Software Engineering

Outcome: Understand the concept and importance of structured software development processes

Outcome: Learn the sequential phases of waterfall model and its applications

Outcome: Understand how to build software in iterations and increments

Outcome: Master the risk-driven approach of spiral model development

Outcome: Learn how testing is integrated at each development phase in V-Model

Outcome: Understand rapid prototyping and quick development approaches

Outcome: Explore agile principles, values, and popular frameworks

Outcome: Analyze project characteristics to choose the most suitable SDLC model

Outcome: Understand the importance of requirements in software development

Outcome: Differentiate between functional and non-functional requirements with examples

Outcome: Master techniques like interviews, surveys, observation, and brainstorming

Outcome: Create use case diagrams and write detailed use case descriptions

Outcome: Develop complete SRS documents following IEEE standards

Outcome: Validate requirements for completeness, consistency, and feasibility

Outcome: Handle changing requirements and maintain traceability

Outcome: Use tools like JIRA, Confluence, and specialized requirements management tools

Outcome: Master SOLID principles for object-oriented design

Outcome: Understand the Gang of Four design patterns and their classification

Outcome: Implement creational patterns for object instantiation

Outcome: Apply structural patterns to compose objects and classes

Outcome: Use behavioral patterns for object communication and responsibility

Outcome: Understand architecture principles, views, and viewpoints

Outcome: Implement layered and MVC architectural patterns

Outcome: Design microservices-based applications and understand their trade-offs

Outcome: Create detailed class and sequence diagrams for system design

Outcome: Model system components and deployment infrastructure

Outcome: Apply principles from Clean Code by Robert Martin

Outcome: Follow language-specific coding standards and best practices

Outcome: Identify code smells and apply refactoring techniques

Outcome: Master Git commands, branching strategies, and workflows

Outcome: Conduct effective code reviews and provide constructive feedback

Outcome: Practice pair programming for better code quality and knowledge sharing

Outcome: Set up basic CI pipelines for automated builds and tests

Outcome: Understand testing levels, types, and their importance in SDLC

Outcome: Practice TDD approach and write effective unit tests

Outcome: Test component interactions using different integration approaches

Outcome: Validate complete systems against requirements

Outcome: Apply black-box and white-box testing techniques

Outcome: Use popular testing frameworks for different languages

Outcome: Test application performance, scalability, and security vulnerabilities

Outcome: Build maintainable automated test suites

Outcome: Understand the four values and twelve principles of agile

Outcome: Implement Scrum with proper ceremonies and artifacts

Outcome: Visualize workflow and optimize process using Kanban boards

Outcome: Apply XP practices like pair programming and continuous integration

Outcome: Create effective user stories following the INVEST criteria

Outcome: Estimate work using story points and velocity metrics

Outcome: Develop project plans with scope, schedule, and resource allocation

Outcome: Create project schedules using various techniques

Outcome: Identify, assess, and mitigate software project risks

Outcome: Estimate project costs using different models

Outcome: Lead software teams and manage team dynamics effectively

Outcome: Track progress and take corrective actions

Outcome: Use industry-standard project management software

Outcome: Distinguish between corrective, adaptive, perfective, and preventive maintenance

Outcome: Assess and manage legacy systems effectively

Outcome: Apply reengineering techniques to modernize software

Outcome: Manage software configurations and control changes

Outcome: Implement DevOps practices and automate deployment pipelines

Outcome: Design and deploy applications on cloud platforms (AWS, Azure, GCP)

Outcome: Integrate machine learning models into production software

Outcome: Build secure software with security integrated throughout SDLC

Outcome: Plan professional growth, certifications, and career advancement