Full-Stack Python Development with AI and Cloud

• Module 3: Web Development Fundamentals and Internet Architecture

Understand browsers, servers, DNS, domains, hosting, HTTP/HTTPS, request-response cycles, status codes, cookies, sessions, browser storage, web application architecture, frontend/backend separation, API-driven applications, project directory structures, browser developer tools, Git collaboration, Jira boards, user stories, acceptance criteria and product requirements.

• Module 4: HTML5, CSS3, Responsive Design and Accessibility

Build semantic websites using HTML5, forms, tables, multimedia, metadata and accessible structures. Learn CSS selectors, cascade, box model, positioning, Flexbox, Grid, variables, media queries, mobile-first design, responsive images, animations, Bootstrap awareness, Tailwind CSS fundamentals, cross-browser testing, keyboard navigation, colour contrast and accessibility standards.

• Module 5: Modern JavaScript, DOM and Asynchronous Web Programming

Learn JavaScript ES6+, scope, functions, arrays, objects, modules, destructuring, spread syntax, array methods, DOM manipulation, events, form validation, local storage, Fetch API, promises, async/await, JSON, browser errors, debugging, API consumption, loading states, retry concepts and secure handling of browser-side data.

• Module 6: Figma UI/UX, Product Design and Design Systems

Understand UI and UX fundamentals, user personas, user journeys, information architecture, wireframes, low-fidelity and high-fidelity designs, interactive prototypes, reusable components, design systems, typography, colour systems, spacing, responsive layouts, usability testing, developer handoff and converting Figma designs into HTML/CSS/JavaScript interfaces.

• Module 7: Apache Web Server, Domains, HTTPS and Production Hosting

Install and configure Apache HTTP Server, understand configuration files, document roots, permissions, virtual hosts, domain mapping, DNS records, server logs, MIME types, redirects, URL rewriting, compression, caching headers, basic reverse-proxy concepts, SSL/TLS certificates, HTTPS, firewall fundamentals, secure server configuration, static-site deployment, backups and common deployment troubleshooting.

• Module 8: PostgreSQL, SQL and Relational Database Design

Learn databases, schemas, tables, data types, keys, constraints, CRUD operations, filtering, sorting, aggregation, GROUP BY, HAVING, joins, subqueries, one-to-one, one-to-many and many-to-many relationships, database normalization, Entity Relationship Diagrams, data validation and realistic sample-data generation.

• Module 9: Advanced PostgreSQL, Transactions, Performance, and Data Security

Learn transactions, ACID properties, isolation concepts, indexes, composite indexes, query plans, query optimization, views, functions, pagination strategies, full-text search concepts, database users, roles, permissions, connection pooling concepts, backups, restores, migrations, audit requirements, personally identifiable information and secure database configuration.

• Module 10: MongoDB and Document-Oriented Data Modelling

 Understand NoSQL concepts, documents, collections, BSON, embedding versus referencing, schema validation, CRUD operations, query operators, indexes, aggregation pipelines, text search, transaction awareness, MongoDB security, backup concepts, Python integration and correct decisions about using PostgreSQL, MongoDB or both.

• Module 11: Django Fundamentals, MVT Architecture and Project Organization

Learn Django installation, projects, applications, settings, URL routing, requests, responses, views, templates, template inheritance, static files, media files, middleware concepts, environment variables, secrets, development and production settings, Django admin, management commands, reusable applications, WSGI/ASGI concepts and professional project organization.

• Module 12: Django ORM, Forms, Business Logic and Database-Driven Development

Create models, relationships, migrations, QuerySets, custom managers, model methods, forms, ModelForms, custom validation, transactions, signals awareness, CRUD operations, generic class-based views, pagination, search, filtering, file uploads, query optimization, database constraints and test-data creation.

• Module 13: Django Authentication, Authorization and Enterprise Workflows

Implement custom user models, registration, login, logout, password reset, profiles, groups, permissions, role-based access control, object-level access concepts, secure sessions, protected views, multiple dashboards, approval workflows, email notifications, audit trails, soft deletion, data-retention concepts and administrative operations.

• Module 14: Django REST Framework and Production API Development

Build REST APIs using serializers, ModelSerializer, API views, generic views, ViewSets, routers, nested relationships, validation, pagination, filters, search, ordering, error formats, API documentation, OpenAPI, Swagger, JWT fundamentals, permissions, throttling, API versioning concepts and automated API testing.

• Module 15: Flask Applications, Microservices, Background Work and Integration Services

Learn Flask routing, application factories, blueprints, configuration, contexts, request validation, response schemas, SQLAlchemy, migrations, JWT authentication, error handling, logging, testing, webhooks, external API clients, health endpoints, timeouts, retries, idempotency, Redis, caching, Celery or background-task concepts and Django-to-Flask service communication.

• Module 16: React.js and TypeScript Fundamentals
 

Learn TypeScript types, interfaces, aliases, unions, functions, generics fundamentals and type-safe API structures. Learn React components, JSX, props, state, events, conditional rendering, lists, forms, controlled components, composition, useState, useEffect, reusable components, Tailwind integration and professional frontend organization.

• Module 17: Advanced React, Routing, State Management and Testing
 

Learn React Router, nested and protected routes, custom hooks, Context API, state-management patterns, form libraries, schema validation, API-service layers, authentication state, token refresh, search, filtering, pagination, file uploads, error boundaries, lazy loading, accessibility, performance, component testing, API mocking and React Testing Library.

• Module 18: Next.js App Router, Rendering, Performance and Modern Web Delivery
 

Learn Next.js App Router, layouts, pages, nested routes, dynamic routes, loading and error interfaces, Server and Client Components, server-side rendering, static generation, incremental rendering concepts, route handlers, middleware, metadata, image optimization, caching and revalidation, environment variables, TypeScript, authentication integration, SEO, testing and deployment. Use Next.js primarily as the frontend and presentation framework while Django and Flask remain the principal backend services.

• Module 19: AI, Machine Learning, Mathematics, and Data Foundations

Understand Artificial Intelligence, machine learning, deep learning, supervised learning, unsupervised learning, reinforcement-learning awareness, classification, regression, clustering, training versus inference, features, labels, datasets and generalization. Learn essential linear algebra, vectors, matrices, probability, statistics, derivatives, gradients, loss functions, data preprocessing, train-validation-test splits, data leakage, class imbalance, evaluation metrics, baseline models and scikit-learn fundamentals.

• Module 20: PyTorch Fundamentals and Neural Networks from First Principles

Learn PyTorch installation, notebooks, Google Colab, CPU/GPU selection, tensors, tensor operations, broadcasting, shapes, devices, automatic differentiation, computational graphs, nn.Module, layers, activations, forward propagation, loss functions, optimizers, backpropagation, learning rates, training loops, validation loops, Dataset, DataLoader, batching, shuffling, model saving, model loading, checkpoints and reproducible experiments.

Students will build neural networks first with basic tensor operations and then through reusable PyTorch modules so that they understand what happens inside a training process.

• Module 21: Computer Vision, CNNs and Transfer Learning with PyTorch

Learn image tensors, preprocessing, normalization, image datasets, TorchVision, fully connected image models, convolution, filters, feature maps, pooling, CNN architectures, multiclass classification, augmentation, dropout, batch normalization, early stopping, overfitting, confusion matrices, precision, recall, F1 score, transfer learning, pretrained models, fine-tuning, custom image datasets and explainability concepts.

• Module 22: NLP, Embeddings, RNNs, LSTMs and Sequence Modelling

Learn text cleaning, tokenization, vocabulary construction, sequence encoding, padding, attention masks, word embeddings, pretrained embeddings, text classification, sentiment analysis, RNNs, GRUs, LSTMs, bidirectional models, sequence generation, time-series fundamentals, windowed datasets, forecasting, sequence evaluation and common limitations of recurrent models.

• Module 23: Transformers, Generative AI, Fine-Tuning and RAG

Understand attention, self-attention, encoder, decoder and encoder-decoder architectures. Use Hugging Face models, tokenizers and pipelines. Learn text classification, generation, summarization, question answering, external AI APIs, prompt engineering, structured output, function calling, embeddings, semantic search, vector databases, document chunking, Retrieval-Augmented Generation, fine-tuning concepts, parameter-efficient fine-tuning, prompt tuning, LoRA concepts, local-model usage and responsible Generative AI integration.

• Module 24: Custom Neural-Network Research, Evaluation, Deployment and MLOps

Learn how to define an AI problem, review related work, read research papers, create baselines, design custom nn.Module architectures, create custom layers, combine CNN, recurrent and attention components, choose losses and metrics, run controlled experiments, tune hyperparameters, perform ablation studies, compare models, detect overfitting, track experiments, manage datasets and model versions, reproduce results and write research reports.

Learn model inference, preprocessing and post-processing pipelines, batch and real-time predictions, Flask-based model APIs, Django integration, model serialization, model export awareness, Docker deployment, model health checks, prediction logging, model drift concepts, monitoring, rollback, security, privacy and human review.

• Module 25: Professional REST API Architecture and Integration Design

Learn REST constraints, resources, endpoint naming, HTTP methods, status codes, headers, request and response schemas, validation, pagination, filtering, sorting, searching, API versioning, idempotency, partial updates, bulk operations, file-transfer APIs, OpenAPI, Swagger, API contracts, Postman collections, webhooks, retries, timeouts, service-to-service communication, API gateways, caching, backward compatibility and API lifecycle management.

• Module 26: Authentication, JWT, OAuth 2.0 and Fine-Grained Authorization

Understand sessions, cookies, tokens, JWT access and refresh tokens, token rotation, logout and revocation concepts, OAuth 2.0 flows, OpenID Connect concepts, Google/GitHub sign-in, scopes, claims, role-based access control, attribute-based concepts, object-level permissions, multi-tenant authorization, API keys, service credentials, CORS, CSRF, secure cookies, rate limiting, throttling and authentication testing.

• Module 27: Web, API, Supply-Chain and AI Application Security

Study secure software-development lifecycle, threat modelling, trust boundaries, attack surfaces and current OWASP risks. Cover broken access control, security misconfiguration, software-supply-chain failures, cryptographic failures, injection, insecure design, authentication failures, integrity failures, logging and alerting failures and mishandling of exceptional conditions.

Practise SQL injection prevention, XSS prevention, CSRF protection, IDOR prevention, SSRF awareness, mass-assignment prevention, secure file uploads, secret scanning, dependency scanning, password security, encryption concepts, HTTPS, security headers, Content Security Policy, audit logs and safe error messages. Learn prompt injection, indirect prompt injection, AI data leakage, excessive agency, insecure model output handling, AI cost abuse and secure AI tool execution.

• Module 28: Mobile Application Development with React Native

Learn React Native project setup, components, styling, responsive mobile layouts, navigation, screens, forms, state management, API integration, authentication, secure token storage concepts, AsyncStorage, SQLite fundamentals, camera and file access awareness, permissions, push-notification concepts, error handling, offline behaviour, debugging, testing fundamentals and Android/iOS build concepts.

• Module 29: Desktop Application Development with Electron.js

Learn Electron architecture, main and renderer processes, preload scripts, inter-process communication, windows, menus, dialogs, notifications, local files, SQLite, API consumption, authentication, secure context isolation, safe IPC, application updates awareness, debugging and packaging for Windows, Linux and macOS.

• Module 30: Full-Stack Testing, Debugging and Software Quality Engineering

Learn the testing pyramid, unit tests, integration tests, API tests, component tests, end-to-end testing concepts, pytest, pytest-django, Flask test clients, React Testing Library, Vitest/Jest concepts, Playwright fundamentals, Postman automation, fixtures, factories, mocking, test isolation, regression tests, coverage, logging, debugging, profiling, static analysis, formatting, type checking, pull-request quality gates, database-query testing and AI-model evaluation tests.

• Module 31: DevOps, Linux Operations, Cloud Fundamentals and Infrastructure Automation

Understand DevOps culture, development, staging and production environments, Linux users, permissions, processes, systemd awareness, networking, DNS, ports, firewalls, reverse proxies, cloud models, regions, availability zones, AWS IAM, EC2, S3, RDS, DigitalOcean droplets, managed databases, object storage, boto3, infrastructure automation, Terraform fundamentals, budgets, cost controls, backup strategies and disaster-recovery fundamentals.

• Module 32: Docker, Docker Compose and Kubernetes Fundamentals

Learn images, containers, Dockerfiles, layers, build contexts, multi-stage builds, volumes, networks, environment variables, secrets, health checks, non-root containers, image scanning, registries and Docker Compose. Containerize React/Next.js, Django, Flask, PostgreSQL, MongoDB where justified, Redis and background workers. Learn Kubernetes architecture, Pods, Deployments, Services, ConfigMaps, Secrets, Ingress, storage, probes, scaling, rolling updates and basic cluster troubleshooting.

• Module 33: GitHub Actions, Cloud Deployment, Observability and Release Engineering

Learn CI/CD workflows, triggers, jobs, steps, runners, caching, secrets, automated tests, linting, type checks, security scans, Docker builds, image registries, staging and production deployments, approvals, migrations, release versions, changelogs and rollbacks. Deploy applications to AWS or DigitalOcean using Nginx, Gunicorn and suitable Python servers. Configure domains, HTTPS, logs, metrics, health checks, uptime monitoring, error tracking, alerts, backups, restore tests, runbooks, incident response and cloud-cost reports.

• Module 34: Capstone Product Engineering and System Design

Finalize functional and non-functional requirements, architecture, user roles, database design, API contracts, AI architecture, mobile and desktop scope, security requirements, testing strategy, cloud architecture and project plan. Learn modular monoliths, microservices, API gateways, caching, queues, event-driven concepts, horizontal and vertical scaling, load balancing, database scaling concepts, failure handling and cost-aware design.

• Module 35: Production Readiness, Documentation and Final Release

Complete remaining features, tests, security checks, performance reviews, AI evaluation, deployment workflows, logs, monitoring, backups and recovery instructions. Prepare README files, architecture diagrams, ER diagrams, API documentation, model cards, AI evaluation reports, security reports, user guides, administrator guides, deployment guides, runbooks, release notes and demonstration videos.

• Module 36: Portfolio, Technical Interviews and Placement Readiness

Prepare professional résumés, LinkedIn profiles, GitHub profiles, and project portfolios. Conduct Python, JavaScript, TypeScript, React, Next.js, Django, Flask, PostgreSQL, MongoDB, REST API, security, PyTorch, AI, Docker, Kubernetes, AWS and system-design interviews. Include debugging rounds, live coding, DSA tests, project viva, HR interviews, group discussions, workplace communication, and job-application strategy.