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This introductory course emphasizes quantitative measurements, the treatment of measurement errors and graphical analysis. A variety of experimental techniques should be employed. The experiments include studies of meters, the oscilloscope, mechanical systems, electrical and mechanical resonant systems, light, heat, viscosity etc., covered in PHY 101 and PHY 102. However, emphasis should be placed on the basic physical techniques for observation, measurements, data collection, analysis and deduction. PHY 108 - General Practical Physics II (1 Unit C: PH 45) Learning Outcomes At the end of the course, students should be able to: 1. conduct measurements of some physical quantities; 2. make observations of events, collect and tabulate data; 3. identify and evaluate some common experimental errors; 4. plot and analyse graphs; 5. draw conclusions from numerical and graphical analysis of data; and 6. prepare and present practical reports. Course Contents This practical course is a continuation of PHY 107 and is intended to be taught during the second semester of the 100 level to cover the practical aspect of the theoretical courses that have been covered with emphasis on quantitative measurements, the treatment of measurement errors, and graphical analysis. However, emphasis should be placed on the basic physical techniques for observation, measurements, data collection, analysis and deduction.

This introductory course emphasizes quantitative measurements, the treatment of measurement errors and graphical analysis. A variety of experimental techniques should be employed. The experiments include studies of meters, the oscilloscope, mechanical systems, electrical and mechanical resonant systems, light, heat, viscosity etc., covered in PHY 101 and PHY 102. However, emphasis should be placed on the basic physical techniques for observation, measurements, data collection, analysis and deduction. PHY 108 - General Practical Physics II (1 Unit C: PH 45) Learning Outcomes At the end of the course, students should be able to: 1. conduct measurements of some physical quantities; 2. make observations of events, collect and tabulate data; 3. identify and evaluate some common experimental errors; 4. plot and analyse graphs; 5. draw conclusions from numerical and graphical analysis of data; and 6. prepare and present practical reports. Course Contents This practical course is a continuation of PHY 107 and is intended to be taught during the second semester of the 100 level to cover the practical aspect of the theoretical courses that have been covered with emphasis on quantitative measurements, the treatment of measurement errors, and graphical analysis. However, emphasis should be placed on the basic physical techniques for observation, measurements, data collection, analysis and deduction.

This introductory course emphasizes quantitative measurements, the treatment of measurement errors and graphical analysis. A variety of experimental techniques should be employed. The experiments include studies of meters, the oscilloscope, mechanical systems, electrical and mechanical resonant systems, light, heat, viscosity etc., covered in PHY 101 and PHY 102. However, emphasis should be placed on the basic physical techniques for observation, measurements, data collection, analysis and deduction. PHY 108 - General Practical Physics II (1 Unit C: PH 45) Learning Outcomes On completion, the student should be able to: 1. conduct measurements of some physical quantities; 2. make observations of events, collect and tabulate data; 3. identify and evaluate some common experimental errors; 4. plot and analyse graphs; 5. draw conclusions from numerical and graphical analysis of data; and 6. prepare and present practical reports. Course Contents This practical course is a continuation of PHY 107 and is intended to be taught during the second semester of the 100 level to cover the practical aspect of the theoretical courses that have been covered with emphasis on quantitative measurements, the treatment of measurement errors, and graphical analysis. However, emphasis should be placed on the basic physical techniques for observation, measurements, data collection, analysis and deduction.

This introductory course emphasises quantitative measurements, the treatment of measurement errors, and graphical analysis. A variety of experimental techniques should be employed. The experiments include studies of meters, the oscilloscope, mechanical systems, electrical and mechanical resonant systems, light, heat, viscosity, etc., covered in PHY 101 and PHY 102. However, emphasis should be placed on the basic physical techniques for observation, measurements, data collection, analysis and deduction.

This introductory course emphasizes quantitative measurements, the treatment of measurement errors and graphical analysis. A variety of experimental techniques should be employed. The experiments include studies of meters, the oscilloscope, mechanical systems, electrical and mechanical resonant systems, light, heat, viscosity etc., covered in PHY 101 and PHY 102. However, emphasis should be placed on the basic physical techniques for observation, measurements, data collection, analysis and deduction. PHY 108 - General Practical Physics II (1 Unit C: PH 45) Learning Outcomes On completion, the student should be able to: 1. conduct measurements of some physical quantities; 2. make observations of events, collect and tabulate data; 3. identify and evaluate some common experimental errors; 4. plot and analyse graphs; 5. draw conclusions from numerical and graphical analysis of data; and 6. prepare and present practical reports. Course Contents This practical course is a continuation of PHY 107 and is intended to be taught during the second semester of the 100 level to cover the practical aspect of the theoretical courses that have been covered with emphasis on quantitative measurements, the treatment of measurement errors, and graphical analysis. However, emphasis should be placed on the basic physical techniques for observation, measurements, data collection, analysis and deduction.

This is a continuation of the experiments designed for PHY 101 and PHY 102 some of which have been covered under PHY 107.

Foundations of HCI. Concept underlying the design of HCI. Principles of GUI. GUI toolkits. System design methods. User conceptual models and interface metaphors. Human cognitive and physical ergonomics. Human-centred software evaluation and development. GUI design and programming. Lab Work: Illustration of the principles of HCI design. Practice on GUI design and programming. Demonstration of some GUI toolkits. Practical evaluation of GUIs

Business leadership. Digital marketing. Emerging trends in entrepreneurship. Business ethics. New venture creation process. Business feasibility planning. Market research. Business strategy. Business models and business plans. Technical presentations.

Introduction to big data. Small data vs. big data. What is big data? The evolution of data/big data. Big data characteristics-3Vs/6Vs. Unique features of big data. Importance of big data? Why does big data matter? Sources of big data. Formats of data. Applications of big data. Use case- issues and solutions. Big data technology. Big data as an opportunity. Example of big data. Big data statistics. Business intelligence vs. big data vs. data mining. Big data handling and techniques. Using the cloud for big data. Big data challenges/problems. How businesses are utilising big data. Big data technologies. Operational and analytical big data. Big data skills. Big data adoption. Big data analysis in practice. Case study session, preparation of case study report and presentation. The big data platform and key aspects. Governance for big data. Big data components. Big data driven organisational change and essential analytical tools and techniques. Develop big data solutions. System and management view of information and big data security. Requirements for information and big data security. Systems-design process and lifecycle security management of information systems. Basic policies on information security and methodologies. Information-security risk management, security policies, security in the systems-engineering process. Laws related to information security and management of operational systems. Apply machine learning techniques and other big data programming languages. Analyse big data recommendations. Cloud-based big data analysis. Lab work: Practice on data acquisition and how to initiate discovery on raw data using discovery systems. Learn Big Data analytics skills. Practical procedure for the crafting of an enterprise-scale cost-efficient Big Data and machine learning solution to uncover insights and value from data. Use the practical exercises to bridge the gap between the theoretical world of technology with the practical ground reality of building corporate Big Data and data science platforms. Hands-on exposure to Hadoop and Spark (or any of the BD tools), build machine learning dashboards using R and R Shiny, create web-based apps using NoSQL databases. Practical assignment of information and BD security.

Fundamental concepts of innovation and business ideas in general. Product development. Business leadership. Digital marketing. Entrepreneurial opportunities in IT. Legal issues and Business ethics. New venture creation process. Business feasibility planning. Market research. Business strategy. Business models and Business plans. Technical presentations. Report on a successful entrepreneurial outfit.