Master In Data Science
We know the amount of data produced globally daily is 2.5 quintillion bytes, which is enormous and is expected to keep increasing as the world’s population gets more access to the internet. The data is now considered a commodity that is more valuable than oil, and buried in these data are answers to countless questions. Data Science helps to deal with these vast volumes of data using modern tools and techniques to find unseen patterns, derive meaningful information, and make business decisions. When the opportunity in data science comes knocking at your door, will you be ready?
The Master in Data Science program aims to prepare students with a well-rounded education in different areas of Data Science to prepare themselves to become successful data scientists. The curriculum is made up of 4 core modules and 2 specialization modules providing in-depth knowledge in the field of Data science and its industrial application. Students will learn how to work with data to solve complex problems. Topics covered include Python, Data Science Algorithms, Data Analytics in Business & Data Mining. In the master’s program students will also learn two specialization modules in (I) Statistical Data Modelling and (II) Applications of Data in Artificial Intelligence & Block Chain. At the end of course modules, all students are required to undertake a capstone project in Data Science to have hands-on working experience by solving real-world problems.
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This module inculcates practical understanding and a framework that allows the execution of essential analytics actions such as extracting, cleaning, changing, and analysing data. In this module, learners grasp the knowledge of programming languages, tools, frameworks, and libraries utilised throughout the course to acquire and model data sets. Data analysis is accomplished through visualising, summarising, and developing rudimentary data handling abilities by paying attention to variable types, names, and values. In addition, managing data using dates, strings, and other elements, enhances learners’ abilities to perform data research and generate visualisations.Learning Outcomes
L01: Analyse information using data visualisation, summary, and counting tools.
L02: Acquire rudimentary skills in data handling, focusing on variable types, names, and values.
L03: To learn how to use the pipe operator to combine numerous tidying operations in a chain.
L04: The ability to work with data that includes dates, strings, and other variableContent Covered
- Data Cleaning Techniques
- Data Preprocessing
- Data Manipulation
- Core Python Programming
- Data Visualisation using Matplotlib
- Linear Algebra
- Statistics and Probability
- Exploratory data analysis
- Variance, Standard Deviation, Median
- Bar charts and Line charts
- Python libraries and framework in data analysis
- 2D Scatter Plot
- 3D Scatter plot
- Pair plots
- Univariate, Bivariate, and Multivariate
- IQR (InterQuartile Range)
- Data analysis with Pandas
This module addresses the principles of creating reliable spreadsheet models, translating conceptual models into mathematical models, and applying them in spreadsheets. It also demonstrates a knowledge of three analytic tools in Excel, Excel functions, and the process of auditing spreadsheet models to assure accuracy. Additionally covered in this module are Decision analysis, Payoff Tables, and Decision Trees. Microsoft Power BI helps users derive practical knowledge from data to solve business concerns, bringing analytical models to corporate decision-making. Learners acquire insight into advanced analytic features of Power BI, such as prediction, data visualisations, and data analysis expressions.Learning Outcomes
LO1: Critically analyse the use of business data in an organisational decision-making context.
LO2: Demonstrate a critical understanding of business analytics principles in management functions.
LO3: Apply appropriate data management and analysis techniques to retrieve, organise and manipulate data.
LO4: Apply appropriate statistical data analysis methods and visualisation techniques to make sound business decisions.Content Covered
- Creating Spreadsheet models
- What-If analysis
- Functions for modelling
- Auditing Spreadsheet models
- Predictive and Prescriptive Spreadsheet models
- Problem Identification
- Decision Analysis
- Decision Analysis with or without Probabilities
- Computing Branch Probabilities
- Utility Theory
- Data streaming in Power BI
- Visualisation in Power BI
- Data Analysis expressions
- Report Views in PowerBI
- Data Sorting
- Data Transformation
The data mining process includes collecting necessary information from enormous databases that help make a knowledgeable decision. The module demonstrates data mining techniques like data processing, pattern discovery, and trends in information. These methods are employed to obtain the skills and abilities for applying data integration, cleansing, selection, and transformation on tables and graphs for knowledge discovery. Python matrix libraries allow learners to construct some realistic representation of text mining by executing tasks such as classification, estimation, segmentation, forecasting, sequence, and data association.Learning Outcomes
LO1: Understand the fundamentals of text mining and analysis, including identifying exciting patterns, extracting helpful knowledge, and supporting decision-making.
LO2: Explore fundamental principles of text mining and essential algorithms and some of their practical applications.
LO3: Applying the learned knowledge and skills to implement scalable pattern discovery techniques on large volumes of transactional data
LO4: Engaging in meaningful discussions about pattern evaluation metrics and investigating techniques for mining various patterns, including sequential and sub-graph patterns.Content Covered
- Introduction to Data mining
- Data Mining in a Python-based environment
- What is a data warehouse
- How to find patterns?
- Affinity Analysis
- Product rесоmmendаtіоn
- Introduction to Database Mining
- Databases and SQL
- DDL, DML, Joins, and Schemas
- How to use Python Matrix Libraries on Datasets.
- Lоаd the Dataset with NumPy
- Mining-friendly data representations
- Text Representation for Data Mining.
- Why is text complex?
- Text mining
- Data Modelling, Evaluation, and Deployment in Text Mining
- Exemplary techniques: Bag of words representation in Text Mining
- Frequent Subgraph Mining
- Data Filtering
- Power Query Editor
- Risk Analysis
- Sensitivity Analysis
This module provides extensive knowledge of splitting data into training, validating, and creating test sets. Develop and assess predictive mining models by integrating a framework and practical perception. There are numerous performance metrics for estimation and categorization systems presented. The most prevalent predictive modelling approaches, including artificial neural networks, support vector machines, k-nearest neighbour, Bayesian learning, ensemble models, and different decision trees, are reviewed in this module, along with their internal workings, capabilities, and applications. Most of these strategies can tackle prediction difficulties of the classification and regression kinds. They are commonly employed to address challenging prediction challenges when other, more traditional approaches fail to deliver results.Learning Outcomes
LO1: Introduce the fundamental algorithmic concepts, including sorting and searching, divide and conquer, and complex algorithms.
LO2: Sort data and use it for search; break down a huge problem into smaller ones and answer them recursively; apply dynamic programming to genomic research; and more.
LO3: Discuss and construct the most often used data structures for modern computing
LO4: To be able to use the most industry-used data structures in modern computingContent Covered
- Static Holdout Method
- k-Fold Cross-Validation
- Class Imbalanced Data
- Evaluating the Classification of Categorical Outcomes
- Evaluating the Estimation of Continuous Outcomes
- Logistic Regression
- K-nearest Neighbour
- Nearest Neighbor Method for Prediction
- Classification and Regression tree
- Support Vector Machines
- Process-Based Approach to the Use of SVM
- Naïve Bayes Methods
- Bayesian Networks
- Neural Network Architectures
- Ensemble Modelling
This module gives learners the insight to apply many prediction models and grasps linear regression. Create predictions based on a group of input variables using regression analysis methods. Learners investigate how to model an extensive range of real-world interactions using complicated statistical methodologies, such as generalised linear and additive models. This module inculcates intermediate and advanced statistical modelling methodologies. It is specifically created for learners to develop proficiency in linear regression analysis, experimental design, and extended linear and additive models. Based on these skills, interpreting data, discovering links between variables, and generating predictions are made simpler via intuitive representations.
LO1: Differentiate between various types of predictive models and Master linear regression
LO2: Understand the inner workings through algorithms of different models
LO3: Analyse and explore the results of logistic regression and understand when to discriminant analysis
LO4: Maximise analytical productivity by analysing different models and interpreting their accuracy in a well-organised manner
- Selecting a Sample
- Point Estimation
- Sampling Distributions
- Interval Estimation
- Hypothesis Tests
- Statistical Inference and practical significance
- A Simple Linear Regression Model
- Least Square method
- Inference and Regression
- Multiple Regression Model
- Logistics Regression
- Predictions with Regression
- Model Fitting
- Tableau data model
- Shape and data transformation using Tableau Query Editor
- Tableau Report View
In this module, learners will better grasp artificial intelligence (AI) applications in business and comprehend AI decision-making. Through breakthroughs in IoT and the emergence of Blockchain, this curriculum prepares students with a broad foundation of AI-enabled software solutions. As learners continue through this module, they become acquainted with the technology that powers the automated world—knowing the sorts of algorithms and how they may be utilised to enhance or replicate human behaviour across diverse applications. This module teaches about AI, IoT, Blockchain, and machine learning components while building on a solid conceptual framework that will present rigorous, hands-on, and step-by-step ways to tackle realistic, complex real-world challenges.
LO1. Introducing Artificial Intelligence (AI), exploring its features and variants in the business domain. Furthermore, to understand the business context of AI and interpret AI decision-making.
LO2. Understand & create an AI implementation plan for a business setup through recognition of suitable model parameters
LO3: To further explore the components of Blockchain and understand Distributed Ledger Technology (DLT) concept, features, benefits, and relevance in application
LO4: Understanding Hyperledger, Smart Contracts, and IoT (Internet of Things) in applied business models to assess the impact in the long term
- Introduction to Artificial intelligence
- AI enables applications
- What is Deep Learning
- Artificial Neural Networks
- Image Processing and OpenCV
- Introduction to NLP
- Artificial Neural Networks
- Text Processing
- Text Classification
- Topic Modelling
- Recurrent Neural Networks
- Major components of IoT
- Variety of Sensors
- IoT protocols at various layers
- Applications and user interface in IoT
- Smart factories of tomorrow and the Industrial Internet of Things
- Introduction to Blockchains
- Introduction and usage of Hyperledger and Smart Contract
- Blockchains Structure
- Centralised, Decentralised, and Distributed systems
- Introduction to DLT
- DLT features, benefits, and usage in Blockchain
- Types of Blockchains
- Why Blockchain?
- Building AI and ML applications using Blockchain technology
The purpose of this module is to discuss and explain the role of Data science and its practices in an organisation and their influence on the overall performance and competence of the organisation. This module is designed to develop an understanding of the contemporary practices and competence to develop a research or design question, illustrate how it links to current knowledge and carry out the study in a systematic manner. Learners will be encouraged to pick a research/development project that displays their past learning in the data science domain. It is meant to acquire an understanding of Data Science and the paradigm shift in the approaches and methods related to various functions of DS like data visualisation, probability, inference and modelling, data mining, data organisation, regression, and machine learning to name a few. It also endeavours to highlight the role and significance of data analytics and data modelling during the planning, decision-making, and implementation of change in the organisation. Upon completing the module, the participants will have comprehensive knowledge about the broader data analysis context and a data product to demonstrate their data science expertise to potential employers or educational programs.
LO1: Conduct independent Research and Development within the context of a Data Science Project.
LO2: Developing the ability to solve problems using analytics and data science independently.
LO3: Communicate technical information clearly and succinctly to a broad, non-specialist audience.
LO4: Create detailed written documentation to a standard expected of a professional in the field of Data Science & evaluate Project outcomes concerning key research publications in the relevant field.
Live & interactive lectures by expert faculties
Recorded session for offline viewing
World-class curriculum by eminent faculty
Regular webinars by industry leaders
Assignments for module assessments
Easy-to-use LMS accessible anywhere
Online library to further enhance your knowledge
Dissertation on your area of research work
What you’ll get as a Masters student with Exeed College
Universidad Católica de Murcia (UCAM), founded in 1996, is a fully-accredited European University based out of Murcia, Spain. With learning centres in the Middle East and Southeast Asia, UCAM aims to provide students with the knowledge and skills to serve society and contribute to the further expansion of human knowledge through research and development.
The university offers various courses, including 30 official bachelor’s degrees, 30 master’s degrees and ten technical higher education qualifications through its Higher Vocational Training Institute, in addition to its in-house qualifications and language courses. The programmes offered are distinguished in Europe and worldwide, with good graduate employability prospects as well.
UCAM is accredited by ANECA (National Agency for Quality Assessment and Accreditation of Spain) and the Ministry of Education regarding 17 of its undergraduate degrees.
If you’d like to gain the complete skill set to succeed in today’s business world, this is the area for you.
Who Can Apply for the Course?
- Any graduate who has a keen interest in Data Science.
- Professionals looking to learn about data analytics.
- Business person trying to acquire technical skills to solve their data problems
- Professionals aiming to upskill their career for better job opportunities
- Professionals who wish to transition to roles such as Data Scientist.
- Bachelor’s Degree from a recognized University
- Proficiency in English language
Due to its involvement in modern Machine Learning algorithms with maths and programming, candidates having knowledge of linear algebra, probability, and calculus could be a plus.
Showcase your capabilities with real-world projects
Bring Your Own Project
Learn to solve a problem that you/your organization is facing using Data Science
Choose From Curated Capstone Projects
- House Rental Prediction
- Image Classification
- Business Insights Reporting
- Python for data science
- Data analysis
- Data Mining
- Data Analytics in Business
- Algorithms in Data Science
- Data in AI & Blockchain
Tools/ Frameworks/ Libraries
Tools/LibrariesPandas, numPy, seaborn, matplotlib, cufflinks, scikit, NLTK, CoreNLP, spaCy, PyNLP, Tensorflow, Keras, Open CV, Power BI, Excel
IDE ShellJupyter Notebook, google colab, pycharm, visualstudio code
Application and Use Cases
- Traffic Management: Data Science can identify the cause of congestion & manage traffic effectively
- Road Safety: Data Science can help us identify accident hotspots & recommend safety measures
- eCommerce: Data Science can gain behaviour patterns & provide recommendations to customers
- Banking: Data Science can handle customer data, detect fraud, manage credit risk in allotting loans
- Marketing & Sales: Data Science helps businesses to market & sell product to the right audience.
- Health Care: Data Science is used for drug discovery, predicting anomalies, and monitoring patient health
- Forecasting: Data Science can be used to predict future happenings by analysing historical data.
- Manufacturing: Data Science can automate large-scale processes & speed up implementation time
- Retail: Data Science can help with demand forecasting, pricing decisions & optimise product placement
Exeed College’s high level of instruction has attracted an increasing number of companies and the placement scene is expanding. Candidates who excel in internships will be eligible for placement at top MNCs that work with Exeed College.
- Deliver five proof-of-concept a month
- We will have our partner companies review the POCs
- JD-based Support training
- Placement in MNC
Exeed Collge provides internships in the respective field for 5-6 months to all eligible and able students.
- Mentoring by software developers
- Live workshops on projects
- Internship certificate
- Candidate's evaluation
After successfully completing the learning modules, eligible students would move on to internships.
What is included in this course?
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The course will be delivered by senior faculty with decades of experience in Management and Engineering. The panel of faculty have experience in academia as well as industry and this makes them quite suited for teaching professionals who are looking for the next big career progression. Our faculty hold doctorates from international universities like Dundee, Ohio, Texas, Leeds, and Stellenbosch, to name a few, and they have experience working with global organizations. The faculty include senior Director of Two South African firms, a veteran educationist who is a pioneer in online education; a business action coach and an HR Business Partner.
The evaluation is based on assignments for the modules and a Dissertation (project) towards the end of the program. We deliver one module at a time and each module will last for a 1-month post, in which you get a week’s time to complete the assignment. The finished assignment should be uploaded in the Learning Management System (LMS). The faculty will evaluate the assignment and publish your result on the same platform.
Exeed College has implemented a teaching methodology with a greater focus on practical expertise. After the enrollment, you will be given a unique user ID and password to access our online LMS. Our teaching is based on case studies presented via HD videos, which increases students’ involvement, and promotes active learning. The course can be done 100% online. Lectures will be delivered through our LMS and the assignments are to be submitted as a soft copy using your student login. Students benefit from 24/7 access to our award-winning study platform and online resources, which include the necessary study materials for their program:
- Live interactive classes by senior faculties
- A recorded session for offline viewing
- Case studies delivered in HD-quality video
- Online resources and publications
- Full academic support
- E-Books and revision kits
- Quick tests for challenging your knowledge of key concepts and theories
- A dedicated online forum for interaction with tutors and classmates
- Access to success manager
- Self-assessed mock assignments
- Live chat feature for any technical support needed
Apart from 8 live interactive sessions for each module, the learners will benefit from the advantage of having these sessions recorded and archived in their LMS, in order to catch up with the missed live sessions. The learners will also have access to the bite-sized learning videos developed with the course content, access to e-library with hundreds and thousands of journals, case studies, presentations, videos, etc. at their disposal to enhance their learning.
As per European Education Framework, a learner has to achieve 60 European Credit Transfer System (ECTS) in order to get this qualification to be recognized as Masters by any European University and internationally as well. These 60 ECTS are equivalent to 180 UK credits.
UCAM is one of the fastest-growing universities in the European Region and is also one of the most innovative and forward-thinking universities. UCAM is ranked among the top 150 universities in the European Region by the Times Higher Education. Also ranked among the top ten for its Business Administration Program and MBA program in the region, UCAM alumni are currently working with leading companies including Microsoft, EY, PwC, Standard Chartered, PwC, Aramco, Sabic, HSBC, Google, Schlumberger, Air Liquide and Honey Well to name a few. UCAM is internationally recognized, and students can get it attested from the respective Foreign and External Affairs Ministry.
Yes, this will definitely help you in migrating to these countries. Students can get their degree equivalence from ECA (Education Credential Assessment) organizations like WES, ICAS, IQAS.
Each class has about 45 students from different nationalities working with leading companies. The batch of students consists of entrepreneurs, managers, CEOs, supervisors, engineers, consultants, directors and senior executives. Also the students are from diverse sectors like oil & gas, government, media, construction, IT, Telecom, consulting, airline, manufacturing, banking, financial services, retail, pharma, FMCG and healthcare sectors. The current batch has students from Air Liquide, Schulumberg, Air Liquide, Saudi Electricity Company, Amazon, Noon, NMC Healthcare, ADFERT, Etihad, Emirates, Botswana Power Corporation, Allergen, Covance, Julphar and Nutricia to name a few.
Post completion of Part-1, you will be entitled to receive a Postgraduate Extended Diploma in Business Administration (Specialization), which is a Level-7 qualification. This carries 120 UK credits which you may choose to transfer towards your MBA top-up with the same University.
The fee of the program is as published on the website and the scholarship can be provided based on different factors. However, this one-year MBA with Exeed – UCAM is one of the most affordable programs in the UAE region and has a flexible payment plan of monthly installments to pay out the fee in a span of 12 months.
The program fee includes your registration to all courses (Part 1 & 2), certification, career support, course delivery.
You can apply by submitting the following documents:
- Application form
- Most updated resume
- Scanned copy of your highest qualification certificate
- Copy of passport
- Passport size photograph
When it comes to an online study program the first question that comes to a student is whether it is a self-study program, but with Exeed College we are looking at more of a guided level learning program with live interactive sessions being conducted which already covers up the main factor involved in availing a full time MBA title. As per European Education Framework, a learner has to achieve 60 ECTS before he/she can be conferred an MBA by any European University. These 60 ECTS which are considered as a full time MBA title under global standards. Through Cambridge International Qualification (CIQ), Exeed has partnered with different Universities in Europe/UK/USA to assist busy working professionals to realize their dream of earning an MBA under a guided level learning program flexible and well-structured online based level platform.
MOFA stands for Ministry of Foreign Affairs. UAE MOFA attestation is mandatory on every document after UAE embassy attestation for getting a valid visa. UCAM MBA title is verified and recognized under MOFA. MOFA attestation is required for all those universities who do not have a physical campus in the UAE.
MOHE stands for Ministry of Higher Education. MOHE approves, accredits and recognizes only those qualifications which are pursued through a physical campus in the country of origin.
However, MOHE attestation is not mandatory for expats residing in the UAE. Therefore, UCAM MBA Degrees are attested and verified by the Ministry of Foreign Affairs.
-Yes, it is quite possible, as we follow the protocols of Recognized Prior Learning Policy (RPL) under which there are two categories:
*RPCL(Recognized Prior Credential Learning): Where the subjects learnt by the student (transcripts required) based on their previous qualifications (Master’s Degree or Level 6 &7 diploma) are mapped with our course modules post which he/she will be eligible for the Module exemptions.
* RPEL (Recognized Prior Experiential Learning): Where the student documents will be mapped with the prior experiential learning (acquired through work experience), post which he/she will be eligible for some exemptions.
Any university in the world allows maximum exemptions of 1 or 2 modules only as per the policy, exceptional cases would be discussed with the authority concerned, to be taken into the consideration.
NOTE: Course fee and Module Exemptions are two independent factors regardless of the number of modules exempted, the course fee will remain the same. This should be noted by the student prior to raising the module exemption request.
Once the module exemption feedback is received, the Advisor concerned will submit the RPL Letter to the student stating the number of modules exempted along with its credits.
Yes, this will help you in migrating to these countries. Students can get their degree equivalence from ECA (Education Credential Assessment) organizations like WES, ICAS, IQAS, as we hold the World Education Services (WES) accreditation.
Although the sessions are being recorded and archived on the LMS system which can be accessed at any time, the student would be required to achieve at least 70% of attendance, which will be captured during the live interactive platform.
Yes, we do provide services in attaining the attestation of a degree certificate with an additional service fee charge.
Students can get their certificates by attending the Graduation Ceremony at the UCAM University Campus, Spain (charges will be additional) or the Certificate will be directly couriered to the respective addresses provided.
All the courses are internationally accepted, including the UAE, and you will receive MOFA attestation for the same, if you wish. An additional charge will be there for the attestation.
Both Westford University and Exeed College are entities of the Westford Education group. We offer MBA programs through various Universities, but we have one University in common which is UCAM and we give different specializations comparing them.
This program is purely designed for working professionals, we take their time and comfort into consideration. Whatever a student learns in two year is combined into one which in turn saves more time and money.
We have many students from your country who have joined us of which we can assist you in giving references. Plus, we have references of our alumni, who have completed the course and you can talk to them on our website.
It is always better to have an MBA rather than opting for the diploma programs. As a student you will be receiving UK Level 7 Diploma qualification as an added benefit included in the course fee.
6 to 8 months depending on the Deferment reason, if a student exceeds the promised deferment period, the student is bound to pay the registration fees.
PGED is 6 Modules which is 120 UK credits, whereas PG Diploma is 2 modules i.e. 40 UK credits.
Yes, definitely it holds a value as it is an added certificate in your profile. A student will gain instant free membership of 1 year affiliate level.
There will be a further specified timeline given to submit the assignment once the initial deadline is expired. If the student still fails to submit then he/she will get a fine of AED 250.
As the program is purely designed for the working professionals there is no failing system. The student always gets an option of redoing the assignments.