Master of Science in Data Science and Analytics
Every day industry executives in both the private and public sectors bemoan the lack of data scientists. CEOs, CIOs, CFOs and COOs need people who theoretically know how to look at the data that their companies generate, and delve into it to derive the all-important insights.
The demand for these professionals with data skills is increasing alongside the rising investment in data. Companies today realise the value of Data Analytics. As a result, they are looking for skilled people to capture and make sense of it.
95% of the world’s data has been created in just the past 2 years.
Data is the next natural resource and Big Data is becoming the new differentiating factor of production. Faced with overwhelming amounts of data, organizations are struggling to extract the powerful insights they need to make smarter business decisions.
During the course of two years, participants will be able take their data analytics skills to the next level as they learn the theory and practice behind recommendation engines, regressions, network and graphical modeling, anomaly detection, hypothesis testing, machine learning, and big data analytics.
This course has been designed for students who have completed a degree in either Statistics, IT, Commerce, Economics or Finance, and technical enthusiasts wishing to further their knowledge of Data Science and Analytics.
The programme provides students with a route to high-quality careers in Big Data, Machine Learning, Artificial Intelligence, Data Analytics and Data Science.
If you want to:
- Clean, prepare your data for analysis, apply programming to explore and model data.
- Apply analytic techniques to solve development problems in Medicine, Engineering, Finance, Economics, Real Estate and Social Sciences. The types of analytics covered include – Descriptive Analytics, Diagnostic Analytics, Predictive Analytics and Prescriptive Analytics.
- Deploy Machine Learning Algorithms to mine your data.
- Interpret analytical models to make better business decisions, present your findings and impress the audience.
Consider applying for Strathmore University's MSc in Data Science and Analytics today!
Course work will cover core areas such as: Data Mining, Storage and Retrieval, Time Series Analysis and Forecasting, Statistical Inference in Big Data, Applied Machine Learning in Data Science, Text and Unstructured Data Analytics.
The course will be a hybrid of both face-to-face sessions as well as video-conferencing.
We have made the decision to accommodate the learning both from home and/or on-campus.
Classes are organised as five (5) taught modules and a dissertation.
Duration
Two (2) Academic Years - Classes will be held Monday to Friday from 5:30 - 8:30 PM.
The programme offers two specialisations:
a. Business Analytics - This is for students who are interested in learning how to extract/discover/find insights from business data, and those who want to improve processes and outcomes within a business. You will learn how to use software to perform data modelling, data and statistical analysis to construct and develop digital analytics arguments with clear assumptions and conclusions. Course topics include Business Intelligence and Big Data in Finance and Banking.
b. Computational Statistics - This is for students interested in improving Data Science algorithms and analytics and/or who want to transition into becoming a Data Science researcher. You will learn the details of computational models behind the study of data science and analytics and how to use software modules to statistically model data, transforming them into usable information, and from that information derive insights. Course topics include Optimisation for Data Science and Bayesian Statistics.
1. Holders of First Class or Upper Second Class honours degrees in Statistics, IT, Commerce, Economics or Finance from recognised universities, or
2. Holders of Lower Second Class degrees plus postgraduate diplomas or certificates, or with at least two years’ relevant experience in the areas above, or
3. Holders of other related qualifications from recognised universities, considered by the Academic Council as equivalent to the criteria in (1) or (2).
The applicant should upload the following documents:
I. Undergraduate degree certificate and transcript of records (TOR) in English giving full details of subjects studied and grades/marks obtained.
II. Kenya Certificate of Secondary Education-KCSE certificate (Secondary/High School Certificate or its equivalent).
III. An updated Curriculum Vitae. Please use the Europass CV template (http://europass.cedefop.europa.eu).
IV. Digital passport photo.
V. A copy of National Identity Card (ID) or a copy of Passport (bio-data page).
VI. Interview fee of Ksh 2,500/= (paid through the application portal).
NB: Upon acceptance into the programme, the above copies and transcripts should be certified by the awarding institution or by an advocate of the high court.
After submission of the application the candidate will be contacted by the University to take the Graduate Entrance Exam (GEE), which can be done in person or online.
The GEE consists of English comprehension and grammar, arithmetic as well as an essay.
Once the applicant has completed and passed the written exam they will be scheduled for an oral interview.
The programme provides students with a route to high-quality careers in Big Data, Machine Learning, Artificial Intelligence, Data Analytics and Data Science.
The programme will supply industry and government entities with a stream of highly trained data experts.
