MS Data Science & AI provides huge career growth. The data science industry is booming, with job opportunities projected to increase by 36 percent by 2031. As data and technology become integral to various sectors such as healthcare, digital marketing, financial services, technology, retail, media, and telecommunications, the demand for professionals who can manage and interpret this data continues to rise.
Our MS Data Science & AI programme is designed and quality assured by doctoral and post-doctoral Professors along with industry experts with huge experience. Learners study 12 modules and a Capstone Consulting Project with an industry mentor. All modules are assessed using project based assignment, and a Capstone Consulting Project and a Master Thesis towards the end of the programme with an industry mentor.
In addition, all our learners become member of our Competency Lab to develop Career, Research and Entrepreneurial Skills, along with Digital Skills in the programme. Our learners are facilitated in preparing public portfolio such as publications, or own GitHub, etc. which allows them boost their profile and promote employability.
Learning Outcomes
Competences
The learner will be able to:
PA1 Demonstrate a deep understanding of core concepts in Data Science and Artificial Intelligence, including statistical modelling, machine learning algorithms, neural networks, big data technologies, natural language processing and computer vision.
PA2 Implement programming languages commonly used in data science and AI, such as Python and R, and be proficient in using relevant libraries and frameworks.
PA3 Develop expertise in data preprocessing, cleaning, and feature engineering to prepare data for analysis and modelling.
PA4 Design and develop research-based solutions for complex problems in data science, artificial intelligence and machine learning industry through appropriate consideration for the public health, safety, cultural, societal, and environmental concerns
1st working day of every month
Day 20th of every month
180 ECTS Credits
Bachelors Degree, Level 6
27 - 36 Months
15-40 Hours per week
English
Asynchronous, Live Master Camps
Students will discover the concepts and gain expertise in the usage and applications of algorithms of Data Science and Artificial Intelligence. They will have abundant opportunities to plunge into advanced concepts. Through hands-on projects, students will gain experience on the concepts behind search algorithms, clustering, classification, optimization, reinforcement learning and other topics such as deep learning, computer vision, natural language processing techniques and incorporate the learning in Python.
This programme would enable students to embrace the concepts of DS and AI and understand their extension to its application. Students will work on projects involving AI in healthcare, education, finance, manufacturing sectors etc. Meticulously designed curriculum suitable to the industry needs with a high focus on practical applications.
We follows continuous and end of the module assessment. Continuous assessment is conducted within various units studied by the learner, and counts towards the final grades, the weightage of continuous assessment is 40%. The nature of continuous assessment is normally multiple choice questions.
End of the module assessment is the final assessment, consisting of 60% weightage. The nature of final assessment is the report submission. The report can be a project, analysis, case study, research paper, etc.
We also integrate formative assessment which does not contribute to the final grade, rather helps in peer to peer learning and reflecting on the concepts used.
Grading system can be accessed via Quality Policies in Download section
Our strategic accreditation allows every learner to earn ECTS credits for every module they study. This allows students to take deferrals, exits and re-join studies and use same ECTS credits for an advanced entry into the programme.
Ages 19 – 30
Age 31 – 65
- Data Analyst
- Natural Language Processing Engineer
- Research Scholar
- Computer Vision Engineer
- Data Scientist
- Machine Learning Engineer
- AI Engineer
- Software Engineer
Programme Structure |
||
|---|---|---|
| Module 1: Statistics for Data Science (6 ECTS, 150 Hours) | ||
| Module 2: Mathematics for Data Science (6 ECTS, 150 Hours) | ||
| Module 3: Programming for Analytics using Python (6 ECTS, 150 Hours) | ||
| Module 4: Data Visualization and Storytelling with Tableau (6 ECTS, 150 Hours) | ||
| Module 5: Artificial Intelligence and Machine Learning (6 ECTS, 150 Hours) | ||
| Module 6: Machine Learning Methods using Python (6 ECTS, 150 Hours) | ||
| Module 7: Convolutional and Recurrent Neural Networks (6 ECTS, 150 Hours) | ||
| Module 8: Computer Vision and Image Recognition (6 ECTS, 150 Hours) | ||
| Module 9: Natural Language Processing (6 ECTS, 150 Hours) | ||
| Module 10: Big Data and NoSQL (6 ECTS, 150 Hours) | ||
| Module 11: Data Warehousing and management (6 ECTS, 150 Hours) | ||
| Module 12: Research Methods (6 ECTS, 150 Hours) | ||
| Module 13: Capstone Consulting Project (18 ECTS, 450 Hours) | ||
Programmes are subject to periodic review. Changes may be implemented to align with academic advancements, student feedback, or industry needs. The institution reserves the right to make modifications in the best interest of academic integrity and learner success.
For more details or admissions contact now!
Andrew Barrow
Head of Admission Department