk coverage: Learn top security threats in AI-generated code.
- Secure practices: Apply coding standards to boost protection.
- Real case studies: See practical examples of secure and insecure AI code.
- Metric-based evaluation: Assess code quality and reliability effectively.
- React framework: Apply secure input validation and protect against XSS.
- Ethical insights: Understand compliance and licensing responsibilities.
Secure AI Coding Information:
This free video course bridges artificial intelligence with secure software development. Learners gain practical skills to build trustworthy AI-driven applications. Topics include AI architecture, prompt engineering, security evaluations, and legal compliance. Through guided exercises and expert lessons, you will learn to generate AI code that performs reliably and adheres to ethical development practices. The course focuses on tools like GPT-4 and GitHub Copilot and provides strategies to mitigate AI-related risks while accelerating development. Students from all technical levels can benefit from this beginner-friendly course, gaining insights that apply across industries including finance, healthcare, and software.
Leave a Reply
You must be logged in to post a comment.