MTech Data Science and Industrial Analytics

Tuition

(Local Students) GHȼ 13,384 /year (International) USD$ 5,190.00

he Master of Technology in Data Science and Industrial Analytics is a rigorous academic programme that prepares students for careers in Data Science and Industrial Analytics. The programme covers a wide range of courses such as; Research Methods, Machine Learning with Python, Data Security and Professional Ethics, Calculus and Matrix Algebra with MATLAB, Data visualization with Power BI, Big Data mining and others. Students will also learn to use analytical tools for big data analyses, conduct practical work-based research and design, maintain and develop data systems to suit current industry demands.

– Applicants must have a degree in Statistics/Actuarial Science, Economics, Accounting, Mathematics, Computer Science, Engineering or any Applied Arts/Science related programme with a minimum of Second-Class Lower division. Students with a pass and industry experience will undergo interview.

– Along with the application form, certified copies of certificates and transcript of academic records from a recognized institution must be submitted.

The programme is of one year duration, made up of two semesters. In the first semester, the focus is on coursework, with a heavier load of six courses. Then, in the second semester, they transition to more practical experiences like industrial attachment, seminars and thesis work, with the option to take up to three courses alongside these activities. This balance allows students to gain both theoretical knowledge and practical experience in their field of study. Details of structure is given below;

YEAR ONE, SEMESTER ONE

CODE	COURSE TITLE	HOURS	PRACT	CREDIT
MDS 601	Research Methods	3	2	3
MDS 602	Advanced Probability theory and Modelling in R	3	2	3
MDS 603	Machine Learning with Python	3	2	3
MDS 604	Calculus and Matrix Algebra with MATLAB	3	2	3
MDS 605	Data Security and Professional Ethics	3	2	3
MDS 606	Database Design and Development	3	2	3
	TOTAL	18	12	18

YEAR ONE, SEMESTER TWO

CODE	COURSE TITLE	HOURS	PRACT	CREDIT
MDS607	Industrial Attachment	2	2	2
MDS608	Seminar	2	2	2
MDS609	Dissertation	5	5	5

ELECTIVES (Select a minimum of 6 or Maximum of 9 Credits)
MDS 610	Data Visualization with Power BI	3	2	3
MDS 611	Big Data Mining	3	2	3
MDS 612	Artificial Intelligence and Internet of Things	3	2	3
MDS613	Data Science Project Management	3	2	3
MDS 614	Analytical Software design and Development	3	3	3
	TOTAL			18

Mode of Delivery

Lectures, seminars and workshops
Assignments and exercises
Individual and group presentations

Assessment

Class tests and quizzes: Students will be assessed through regular class tests and quizzes, which carry a weightage of 10%.
Assignments, with a weightage of 10%.
Mid-semester examination, which carries a weightage of 20%.
End-semester examination, which carries a weightage of 60%.

It is expected that by the time students graduate from the programme, they should be able to:

Competently use analytical tools such as Python, R, and Power BI for big data analysis and interpretation.
Conduct practical, work-based research.
Integrate computer science, optimization, and statistics to generate effective and well-rounded industrial solutions.
Identify problems, evaluate their extent, and recommend appropriate solutions.
Design, develop, and maintain data systems to meet current innovative demands.
Interpret data findings effectively for different audiences through oral, visual, and written formats.

Career Prospects

Data Scientist
Develop and implement advanced data models and algorithms.
Analyze large datasets to derive actionable insights and solve complex business problems.
Machine Learning Engineer
Design, build, and deploy scalable machine learning models.
Optimize algorithms for performance and accuracy in various industrial applications.
Data Analyst
Perform statistical analyses and prepare reports to support informed business decision-making.
Interpret data trends and patterns to provide strategic recommendations.Business Intelligence Analyst. Develop and manage business intelligence solutions.

Create and maintain dashboards, reports, and data visualizations.

Industrial Data Analyst
Analyze manufacturing and production data to improve efficiency and reduce costs.
Implement predictive maintenance models to minimize equipment downtime.
Data Engineer
Design, construct, and maintain data pipelines and databases.
Ensure data integrity and accessibility for analysis and reporting.
Analytics Consultant
Provide expert advice on data strategy, analytics solutions, and technology implementation.
Support organizations in leveraging data for business growth and innovation.
Quantitative Analyst (Quant)
Apply statistical and mathematical models to assess financial risks and opportunities.
Develop trading algorithms and investment strategies.
Data Architect
Design and manage organizational data architecture and frameworks.
Ensure data systems are scalable, secure, and aligned with business requirements.
Chief Data Officer (CDO)
Lead data management and governance strategies within an organization.
Drive data initiatives and ensure alignment with organizational goals.
AI Research Scientist
Conduct research on advanced artificial intelligence and machine learning techniques.
Publish findings and contribute to the development of new technologies.
Industrial Engineer
Apply data science techniques to optimize industrial processes and systems.
Develop simulation models to predict and enhance production outcomes.
Fraud Analyst
Use data analytics to detect and prevent fraudulent activities.
Develop fraud detection models and conduct investigations.
Customer Insights Analyst
Analyze customer data to understand behaviour and preferences.
Provide insights to improve customer experience and engagement.
Supply Chain Analyst
Optimize supply chain operations using data analysis.
Predict demand and manage inventory levels effectively.

These roles cut across various sectors including, but not limited to, technology, finance, healthcare, manufacturing, retail, and related industries, reflecting the versatility and high demand for professionals with expertise in data science and industrial analytics.

Application E-Voucher Cost

The cost of the application E-Voucher is GHȼ 200.00.

E-Voucher Number and Serial Can Be Obtained From:

All mobile networks: Dial the short code *389*288# and follow the prompt to pay and receive your E-Voucher by SMS.
All branches of Access Bank.
All branches of Bank of Africa.
All branches of Fidelity Bank.

International students should send an email to info@atu.edu.gh. An application voucher will be generated and sent in response to the email.

Application Process

Log on to the admissions system at https://application.atu.edu.gh with the E-Voucher number and PIN for the 2024/2025 Academic Year admissions.

Follow the steps on the online admissions system to complete your application.
Please note: Use a passport picture with a sea blue background (160 × 160 px dimensions).
Submit the completed application online and keep a copy of the summary page for personal reference.

Further Information

For more information on admission, applicants are advised to contact the Graduate School Secretariat, visit the University website https://atu.edu.gh, or email graduateschool@atu.edu.gh, or call (+233) 271061481 / 0332095371.