Post-Graduate Certificate in Data Science allows you to lay down foundation in furhering your data science career. If Data Science is new to you and before commiting to full degree, you wish to explore its foundation, then this is the right place for you to start.
This Certificate will teach you 5 extensive modules that enables you going forward to oursue advanced Data Science & AI modules.
Needless to mention on huge penetration of Data Science in all fields, and this Certificate can be a great start.
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.
“EU Global Post Graduate Certificate in Data Science & AI focuses on setting up foundation for studying further Data Science Courses. This Certificate arouses your interest in delving deeper into the Data Science advanced modules.
Post completing this Certificate, the learners can advance their study by enrolling into the higher programme, such as Diploma and Degree in MS Data Science & AI.”
| 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 |
| PA5 | Design and implement machine learning models for various applications, such as classification, regression, clustering, and recommendation systems |
| PA6 | Utilise tools like Matplotlib, Seaborn, and Tableau to create compelling visualisations that aid in decision-making processes. |
| PA7 | Apply NLP and computer vision techniques to process and analyse human language data, image recognition, object detection, and image generation tasks. |
| PA8 | Apply theoretical knowledge and work on capstone projects that showcase the ability to solve complex problems using data science and AI methodologies. |
Students pursuing MS Data Science & AI/ 90 ECTS have to complete all thirteen modules including the Capstone Consulting Project.
Students pursuing only top-up will have to complete Research Methods, Statistics for Data Science and Capstone Consulting Project. Top-up Students may have to study additional modules if not recognised at the time of entry. Please consult your admissions team.
Students pursuing Post-Graduate Diploma in Data Science & Artificial Intelligence/ 60 ECTS will have to complete all modules, except Research Methods and Capstone Consulting Projects.
| Module/Unit Title | Compulsory (C) or Elective (E) | ECTS (Figures must be whole integers and with a value of at least 1 ECTS | MQF Level of each module |
|---|---|---|---|
| Statistics for Data Science | C | 6 | 7 |
| Mathematics for Data Science | C | 6 | 7 |
| Programming for analytics using Python | C | 6 | 7 |
| Data Virtualization and storytelling with tableau | C | 6 | 7 |
| Artificial Intelligence and Machine Learning | C | 6 | 7 |
| Machine Learning Methods using Python | C | 6 | 7 |
| Convolution and Recurrent Neural Networks | C | 6 | 7 |
| Computer Vision and Image Recognition | C | 6 | 7 |
| Natural Language Processing | C | 6 | 7 |
| Big Data and NoSQL | C | 6 | 7 |
| Data Warehousing and management | C | 6 | 7 |
| Research Methods | C | 6 | 7 |
| Capstone Consulting Projects | C | 18 | 7 |
Sr. No. MS in Data Science & AI - revised Program Structure ECTS
1 Statistics for Data Science 6
2 Mathematics for Data Science 6
3 Programming for analytics using Python 6
4 Data Virtualization and storytelling with tableau 6
5 Artificial Intelligence and Machine Learning 6
6 Machine Learning Methods using Python 6
7 Convolution and Recurrent Neural Networks 6
8 Computer Vision and Image Recognition 6
Sr. No. MS in Data Science & AI - revised Program Structure ECTS
1 Statistics for Data Science 6
2 Mathematics for Data Science 6
3 Programming for analytics using Python 6
4 Data Virtualization and storytelling with tableau 6
5 Artificial Intelligence and Machine Learning 6
| Sr. No. | MS in Data Science & AI – revised Program Structure | ECTS |
|---|---|---|
| 1 | Statistics for Data Science | 6 |
| 2 | Research Methods | 6 |
| 3 | Capstone Consulting Projects | 18 |
Professionals with relevant work experience in data science, software engineering, or related fields who want to earn formal qualification in DS and ML.
Professionals working in data-related roles who want to deepen their expertise in machine learning and AI techniques can benefit from an MS program to enhance their career prospects.
Those looking to start AI and DS-related businesses or develop innovative AI applications can benefit from an MS program to acquire the necessary skills and knowledge.
Those interested in conducting research in DS, AI and ML may pursue these masters to gain the necessary skills and knowledge for their research endeavours.
Top-level executives who wish to understand the landscape of DS & AI to guide its implementation in the organisation.
| Career Path | Job Description |
|---|---|
| Data Analyst | Forecasting future trends and identifying significant patterns in data. Also, Analysing massive datasets for anomalies, patterns, etc., to make predictions |
| Natural Language Processing Engineer | Investigating the relationship between spoken language and computer systems, working on chatbot and virtual assistant projects |
| Research Scholar | Pursuing Ph.D. in the areas of Data Science |
| Researcher | Engaging in AI and computer science research, advancing Data Science technologies |
| Research Scientist | Expert in computational statistics, machine learning, deep learning, and applied mathematics, typically requiring a doctorate |
| Software Engineer | Developing applications using AI tools, also known as a programmer or AI developer |
| AI Engineer | Creating AI models from scratch, assisting stakeholders in understanding outcomes |
| Machine Learning Engineer | Designing, developing, and maintaining ML software systems using data |
| Data Scientist | Assembling, scrutinising, and understanding data sets |
| Computer Vision Engineer | Creating and working on systems and projects using visual data |
MS in Data Science and AI (Top Up)
Post-Graduate Diploma in Data Science & Artificial Intelligence
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