Master of Technology in Software Engineering (Top Up)
Master of Technology in Software Engineering (Top Up)
18 Months Part-time
Software Engineering
Master’s Degree
Universidad Catolica De Murcia (UCAM)
Course Overview
The “Master of Technology in Software Engineering” program offers an immersive educational experience, combining rigorous academic training with practical exposure. Key modules include UI & UX, where learners focus on design thinking, advanced prototyping techniques, and human-centric design to create intuitive and effective interfaces.
This educational journey equips participants to become versatile software engineers, capable of tackling complex challenges, driving innovation, and leading technological advancements.
Recognize UI/UX principles and develop customer-centric, and data-driven applications
Articulate the use of design patterns, frameworks, and testing methods to ensure that the developed applications meet high standards of quality and reliability.
Exemplify advanced AI concepts, such as Neural Networks, CNNs, RNNs, and techniques for optimizing model efficiency.
Choose suitable tools, techniques, design patterns, frameworks, and software methodologies to develop robust and efϐicient applications.
Master these tech tools
E-Learning
80 hours
80 hours
Projects/Assignments
120 hours
120 hours
Flipped Class/Mentoring
40 hours
40 hours
Additional Practice
-hours
-hours
Assessment
-hours
-hours
Prerequisites
Target Audience
Candidates must have a minimum of a second-class bachelor’s degree from a recognized university or is a Polytechnic Diploma holders in STEM with minimum 5 years of relevant working experience. Those with a recognized professional qualification and relevant work experience, and mature candidates with a minimum of 8 years of relevant work experience will be considered on a case-by-case basis.
Admission Prerequisite
Academic Qualification:
IELTS 6.5 (with no elements lower than 5.5) or its equivalent
Minimum second-class bachelor’s degree in any field from the recognized University
- Non-graduates with appropriate professional qualifications will be considered on a case-to-case basis by the University
- Polytechnic Diploma in STEM with relevant experience will be considered on a case-to-case basis by the University
- Matured candidates with a minimum of 8 years of relevant experience will be considered on a case-to-case basis
IELTS 6.5 (with no elements lower than 5.5) or its equivalent
Graduation Requirements
Minimum attendance of 75% in all the sessions of each module
Minimum pass grade in the summative assessment of each module
Minimum pass grade in the summative assessment of each module
Module Summary
Module 1
Module 2
Module 3
Module 4
Module 1
UX UI Design
Session Plan Details
Gain expertise in UI Frameworks with design thinking, UI heuristics, prototyping, and usability testing. Master accessibility standards and high-fidelity prototyping. Develop skills in UX research, user interviews, and surveys. Showcase proficiency in wireframing, prototyping, and usability testing through hands-on projects.
What You’ll Learn
- Persona creation
- Information Architecture and Interaction Design
- Visual Design and Branding
- Prototyping
- Usability Testing & Documentation
Module 2
Machine Learning
Session Plan Details
Gain a solid foundation in machine learning concepts and techniques. Explore supervised learning for classification and regression, and unsupervised learning for clustering and anomaly detection. Enhance model performance with feature selection and hyperparameter tuning. Learn to implement machine learning pipelines for data preprocessing, training, and evaluation.
What You’ll Learn
- Introduction To Machine Learning
- Supervised Machine Learning
- Unsupervised Machine Learning
- Improve Model Performance
- Hyperparameter Tuning
Module 3
Deep Learning
Session Plan Details
Acquire essential knowledge and skills in AI and Deep Learning. Learn about Artificial Neural Networks, CNNs, and RNNs, and optimize model performance. Gain hands-on experience deploying Deep Learning models for real-world applications, particularly in image recognition using CNNs. Develop proficiency in designing and fine-tuning Neural Networks for image processing tasks, preparing to solve complex AI and Computer Vision challenges.
What You’ll Learn
- Introduction to AI and Deep Learning
- Artificial Neural Networks
- Convolutional Neural Networks
- Recurrent Neural Networks
- Techniques for Optimizing Model Performance
Module 4
Reinforcement Learning
Session Plan Details
Acquire comprehensive knowledge and practical skills in Reinforcement Learning through focused instructional units. Master fundamental concepts and explore algorithms and real-world applications. Learn about exploration-exploitation trade-offs and problem-solving techniques like Markov Decision Processes and Q-learning. Gain hands-on experience through projects spanning different units, mastering deployment of RL methodologies across diverse scenarios.
What You’ll Learn
- Introduction to Reinforcement Learning
- Types and Applications of Reinforcement Learning
- Bandits and Exploration Strategies
- Solving the Reinforcement Learning Problem
- Advanced Reinforcement Learning Techniques
Module 1
Module 2
Module 3
Module 4
Module 1
UX UI Design
Session Plan Details
Gain expertise in UI Frameworks with design thinking, UI heuristics, prototyping, and usability testing. Master accessibility standards and high-fidelity prototyping. Develop skills in UX research, user interviews, and surveys. Showcase proficiency in wireframing, prototyping, and usability testing through hands-on projects.
What You’ll Learn
- Persona creation
- Information Architecture and Interaction Design
- Visual Design and Branding
- Prototyping
- Usability Testing & Documentation
Module 2
Machine Learning
Session Plan Details
Gain a solid foundation in machine learning concepts and techniques. Explore supervised learning for classification and regression, and unsupervised learning for clustering and anomaly detection. Enhance model performance with feature selection and hyperparameter tuning. Learn to implement machine learning pipelines for data preprocessing, training, and evaluation.
What You’ll Learn
- Introduction To Machine Learning
- Supervised Machine Learning
- Unsupervised Machine Learning
- Improve Model Performance
- Hyperparameter Tuning
Module 3
Deep Learning
Session Plan Details
Acquire essential knowledge and skills in AI and Deep Learning. Learn about Artificial Neural Networks, CNNs, and RNNs, and optimize model performance. Gain hands-on experience deploying Deep Learning models for real-world applications, particularly in image recognition using CNNs. Develop proficiency in designing and fine-tuning Neural Networks for image processing tasks, preparing to solve complex AI and Computer Vision challenges.
What You’ll Learn
- Introduction to AI and Deep Learning
- Artificial Neural Networks
- Convolutional Neural Networks
- Recurrent Neural Networks
- Techniques for Optimizing Model Performance
Module 4
Reinforcement Learning
Session Plan Details
Acquire comprehensive knowledge and practical skills in Reinforcement Learning through focused instructional units. Master fundamental concepts and explore algorithms and real-world applications. Learn about exploration-exploitation trade-offs and problem-solving techniques like Markov Decision Processes and Q-learning. Gain hands-on experience through projects spanning different units, mastering deployment of RL methodologies across diverse scenarios.
What You’ll Learn
- Introduction to Reinforcement Learning
- Types and Applications of Reinforcement Learning
- Bandits and Exploration Strategies
- Solving the Reinforcement Learning Problem
- Advanced Reinforcement Learning Techniques
Flexible Learning Pathway
After meeting the graduation requirements, the candidate will be awarded a top-up degree.
Professional Certificate in AI Application Development
Professional Certificate
Professional Diploma in Full Stack Software Development
Professional Diploma
Master of Technology in Software Engineering (Top Up)
Master’s Degree
Certification(s)
Certification(s) Earned
- Master of Technology in Software Engineering awarded by Universidad Catolica De Murcia (UCAM), Spain
Pricing
Course Fee
USD 2,500
Payment Plan
Tuition fee is available for full payment and installments before the start of class. For more details Contact Us.
| Master of Technology in Software Engineering (Top Up) | Installment Plan | Tuition Fees |
|---|---|---|
| Month 1 | USD 1,050 | |
| Month 2-4 | USD 150 /month | |
| Month 5 | USD 1,050 | |
| Month 6-8 | USD 150 /month | |
| Total | 8 installments | USD 3,000 |
About Universidad Catolica De Murcia
Founded in 1996, Universidad Católica de Murcia (UCAM) stands as a prestigious private university located in Murcia, Spain. Dedicated to academic excellence and innovation, UCAM offers a wide range of undergraduate, postgraduate, and doctoral programs across various fields including health sciences, sports, business, humanities, and technology. The university prides itself on its commitment to personalized education, integrating theoretical knowledge with practical skills through modern teaching methodologies and state-of-the-art facilities. UCAM’s programs are designed to prepare students for successful careers in their chosen fields, fostering critical thinking, creativity, and a global perspective.
UCAM places a strong emphasis on research and innovation, collaborating with industry and international institutions to address contemporary challenges. With a diverse and multicultural environment, UCAM welcomes students from around the world, providing them with opportunities to engage in cultural exchange and broaden their perspectives. Through its strong network of partnerships and a commitment to holistic development, UCAM prepares graduates to make meaningful contributions to society and thrive in a competitive global landscape.
Learn more ucam.edu
