Certificate in AI Tools for Web Developers (Basic to Advanced)

UNIT 1: AI Fundamentals for Web Development

Theory

1. Introduction to AI in web development
2. Generative AI and Large Language Models
3. Role of AI in modern web development
4. AI-assisted coding concepts
5. Introduction to AI coding assistants
6. Prompt engineering fundamentals
7. Writing effective coding prompts
8. Context, constraints and expected output
9. Understanding AI-generated code
10. Benefits and limitations of AI coding tools
11. AI hallucinations and incorrect code
12. Responsible and secure use of AI
13. Protecting API keys and sensitive information
14. Human review and code verification

Practical

1. Set up an AI coding assistant
2. Generate basic HTML using AI
3. Generate CSS layouts using AI
4. Generate JavaScript snippets
5. Ask AI to explain existing code
6. Convert a design idea into HTML/CSS
7. Create prompts for coding tasks
8. Improve AI-generated prompts
9. Debug a simple coding error using AI
10. Review and correct AI-generated code
11. Build a simple responsive webpage with AI assistance

UNIT 2: AI-Assisted Front-End Web Development

Theory

1. HTML fundamentals and semantic structure
2. CSS fundamentals and responsive design
3. JavaScript fundamentals
4. AI-assisted HTML development
5. AI-assisted CSS development
6. AI-assisted JavaScript development
7. Responsive layouts using AI
8. Component-based UI concepts
9. UI/UX design assistance with AI
10. Accessibility fundamentals
11. Browser compatibility
12. Code readability and maintainability
13. Front-end performance basics
14. Using AI for code refactoring

Practical

1. Generate a semantic HTML page using AI
2. Create a responsive CSS layout
3. Generate navigation menus
4. Create forms and form validation
5. Build responsive cards and sections
6. Generate JavaScript interactions
7. Create a mobile navigation menu
8. Build a responsive landing page
9. Ask AI to improve accessibility
10. Refactor repetitive code using AI
11. Optimize front-end code
12. Test the webpage on different screen sizes

UNIT 3: AI for JavaScript, APIs & Web Application Development

Theory

1. JavaScript programming with AI assistance
2. DOM manipulation
3. Events and event handling
4. Functions and reusable code
5. Asynchronous JavaScript
6. JSON fundamentals
7. REST API concepts
8. Fetch API
9. Working with external APIs
10. Error handling
11. Authentication concepts
12. Environment variables
13. Introduction to frameworks and libraries
14. AI-assisted debugging
15. AI-assisted code documentation

Practical

1. Generate JavaScript functions using AI
2. Manipulate webpage elements with JavaScript
3. Create interactive buttons
4. Build form validation
5. Work with JSON data
6. Connect a webpage to a sample API
7. Fetch and display API data
8. Handle API errors
9. Create a dynamic search interface
10. Ask AI to debug JavaScript
11. Refactor JavaScript code with AI
12. Generate documentation for code

UNIT 4: Advanced AI Development, Backend & Automation

Theory

1. Introduction to full-stack development
2. Front-end and back-end architecture
3. Server-side programming concepts
4. Databases and data management
5. AI-assisted backend development
6. API development
7. CRUD operations
8. Authentication and authorization concepts
9. AI-assisted database queries
10. Testing web applications with AI
11. Automated debugging
12. Code optimization
13. Git and version-control fundamentals
14. AI-assisted documentation
15. Deployment fundamentals
16. Web security and responsible AI development

Practical

1. Generate a basic backend structure using AI
2. Create a simple API
3. Create CRUD functionality
4. Connect a frontend to a backend API
5. Work with a sample database
6. Generate database queries with AI
7. Add basic validation
8. Implement basic authentication concepts
9. Use AI to identify potential security issues
10. Generate test cases
11. Debug application errors using AI
12. Refactor and optimize application code
13. Prepare the project for deployment

UNIT 5: AI-Powered Web Development Projects & Professional Workflow

Theory

1. AI-powered development workflow
2. Planning web projects with AI
3. Requirements gathering
4. Creating technical specifications with AI
5. AI-assisted UI/UX planning
6. AI-assisted coding workflow
7. AI-assisted testing and debugging
8. Performance optimization using AI
9. SEO assistance using AI
10. Accessibility auditing with AI
11. Documentation generation
12. Code review using AI
13. Deployment and maintenance
14. Version control and collaboration
15. Freelancing and client communication
16. Building a professional developer portfolio

Practical

Project 1 – AI-Assisted Website

1. Define project requirements
2. Generate project structure
3. Create sitemap
4. Plan UI/UX
5. Generate HTML
6. Generate CSS
7. Add JavaScript functionality
8. Make the website responsive
9. Test the website
10. Optimize the code

Project 2 – AI-Assisted Web Application

1. Define application requirements
2. Design user interface
3. Create frontend
4. Create backend
5. Connect API
6. Connect sample database
7. Add validation
8. Test functionality
9. Debug errors using AI
10. Optimize performance

Final Project

1. Select a real-world website/app concept
2. Prepare project requirements
3. Create sitemap and wireframe
4. Generate development plan using AI
5. Build frontend
6. Develop interactive functionality
7. Build backend/API where appropriate
8. Connect data source/database
9. Perform testing
10. Conduct security review
11. Optimize performance
12. Optimize basic SEO
13. Check accessibility
14. Generate technical documentation
15. Prepare final deployment
16. Present the completed project

3-Month Course Progression

MONTH 1 – AI & Front-End Development

Unit 1: AI Fundamentals for Web Development

Unit 2: AI-Assisted Front-End Web Development

Students learn:

• Generative AI
• AI coding assistants
• Prompt engineering
• HTML
• CSS
• JavaScript
• Responsive design
• UI/UX assistance
• Accessibility
• AI-assisted debugging

Practical Project: Build a responsive AI-assisted business/portfolio website.

MONTH 2 – JavaScript, APIs & Web Applications

Unit 3: AI for JavaScript, APIs & Web Application Development

Unit 4: Advanced AI Development, Backend & Automation

Students learn:

• JavaScript
• DOM
• APIs
• JSON
• Fetch
• Backend concepts
• Databases
• CRUD
• Authentication
• Testing
• Debugging
• Code optimization
• Security

Practical Project: Build a dynamic web application connected to an API or sample database.

MONTH 3 – Advanced AI Development Project

Unit 5: AI-Powered Web Development Projects & Professional Workflow

Students work through the complete professional workflow:

Idea → Requirements → Sitemap → UI/UX → AI Prompting → Coding → API/Backend → Database → Testing → Debugging → Security Review → Performance → SEO → Documentation → Deployment → Presentation

Professional AI Workflow

Students learn how to use AI as a development assistant, while understanding and reviewing the generated code rather than blindly copying it.

Final Assessment

Theory Examination

Students will be assessed on:

• AI fundamentals
• Generative AI
• Prompt engineering
• AI coding assistants
• HTML/CSS/JavaScript
• APIs
• Web application development
• Backend concepts
• Databases
• Testing
• Security
• Performance
• Deployment

Practical Examination

Students should demonstrate:

1. Write effective coding prompts
2. Generate and review HTML/CSS
3. Create responsive layouts
4. Generate JavaScript functionality
5. Debug code using AI
6. Connect to an API
7. Build a basic web application
8. Generate and test backend code
9. Optimize website performance
10. Document the project using AI assistance

Final Project

Create a complete AI-assisted web application or professional website containing:

• Responsive frontend
• Interactive JavaScript features
• API integration
• Backend functionality where appropriate
• Database integration where appropriate
• Form validation
• Error handling
• Basic security practices
• SEO optimization
• Accessibility checks
• Performance optimization
• Technical documentation

Student Portfolio

The final portfolio can include:

• AI-assisted landing page
• Responsive website
• JavaScript project
• API integration project
• Web application
• AI-generated development documentation
• Debugging and optimization case study
• Final full-stack/project deployment