AI5 PROFESSIONAL CERTIFICATE · BY TGC INDIA · UPDATED AUGUST 2026
Secure Coding with GitHub Copilot, Snyk & CodeQL
Use AI-assisted development with security scanning, code review and remediation workflows that keep the developer accountable.
Online + OfflineWeekdays + WeekendsRegular + Fast Track
22+years in training
20,000+learners across TGC
5classroom locations
Live onlinejoin from anywhere
NEXT START OPTIONS
Choose a live batch.
COURSE OVERVIEW
What this course
is built to do.
Combine AI-assisted coding with static analysis, dependency checks, security review and documented remediation using GitHub Copilot, Snyk and CodeQL.
Each module combines a live trainer demonstration, guided lab, assignment and review before the next stage.
CONNECTED CAREER DIRECTIONS
Secure Software DeveloperApplication Security AssociateDevSecOps EngineerAI-Assisted Code Reviewer
IS THIS COURSE RIGHT FOR YOU?
Choose it for the right reason.
You already write or review software
You want AI coding speed with security gates
You need practical Snyk, CodeQL and dependency-remediation experience
YOUR LEARNING ARC
From guided foundation to finished work.
Threat model
Map assets, trust boundaries and likely misuse.
Build
Use Copilot with secure coding rules and review discipline.
Scan
Run Snyk, CodeQL and dependency checks.
Remediate
Fix findings, retest and document a secure release.
INDUSTRY TASKS
Practise the work, not only the tool.
- Threat-model a small web application
- Trace and repair a CodeQL or Snyk finding
- Create a pull-request security gate and remediation report
PRO
LED
LED
YOUR TRAINING TEAM
Learn from experienced working professionals.
Live demonstrations, guided practice and direct project feedback are part of the course. Trainers update examples and tool coverage as professional practice changes.
WHAT YOU WILL BE ABLE TO DO
Course outcomes
01
Threat-model an application change
A documented asset, boundary and misuse-case analysis.
02
Use Copilot under security controls
An explainable feature branch with reviewed AI-assisted changes.
03
Find and repair code risk
Validated Snyk and CodeQL findings with tested fixes.
04
Run a secure release gate
A CI-backed release dossier with exceptions and ownership recorded.
TAKE THE NEXT STEP
Need fees, syllabus or the right batch?
An AI5 Academy advisor can help you compare mode, schedule and starting level.
DETAILED COURSE FLOW
5 learning modules
Use AI coding assistance inside a defensive development process built around threat models, secure design, automated scanning, human review and verified remediation.
Threat modelling and secure development rules
Define what must be protected and how security will be checked before code is generated.
CORE TOPICS
- Assets, actors, trust boundaries and attack paths
- OWASP risks and misuse cases
- Secure coding standards and repository instructions
- Secrets, dependencies and environment separation
GUIDED PRACTICE
Threat-model a small web application and turn the findings into coding and review rules.
MODULE DELIVERABLE
Application threat model and security checklist
Controlled coding with GitHub Copilot
Use AI assistance for small, explainable changes without accepting unsafe defaults.
CORE TOPICS
- Context selection and secure prompt patterns
- Authentication, validation and authorisation code
- Cryptography and secrets management boundaries
- Diff review, provenance and developer accountability
GUIDED PRACTICE
Implement a feature with Copilot, explain every change and reject unsafe suggestions.
MODULE DELIVERABLE
Reviewed secure feature branch
Snyk and dependency security
Detect vulnerable packages, configuration issues and code findings, then judge their real impact.
CORE TOPICS
- Software composition analysis and dependency trees
- Snyk Code and configuration scanning
- Severity, reachability and exploit context
- Upgrades, compensating controls and false positives
GUIDED PRACTICE
Scan a sample project, rank findings and repair the highest-risk dependency or code issue.
MODULE DELIVERABLE
Snyk findings and remediation report
CodeQL and security review
Use query-based analysis to trace risky data flow and support a disciplined pull-request review.
CORE TOPICS
- CodeQL databases, queries and data flow
- Sources, sinks, sanitisation and taint tracking
- GitHub code scanning and pull-request findings
- Custom query concepts and result validation
GUIDED PRACTICE
Trace one injection or data-flow finding from source to sink and verify the repair.
MODULE DELIVERABLE
CodeQL analysis and fixed pull request
Secure release capstone
Combine automated gates and manual checks into a repeatable release decision.
CORE TOPICS
- Unit, integration and abuse-case tests
- CI scanning and branch protection
- Security exceptions and remediation ownership
- Release evidence, monitoring and incident feedback
GUIDED PRACTICE
Build a small application change, run the complete security gate and present the release or rejection decision.
MODULE DELIVERABLE
Secure coding capstone and release dossier
HOW THE TRAINING WORKS
Learn it. Apply it. Get it reviewed. Improve it.
Every important skill moves through explanation, demonstration, guided use and independent application. Trainer feedback is used to revise the work before it becomes part of the final portfolio.
Concept briefing
The trainer explains the principle, use case, limitations and the quality standard expected.
Live demonstration
A complete task is demonstrated while the trainer explains decisions, checks and common mistakes.
Guided lab
Learners repeat the method with support, ask questions and correct problems during the session.
Applied assignment
The same method is used on a different brief so the learner must make independent decisions.
Review and revision
Work is checked against a rubric, revised after feedback and prepared for project presentation.
PROGRESS IS CHECKED THROUGHClass exercisesModule deliverablesProject reviewsFinal capstone presentation
PORTFOLIO WORK
Projects you can show
Guided practice brief
Plan, produce, test and present a finished piece with trainer feedback.
Individual application
Plan, produce, test and present a finished piece with trainer feedback.
Workflow build
Plan, produce, test and present a finished piece with trainer feedback.
Industry-style assignment
Plan, produce, test and present a finished piece with trainer feedback.
Quality review
Plan, produce, test and present a finished piece with trainer feedback.
Final capstone
Plan, produce, test and present a finished piece with trainer feedback.
TAKE THE NEXT STEP
Need fees, syllabus or the right batch?
An AI5 Academy advisor can help you compare mode, schedule and starting level.
TOOLS COVERED
GitHub CopilotSnykCodeQLDependabot
Tool coverage may be updated when the industry changes. Core methods remain part of the course.COMMON QUESTIONS
Before you apply
Which language is used?
Exercises can use JavaScript or Python, with scanning examples that transfer to other supported languages.
＋Does AI-generated code remain safe automatically?
No. Every change is reviewed, scanned and tested against the threat model.
＋Is this a penetration-testing course?
No. It focuses on defensive software development, code analysis and remediation.
＋Do I need coding experience?
No, unless the course level says otherwise. Your advisor will check the right starting level.
＋Are classes live or recorded?
Classes are trainer-led in the classroom or live online. Recordings may support revision but do not replace class.
＋Will I receive a certificate?
Yes. Course completion requires attendance, assignments and the final project.
＋Can working professionals join?
Yes. Weekday, weekend and selected fast-track schedules are available.
＋NEXT BATCH
Choose your course.
Choose your schedule.
Online or offline. Weekdays or weekends. Regular or fast track. Speak with an AI5 Academy advisor about the right starting level.