GIT:
-create repo
-branch, local repo
-remote repo
-conflict resolution
-github plugin VS, pull, stash

AI Practice: Using AI to translate natural language into Git CLI commands, explain the “why” behind merge conflicts, and simulate safe branching strategies before executing them.

HTML, CSS, JS overview
User Interface design
UI Libraries (i.e., Bootstrap)

AI Practice: Using AI to generate semantic HTML/CSS layouts and user interactivity through JS from text descriptions, convert raw ideas into Bootstrap grid structures, and troubleshoot common CSS alignment/flexbox issues.

Overview of Angular and setting up a new project
Basic components and the Angular CLI
Module Architecture (Core/Shared/Feature)
Introduction to standalone components and modules

AI Practice: AI assistance to accelerate project bootstrapping and generating CLI commands.

Property binding, event binding, and interpolation
@if, @for, @switch modern template control flow
Component communication: @Input and @Output decorators

AI Practice: Using AI to migrate legacy *ngIf/*ngFor snippets to the modern Angular control flow syntax, and generating boilerplate for parent-child component communication.

Overview of Observables and reactive programming concepts
Observables for real-time data flow
RxJS basics: operators, streams, and error handling

AI Practice: Using AI to explain and visualize reactive data flow, suggest appropriate RxJS operators for specific data transformations (e.g., switchMap vs mergeMap), and break down complex data streams.

Signals for reactive data handling
Signals in template directives
Signals vs RxJS

AI Practice: AI-supported refactoring from legacy RxJS BehaviorSubject patterns to modern Angular Signals

Introduction to services and dependency injection in Angular
Shared services for component interaction

AI Practice: Using AI to scaffold robust service classes and identify tight coupling in service design.

Introduction to Angular’s HTTP Client, API integration patterns and
HTTP requests (GET, POST, PUT, DELETE)
Typed API responses
Observables/Signals in use with HTTP requests and handling errors

AI Practice: Preparation for AI-enabled application communication, using AI to generate strongly-typed TypeScript interfaces from raw JSON API payloads, and scaffolding HTTP services with robust error handling.

Overview of Angular forms: template-driven vs. reactive forms
Template-driven forms with basic validation
Introduction to reactive forms and FormBuilder

AI Practice: Using AI to rapidly generate FormBuilder scaffolding based on a list of required business fields.

FormGroup, FormControl, and FormArray
Custom validation and error handling
Conditional form controls and dynamic form fields
Signal Forms

AI Practice: Using AI to write complex custom validators (e.g., specific regex for passwords/IDs), generate logic for dynamic FormArrays, and adapt traditional forms to stateful Signal patterns.

Routing and nested routes
Configuration of lazy-loaded modules and route-based lazy loading in standalone apps
Route guards to secure navigation

AI Practice: Using AI to configure complex nested route objects, generate lazy-loading syntax for standalone components, and write modern functional route guards for authentication.

Resolvers
Application security: Guards, Interceptors and JWT Token

AI Practice: Using AI to scaffold modern functional HTTP Interceptors for JWT attachment, simulate security vulnerability audits in client-side code, and write modern functional resolvers.

SSR vs CSR and prerendering
Route/Server render modes

AI Practice: Using AI to troubleshoot common SSR errors (e.g., handling missing window or document objects on the server).

Build system and compilation

AI Practice: Using AI to analyze bundle sizes and suggest tree-shaking optimizations.

Hydration
Incremental Hydration

AI Practice: Using AI to design components optimized for @defer blocks and incremental hydration, improving Core Web Vitals and initial load times.

Introduction to unit testing for components and services
Reactive forms and HTTP calls testing
Best practices for structuring and maintaining an Angular project
Legacy enteprise setup: Karmine/Jasmine
Modern setup: Vitest

AI Practice: Using AI to generate comprehensive test suites in Vitest, mock complex HTTP dependencies, ensure edge-case coverage in form validation, and translate legacy Karma/Jasmine tests into modern Vitest syntax.

Introduction to docker
Dockerization of an Angular application
Differences between dev image and production image

AI Practice: Using AI to generate multi-stage Dockerfile configurations optimized for Angular, configure Nginx for serving static files efficiently, and troubleshoot common container networking issues.

Introduction to NgRx
NgRx with signals

AI Practice: Using AI to reduce NgRx boilerplate (generating Actions, Reducers, Effects), and assisting in migrating legacy NgRx state to the modern, lightweight NgRx SignalStore.

Building an AI Chat Interface with Angular
Chat-style UI structure, message thread presentation, prompt input, loading and error states
HTTP communication with backend endpoints for prompt submission and response retrieval
Reactive state handling for conversation history, response updates, and user interaction flow
Security in AI applications

AI Practice: Using AI to architect the chat UI state machine, generate robust loading/streaming text UI components, and analyze potential prompt injection vulnerabilities in the application layer.

Understanding the role of MCP in Angular, structured context in AI-assisted development, and current ecosystem limitations
AI-assisted Angular development patterns for components, services, and templates with emphasis on validation and developer responsibility
Evaluation of AI-generated Angular code, common pitfalls, best practice alignment, and architectural control

AI Practice: Using AI to query up-to-date Angular documentation, generate and refine small scoped code snippets, validate implementations against official standards, and explain reasoning behind suggested solutions.