{"id":792,"date":"2026-05-06T09:34:49","date_gmt":"2026-05-06T09:34:49","guid":{"rendered":"https:\/\/atu.edu.gh\/gradsch\/?page_id=792"},"modified":"2026-05-06T11:42:14","modified_gmt":"2026-05-06T11:42:14","slug":"master-of-technology-mtech-in-data-science-and-industrial-analytics","status":"publish","type":"page","link":"https:\/\/atu.edu.gh\/gradsch\/master-of-technology-mtech-in-data-science-and-industrial-analytics\/","title":{"rendered":"Master of Technology (MTech) in Data Science and Industrial Analytics"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-page\" data-elementor-id=\"792\" class=\"elementor elementor-792\">\n\t\t\t\t<div class=\"elementor-element elementor-element-152f93f e-flex e-con-boxed wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no wpr-equal-height-no e-con e-parent\" data-id=\"152f93f\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-23e548c elementor-widget elementor-widget-spacer\" data-id=\"23e548c\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-0d839a0 elementor-widget elementor-widget-wpr-post-title\" data-id=\"0d839a0\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"wpr-post-title.default\">\n\t\t\t\t\t<h1 class=\"wpr-post-title\">Master of Technology (MTech) in Data Science and Industrial Analytics<\/h1>\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-9acd756 e-grid e-con-full wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no wpr-equal-height-no e-con e-child\" data-id=\"9acd756\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-61fd96e elementor-icon-list--layout-traditional elementor-list-item-link-full_width elementor-widget elementor-widget-icon-list\" data-id=\"61fd96e\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"icon-list.default\">\n\t\t\t\t\t\t\t<ul class=\"elementor-icon-list-items\">\n\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<i aria-hidden=\"true\" class=\"icon icon-calendar-1\"><\/i>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Duration (1 Year)<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3145973 elementor-icon-list--layout-traditional elementor-list-item-link-full_width elementor-widget elementor-widget-icon-list\" data-id=\"3145973\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"icon-list.default\">\n\t\t\t\t\t\t\t<ul class=\"elementor-icon-list-items\">\n\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<i aria-hidden=\"true\" class=\"icon icon-countdown-timer\"><\/i>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Session (Weekday or Weekend)<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-384b246 elementor-widget elementor-widget-spacer\" data-id=\"384b246\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-6475bb4 e-con-full e-flex wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no wpr-equal-height-no e-con e-parent\" data-id=\"6475bb4\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t<div class=\"elementor-element elementor-element-f474316 e-flex e-con-boxed wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no wpr-equal-height-no e-con e-child\" data-id=\"f474316\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-5847be8 e-n-tabs-mobile elementor-widget elementor-widget-n-tabs\" data-id=\"5847be8\" data-element_type=\"widget\" data-e-type=\"widget\" data-settings=\"{&quot;tabs_justify_horizontal&quot;:&quot;start&quot;,&quot;horizontal_scroll&quot;:&quot;disable&quot;}\" data-widget_type=\"nested-tabs.default\">\n\t\t\t\t\t\t\t<div class=\"e-n-tabs\" data-widget-number=\"92568552\" aria-label=\"Tabs. Open items with Enter or Space, close with Escape and navigate using the Arrow keys.\">\n\t\t\t<div class=\"e-n-tabs-heading\" role=\"tablist\">\n\t\t\t\t\t<button id=\"e-n-tab-title-925685521\" data-tab-title-id=\"e-n-tab-title-925685521\" class=\"e-n-tab-title\" aria-selected=\"true\" data-tab-index=\"1\" role=\"tab\" tabindex=\"0\" aria-controls=\"e-n-tab-content-925685521\" style=\"--n-tabs-title-order: 1;\">\n\t\t\t\t\t\t<span class=\"e-n-tab-title-text\">\n\t\t\t\tABOUT THE PROGRAMME\t\t\t<\/span>\n\t\t<\/button>\n\t\t\t\t<button id=\"e-n-tab-title-925685522\" data-tab-title-id=\"e-n-tab-title-925685522\" class=\"e-n-tab-title\" aria-selected=\"false\" data-tab-index=\"2\" role=\"tab\" tabindex=\"-1\" aria-controls=\"e-n-tab-content-925685522\" style=\"--n-tabs-title-order: 2;\">\n\t\t\t\t\t\t<span class=\"e-n-tab-title-text\">\n\t\t\t\tModules &amp; Courses\t\t\t<\/span>\n\t\t<\/button>\n\t\t\t\t<button id=\"e-n-tab-title-925685523\" data-tab-title-id=\"e-n-tab-title-925685523\" class=\"e-n-tab-title\" aria-selected=\"false\" data-tab-index=\"3\" role=\"tab\" tabindex=\"-1\" aria-controls=\"e-n-tab-content-925685523\" style=\"--n-tabs-title-order: 3;\">\n\t\t\t\t\t\t<span class=\"e-n-tab-title-text\">\n\t\t\t\tCareer Prospect\t\t\t<\/span>\n\t\t<\/button>\n\t\t\t\t\t<\/div>\n\t\t\t<div class=\"e-n-tabs-content\">\n\t\t\t\t<div id=\"e-n-tab-content-925685521\" role=\"tabpanel\" aria-labelledby=\"e-n-tab-title-925685521\" data-tab-index=\"1\" style=\"--n-tabs-title-order: 1;\" class=\"e-active elementor-element elementor-element-091b2d4 e-con-full e-flex wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no wpr-equal-height-no e-con e-child\" data-id=\"091b2d4\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-9f450a2 elementor-widget elementor-widget-text-editor\" data-id=\"9f450a2\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p>The 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.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div id=\"e-n-tab-content-925685522\" role=\"tabpanel\" aria-labelledby=\"e-n-tab-title-925685522\" data-tab-index=\"2\" style=\"--n-tabs-title-order: 2;\" class=\" elementor-element elementor-element-27d0485 e-con-full e-flex wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no wpr-equal-height-no e-con e-child\" data-id=\"27d0485\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-c85e7a7 elementor-widget elementor-widget-text-editor\" data-id=\"c85e7a7\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p>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;<\/p><p><strong>\u00a0YEAR ONE, SEMESTER ONE<\/strong><\/p><table><tbody><tr><td width=\"105\"><p><strong>CODE<\/strong><\/p><\/td><td width=\"200\"><p><strong>COURSE TITLE<\/strong><\/p><\/td><td width=\"82\"><p><strong>HOURS<\/strong><\/p><\/td><td width=\"76\"><p><strong>PRACT<\/strong><\/p><\/td><td width=\"82\"><p><strong>CREDIT<\/strong><\/p><\/td><\/tr><tr><td width=\"105\"><p>MDS 601<\/p><\/td><td width=\"200\"><p>Research Methods<\/p><\/td><td width=\"82\"><p>3<\/p><\/td><td width=\"76\"><p>2<\/p><\/td><td width=\"82\"><p>3<\/p><\/td><\/tr><tr><td width=\"105\"><p>MDS 602<\/p><\/td><td width=\"200\"><p>Advanced Probability theory and Modelling in R<\/p><\/td><td width=\"82\"><p>3<\/p><\/td><td width=\"76\"><p>2<\/p><\/td><td width=\"82\"><p>3<\/p><\/td><\/tr><tr><td width=\"105\"><p>MDS 603<\/p><\/td><td width=\"200\"><p>Machine Learning with Python<\/p><\/td><td width=\"82\"><p>3<\/p><\/td><td width=\"76\"><p>2<\/p><\/td><td width=\"82\"><p>3<\/p><\/td><\/tr><tr><td width=\"105\"><p>MDS 604<\/p><\/td><td width=\"200\"><p>Calculus and Matrix Algebra with MATLAB<\/p><\/td><td width=\"82\"><p>3<\/p><\/td><td width=\"76\"><p>2<\/p><\/td><td width=\"82\"><p>3<\/p><\/td><\/tr><tr><td width=\"105\"><p>MDS 605<\/p><\/td><td width=\"200\"><p>Data Security and Professional Ethics<\/p><\/td><td width=\"82\"><p>3<\/p><\/td><td width=\"76\"><p>2<\/p><\/td><td width=\"82\"><p>3<\/p><\/td><\/tr><tr><td width=\"105\"><p>MDS 606<\/p><\/td><td width=\"200\"><p>Database Design and Development<\/p><\/td><td width=\"82\"><p>3<\/p><\/td><td width=\"76\"><p>2<\/p><\/td><td width=\"82\"><p>3<\/p><\/td><\/tr><tr><td width=\"105\"><p><strong>\u00a0<\/strong><\/p><\/td><td width=\"200\"><p><strong>TOTAL<\/strong><\/p><\/td><td width=\"82\"><p><strong>18<\/strong><\/p><\/td><td width=\"76\"><p><strong>12<\/strong><\/p><\/td><td width=\"82\"><p><strong>18<\/strong><\/p><\/td><\/tr><\/tbody><\/table><p><strong>YEAR ONE, SEMESTER TWO<\/strong><\/p><table><tbody><tr><td width=\"105\"><p><strong>CODE<\/strong><\/p><\/td><td width=\"200\"><p><strong>COURSE TITLE<\/strong><\/p><\/td><td width=\"82\"><p><strong>HOURS<\/strong><\/p><\/td><td width=\"76\"><p><strong>PRACT<\/strong><\/p><\/td><td width=\"82\"><p><strong>CREDIT<\/strong><\/p><\/td><\/tr><tr><td width=\"105\"><p><strong>MDS607<\/strong><\/p><\/td><td width=\"200\"><p>Industrial Attachment<\/p><\/td><td width=\"82\"><p><strong>2<\/strong><\/p><\/td><td width=\"76\"><p><strong>2<\/strong><\/p><\/td><td width=\"82\"><p><strong>2<\/strong><\/p><\/td><\/tr><tr><td width=\"105\"><p><strong>MDS608<\/strong><\/p><\/td><td width=\"200\"><p>Seminar<\/p><\/td><td width=\"82\"><p><strong>2<\/strong><\/p><\/td><td width=\"76\"><p><strong>2<\/strong><\/p><\/td><td width=\"82\"><p><strong>2<\/strong><\/p><\/td><\/tr><tr><td width=\"105\"><p><strong>MDS609<\/strong><\/p><\/td><td width=\"200\"><p>Dissertation<\/p><\/td><td width=\"82\"><p><strong>5<\/strong><\/p><\/td><td width=\"76\"><p><strong>5<\/strong><\/p><\/td><td width=\"82\"><p><strong>5<\/strong><\/p><\/td><\/tr><tr><td width=\"105\"><p><strong>\u00a0<\/strong><\/p><\/td><td width=\"200\"><p><strong>\u00a0<\/strong><\/p><\/td><td width=\"82\"><p><strong>\u00a0<\/strong><\/p><\/td><td width=\"76\"><p><strong>\u00a0<\/strong><\/p><\/td><td width=\"82\"><p><strong>\u00a0<\/strong><\/p><\/td><\/tr><tr><td colspan=\"2\" width=\"305\"><p><strong>ELECTIVES (Select a minimum of 6 or Maximum of 9 Credits)<\/strong><\/p><\/td><td width=\"82\"><p><strong>\u00a0<\/strong><\/p><\/td><td width=\"76\"><p><strong>\u00a0<\/strong><\/p><\/td><td width=\"82\"><p><strong>\u00a0<\/strong><\/p><\/td><\/tr><tr><td width=\"105\"><p>MDS 610<\/p><\/td><td width=\"200\"><p>Data Visualization with Power BI<\/p><\/td><td width=\"82\"><p>3<\/p><\/td><td width=\"76\"><p>2<\/p><\/td><td width=\"82\"><p>3<\/p><\/td><\/tr><tr><td width=\"105\"><p>MDS 611<\/p><\/td><td width=\"200\"><p>Big Data Mining<\/p><\/td><td width=\"82\"><p>3<\/p><\/td><td width=\"76\"><p>2<\/p><\/td><td width=\"82\"><p>3<\/p><\/td><\/tr><tr><td width=\"105\"><p>MDS 612<\/p><\/td><td width=\"200\"><p>Artificial Intelligence and Internet of Things<\/p><\/td><td width=\"82\"><p>3<\/p><\/td><td width=\"76\"><p>2<\/p><\/td><td width=\"82\"><p>3<\/p><\/td><\/tr><tr><td width=\"105\"><p>MDS613<\/p><\/td><td width=\"200\"><p>Data Science Project Management<\/p><\/td><td width=\"82\"><p>3<\/p><\/td><td width=\"76\"><p>2<\/p><\/td><td width=\"82\"><p>3<\/p><\/td><\/tr><tr><td width=\"105\"><p>MDS 614<\/p><\/td><td width=\"200\"><p>Analytical Software design and Development<\/p><\/td><td width=\"82\"><p>3<\/p><\/td><td width=\"76\"><p>3<\/p><\/td><td width=\"82\"><p>3<\/p><\/td><\/tr><tr><td width=\"105\"><p><strong>\u00a0<\/strong><\/p><\/td><td width=\"200\"><p><strong>TOTAL<\/strong><\/p><\/td><td width=\"82\"><p><strong>\u00a0<\/strong><\/p><\/td><td width=\"76\"><p><strong>\u00a0<\/strong><\/p><\/td><td width=\"82\"><p><strong>18<\/strong><\/p><\/td><\/tr><\/tbody><\/table><p>Mode of Delivery<\/p><ul><li>Lectures, Seminars and Workshops<\/li><li>Assignments and Exercises<\/li><li>Individual and Group Presentations<\/li><\/ul><p><strong>Assessment<\/strong><\/p><ul><li>Class Test and Quizzes. Students will be assessed through regular class test and quizzes, which carry a weightage of 10%.<\/li><li>Assignments, with a weightage of 10%.<\/li><li>Mid-Semester Examination, which carry a weightage of 20%<\/li><li>End-Semester Examination, which carry a weightage of 60%<\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div id=\"e-n-tab-content-925685523\" role=\"tabpanel\" aria-labelledby=\"e-n-tab-title-925685523\" data-tab-index=\"3\" style=\"--n-tabs-title-order: 3;\" class=\" elementor-element elementor-element-6a378e8 e-con-full e-flex wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no wpr-equal-height-no e-con e-child\" data-id=\"6a378e8\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-74ac641 elementor-widget elementor-widget-text-editor\" data-id=\"74ac641\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p>It is expected that by the time students\u2019 graduate from the programme, they should be:<\/p><ul><li>Able to competently use analytical tools like Python, R, Power BI for big data analysis and interpretation.<\/li><li>Able to conduct practical work-based research<\/li><li>Able to integrate fields within computer science, optimization and statistics to generate adept and well-rounded industrial solutions.<\/li><li>Able to identify problems and evaluate the extents of such problems and recommend appropriate solutions.<\/li><li>Able to design, maintain and develop data systems to suit current innovative demands<\/li><li>Able to interpret data findings effectively to any audience orally, visually and written formats.<\/li><li>\u00a0<\/li><\/ul><p><strong>Career Prospects<\/strong><\/p><p><strong>1. Data Scientist<\/strong><\/p><ul><li>Develop and implement advanced data models and algorithms.<\/li><li>Analyze large datasets to derive actionable insights and solve complex business problems.<\/li><\/ul><p>\u00a0<\/p><p><strong>2. Machine Learning Engineer<\/strong><\/p><ul><li>Design, build, and deploy scalable machine learning models.<\/li><li>Optimize algorithms for performance and accuracy in various industrial applications.<\/li><\/ul><p>\u00a0<\/p><p><strong>3. Data Analyst<\/strong><\/p><ul><li>Perform statistical analysis and create reports to help businesses make informed decisions.<\/li><li>Interpret data trends and patterns to provide strategic recommendations.<\/li><li>Business Intelligence Analyst<\/li><li>Develop and manage BI solutions for businesses.<\/li><li>Create and maintain dashboards, reports, and data visualizations.<\/li><\/ul><p>\u00a0<\/p><p><strong>4. Industrial Data Analyst<\/strong><\/p><ul><li>Analyze manufacturing and production data to improve efficiency and reduce costs.<\/li><li>Implement predictive maintenance models to minimize equipment downtime.<\/li><\/ul><p>\u00a0<\/p><p><strong>5. Data Engineer<\/strong><\/p><ul><li>Design, construct, and maintain data pipelines and databases.<\/li><li>Ensure data integrity and accessibility for analysis and reporting purposes.<\/li><\/ul><p>\u00a0<\/p><p><strong>6. Analytics Consultant<\/strong><\/p><ul><li>Provide expert advice on data strategy, analytics solutions, and technology implementation.<\/li><li>Help organizations leverage data to drive business growth and innovation.<\/li><\/ul><p>\u00a0<\/p><p><strong>7. Quantitative Analyst (Quant)<\/strong><\/p><ul><li>Use statistical and mathematical models to assess financial risks and opportunities.<\/li><li>Develop trading algorithms and investment strategies.<\/li><\/ul><p>\u00a0<\/p><p><strong>8. Data Architect<\/strong><\/p><ul><li>Design and manage an organization\u2019s data architecture and frameworks.<\/li><li>Ensure data systems are scalable, secure, and meet business requirements.<\/li><\/ul><p><strong>9. Chief Data Officer (CDO)<\/strong><\/p><ul><li>Lead data management and governance strategies within an organization.<\/li><li>Drive data initiatives and ensure alignment with business goals.<\/li><\/ul><p>\u00a0<\/p><p><strong>10. AI Research Scientist<\/strong><\/p><ul><li>Conduct research on advanced AI and machine learning techniques.<\/li><li>Publish findings and contribute to the development of new technologies.<\/li><\/ul><p>\u00a0<\/p><p><strong>11. Industrial Engineer<\/strong><\/p><ul><li>Use data science techniques to optimize industrial processes and systems.<\/li><li>Develop simulation models to predict and enhance production outcomes.<\/li><\/ul><p>\u00a0<\/p><p><strong>12. Fraud Analyst<\/strong><\/p><ul><li>Use data analytics to detect and prevent fraudulent activities.<\/li><li>Implement fraud detection models and conduct investigations.<\/li><\/ul><p>\u00a0<\/p><p><strong>13. Customer Insights Analyst<\/strong><\/p><ul><li>Analyze customer data to understand behaviors and preferences.<\/li><li>Provide insights to improve customer experience and drive engagement.<\/li><\/ul><p>\u00a0<\/p><p><strong>14. Supply Chain Analyst<\/strong><\/p><ul><li>Optimize supply chain operations using data analysis.<\/li><li>Predict demand and manage inventory levels effectively.<\/li><\/ul><p>\u00a0<\/p><p>These roles cut across various sectors including but not limited to: technology, finance, healthcare, manufacturing, retail, and more, reflecting the versatility and high demand for professionals with expertise in data science and industrial analytics.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b576905 elementor-widget elementor-widget-spacer\" data-id=\"b576905\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Master of Technology (MTech) in Data Science and Industrial Analytics Duration (1 Year) Session (Weekday or Weekend) ABOUT THE PROGRAMME Modules &amp; Courses Career Prospect The 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. 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; \u00a0YEAR 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 \u00a0 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 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 ELECTIVES (Select a minimum of 6 or Maximum of 9 Credits) \u00a0 \u00a0 \u00a0 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 \u00a0 TOTAL \u00a0 \u00a0 18 Mode of Delivery Lectures, Seminars and Workshops Assignments and Exercises Individual and Group Presentations Assessment Class Test and Quizzes. Students will be assessed through regular class test and quizzes, which carry a weightage of 10%. Assignments, with a weightage of 10%. Mid-Semester Examination, which carry a weightage of 20% End-Semester Examination, which carry a weightage of 60% It is expected that by the time students\u2019 graduate from the programme, they should be: Able to competently use analytical tools like Python, R, Power BI for big data analysis and interpretation. Able to conduct practical work-based research Able to integrate fields within computer science, optimization and statistics to generate adept and well-rounded industrial solutions. Able to identify problems and evaluate the extents of such problems and recommend appropriate solutions. Able to design, maintain and develop data systems to suit current innovative demands Able to interpret data findings effectively to any audience orally, visually and written formats. \u00a0 Career Prospects 1. Data Scientist Develop and implement advanced data models and algorithms. Analyze large datasets to derive actionable insights and solve complex business problems. \u00a0 2. Machine Learning Engineer Design, build, and deploy scalable machine learning models. Optimize algorithms for performance and accuracy in various industrial applications. \u00a0 3. Data Analyst Perform statistical analysis and create reports to help businesses make informed decisions. Interpret data trends and patterns to provide strategic recommendations. Business Intelligence Analyst Develop and manage BI solutions for businesses. Create and maintain dashboards, reports, and data visualizations. \u00a0 4. Industrial Data Analyst Analyze manufacturing and production data to improve efficiency and reduce costs. Implement predictive maintenance models to minimize equipment downtime. \u00a0 5. Data Engineer Design, construct, and maintain data pipelines and databases. Ensure data integrity and accessibility for analysis and reporting purposes. \u00a0 6. Analytics Consultant Provide expert advice on data strategy, analytics solutions, and technology implementation. Help organizations leverage data to drive business growth and innovation. \u00a0 7. Quantitative Analyst (Quant) Use statistical and mathematical models to assess financial risks and opportunities. Develop trading algorithms and investment strategies. \u00a0 8. Data Architect Design and manage an organization\u2019s data architecture and frameworks. Ensure data systems are scalable, secure, and meet business requirements. 9. Chief Data Officer (CDO) Lead data management and governance strategies within an organization. Drive data initiatives and ensure alignment with business goals. \u00a0 10. AI Research Scientist Conduct research on advanced AI and machine learning techniques. Publish findings and contribute to the development of new technologies. \u00a0 11. Industrial Engineer Use data science techniques to optimize industrial processes and systems. Develop simulation models to predict and enhance production outcomes. \u00a0 12. Fraud Analyst Use data analytics to detect and prevent fraudulent activities. Implement fraud detection models and conduct investigations. \u00a0 13. Customer Insights Analyst Analyze customer data to understand behaviors and preferences. Provide insights to improve customer experience and drive engagement. \u00a0 14. Supply Chain Analyst Optimize supply chain operations using data analysis. Predict demand and manage inventory levels effectively. \u00a0 These roles cut across various sectors including but not limited to: technology, finance, healthcare, manufacturing, retail, and more, reflecting the versatility and high demand for professionals with expertise in data science and industrial analytics. The 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. The programme is of one year duration, made up of two semesters. 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