Introduction to Software Engineering_Nhập môn kỹ thuật phần mềm
Introduction to Software Engineering
- Tín chỉ
- 3
- Bậc
- Bachelor
- Thang điểm
- 10
- Điểm qua
- 5
Mô tả
The course includes two parts: The first part introduces the use of Generative AI (GenAI) and Large Language Models (LLMs) in modern software development. Students will learn how AI-powered tools can accelerate the software engineering process, from analyzing requirements to generating code, writing tests, debugging, and producing technical documentation. The second part provides a comprehensive introduction to modern software engineering principles, methods, and practices. The course equips students with the foundational and advanced skills needed to design, develop, test, deploy, and maintain reliable software systems. Learners explore the full software development lifecycle (SDLC), including requirements engineering, architectural and object-oriented design, software construction, quality assurance, and DevOps practices. Emphasis is placed on practical, industry-relevant techniques such as version control, automated testing, API development, and iterative development using Agile. Through a combination of theoretical concepts, hands-on exercises, and real-world case studies, the course prepares students to work effectively in software engineering teams and build scalable, maintainable, and high-quality software products.
Phân bổ thời gian
Study hour (150h) =82h online + 3h offline + 1h TE + 2h PE + 62 h self-study
Nhiệm vụ sinh viên
Student must get the certification of Software Engineering Specialization and Generative AI in Software Development course from Coursera to be accepted to the final examination
Lưu ý
1. Complete the online courses to be allowed to take Final Exam 2. Final Exam is included of Final Theory Exam (TE) & Final Practical Exam (PE): 100% 3. Students who complete all MOOCs before the course deadline will receive 1 bonus point; otherwise, no bonus point will be awarded. 4. Completion Criteria: Final TE Score >=4 & Final PE Score >=4 & FR >= 5 FR = min[10, (Final TE Score * weight of Final TE) + (Final PE Score * weight of Final PE) + bonus]