The Curriculum Design and Development course provides students on the Masters of Instructional Design and Technology with a theoretical and practical understanding of curriculum design, development, implementation, monitoring and evaluation. Your work as an Instructional designer is in balance if there is no curriculum you are designing those materials for.   Therefore, after this course, you will be able to explain the foundations of curriculum design, conduct a needs assessment or situational analyses for the viability of a curriculum, design a curriculum and evaluate its appropriateness.

The purpose of this course is to give students a wider understanding of principles of water resources planning and management The main objectives and contents of this course are based on understanding of water resource management approach, discussion on planning process and implementation of water resources projects, design and protection of watersheds as natural systems that benefit both human beings and the environment. Basic theories and design skills of rainwater harvesting systems and integrated water resources management (IWRM).

This module is designed to introduce students to the concept and design of hydraulic structures. Latter being anything whether fully submerged or partially submerged, that can be used to control water flow velocities, directions and depths, the elevation and slope of the stream bed. This module introduces to them the general configuration of waterways including their stability and maintenance characteristics. A weir, for example, is a type of hydraulic structure that can be used to pool water for irrigation, establish control of the bed (grade control) or, as a new innovative technique, to divert flow away from eroding banks or into diversion channels for flood control. The shape, size and other features of a hydraulic structure can vary widely for different projects, depending upon their functions. Hydraulic design procedures must govern the final design of all structures. This module will introduce the students to understand the basic principles of river engineering, and design of diversion works and cross-drainage and drop structures.

Please log into the module homepage for more details. 

This courses discusses different aspects related to:

• Water Quality Parameters, Water Quality Analysis, Water quality starndards
• Physical operations and units in Water Treatment
• Chemical processes and units in Water treatment

This module is designed to provide an advanced hydrology at watershed scale, including a study of flood hydrograph, flood routing, design flood estimation and flood control methods. It also looks at climate change and water resources sustainability as well as at human-water-climate interactions. This course focuses on modelling the rainfall-runoff process and its application to catchment areas. It will look at how water movement, storage and transformation on the Earth’s surface are influenced by landscape characteristics, including human modifications of those characteristics, and weather. This module serves as a guide for professional and competitive examinations for undergraduate students of water resources engineering.

The aim of this course is to introduce students to basic concepts of water regulation structures. The structures covered range from spillways to dams. It focuses mainly on their structural behavior, modes of failure, and design considerations.

Introduction

Hydraulic structures are anything that can be used to control water flow velocities, directions and depths, the elevation and slope of the stream bed, and general configuration of waterway including its stability and maintenance characteristics. A weir, for example, is a type of hydraulic structure which can be used to pool water for irrigation, establish control of the bed (grade control) or, as a new innovative technique, to divert flow away from eroding banks or into diversion channels for flood control. The shape, size and other features of a hydraulic structure can vary widely for different projects, depending upon their functions. Hydraulic design procedures must govern the final design of all structures. This module will introduce the students to understand the basic principles of river engineering, and design of diversion works and cross-drainage and drop structures.

The following is a brief indicative of the module of hydraulic structures I:

Topic 1: River engineering

• Some basic principles of open channel flow,
• River morphology and regime,
• River surveys,
• River flood routing,
• River improvement.

Topic 2: Diversion works

• Weirs and barrages
• Intakes
• Fish passes

Topic 3: Cross-drainage and drop structures

• Aqueducts and canal inlets and outlets
• Culverts, bridges and dips
• Drop structures.

Dear students,

Welcome to CWE3264 Water Supply and Sanitary Engineering module

The course gives students an introduction to the basic theories for water, wastewater, and stormwater. Water and wastewater systems, stormwater calculations, treatment of drinking water and wastewater, applying a selected set of methods for design and analysis.

Students will gain knowledge in:
- demand for water supply to households, industry and public servises
- the components of water supply systems from source to recipient
- the components in wastewater collection systems for both combined and separate systems
- urban hydrology and relationships between precipitation and runoff
- process theory for water and wastewater treatment
- characteristics of waste water (amount and composition)
- regulations for drinking water quality and effluent quality
- methods for treatment of water and waste water

Skills:
- calculate the demand needs for water supply to households, industry and public servises
- calculations on the components of water supply systems

Facilitators' details

UWIMPUHWE Charlotte, 0782862618, enguw2005@yahoo.com (module leader)

NIKUZE Marie Joselyne, 0788403078, nikuzemariejoselyne@yahoo.fr

This course intends to provide the students with fundamental knowledge and practical understanding of common techniques to process, present, and interpret data in water resources engineering. This knowledge and understanding will allow the students to select and apply the most appropriate techniques to summarize and organize data when they will be trying to study certain variables in water resources engineering. It also allows them to have an insight into the limitations of data collection, data analysis, and data interpretation. It will also allow students to understand more specifically, the consequences to the development and the calibration of mathematical models and other predictive tools in water resources engineering. Also, the consequences to the evaluation, the exploitation, and the management of the water systems will be discussed. The understanding of the data limitations and their consequences are useful in setting up the most appropriate data collection programs for specific water management and planning problems. Based on discussions of the different uncertainty sources, also a fundamental insight is given in the general process of mathematical modeling and of generating different data-driven scenarios.

The purpose of this course is to give students a wider understanding of principles of water resources planning and management The main objectives and contents of this course are based on understanding of water resource management approach, discussion on planning process and implementation of water resources projects, design and protection of watersheds as natural systems that benefit both human beings and the environment. Basic theories and design skills of rainwater harvesting systems and integrated water resources management (IWRM).

At the end of this course students will be able to explain changes that occur in watersheds—both natural and human-induced changes, to understand the basic theory, designing skills of the rainwater harvesting system;  and to  understand principles of Integrated Water Resources Management.

This lecture aims to show the direct link between data  systems and their use in economic modeling aimed to analyze specific policy issues. The lecture first illustrates the use of a SAM in the calculation of accounting and price multipliers and their use in the analysis of economy-wide effects of an injection. The second part of the lecture describes how to calibrate a static applied general equilibrium (AGE) model using a SAM and an IO table. It further explores how to apply this calibrated model in the analysis of alternative policy scenarios.

This module aims introduce computer networking concepts, focusing on the OSI and TCP/IP models, their layered approach, functions, and services. It covers network devices, transmission media, and network addressing schemes such as subnetting. Students will learn enhanced switching technologies, including VLANs, VTP, RSTP, 802.1q, and inter-VLAN routing. The module also provides hands-on skills in configuring and troubleshooting small, switched networks.

Dear Students,

Welcome to the Module of Computer Application and Data Management, Unit of Data Management and Analysis. The Module of Computer Applications and Data Management is a Module for the Year four students of Environmental Health Department. The Module is divided into two unit : Computer Applications and Data Management. The unit of Data management and analysis consists of using IBM SPSS to create a health data set, perform relevant data exploration and data analysis. The unit pays special consideration of the following:

• Structure of a questionnaire (DHS Rwanda 2014-2015 questionnaires): Consent forms, Approvals, questionnaire title, and questions ;
• Familiarize with IBM SPSS window: Data view & variable view
• Explore different menus in IBM SPSS
• Entering and importing data in IBM/SPSS
• Transforming & generating new variables from the existing ones in IBM/SPSS
• Perform descriptive & inferential statistics and related data interpretation: frequency tables, measures of central location (mean, mode, median), measures of variability ( standard deviation, variance, standard error of the mean); range, minimum, maximum, IQR; generating graphs (histograms, pie charts,..), use of chart builder; cross tabulations (2 X2 tables),, chi-square test, Fisher’s exact test, degrees of freedom, p-value and its interpretation; Simple linear regression; Correlation; One-way ANOVA; Use of Bonferroni test; Independent sample t-test
• Run a customized data analysis: select cases, merging data sets, perform customized analysis: Select cases in IBM SPSS and run related analysis; and merging datasets in IBM SPSS (merging files)

1.     Course description

This advanced module introduces the learners to the principles and practice to gain knowledge of algorithms and methods of Data Mining and Knowledge Discovery. It aims to cover each stage of the Data Mining and Knowledge Discovery, including preliminary data exploration, data cleansing, pre-processing and the various data analysis tasks that fall under the heading of data mining.

The ongoing rapid growth of online data due to the Internet and the widespread use of large scale databases have created an immense need for Data Mining and Knowledge Discovery methodologies. The challenge of extracting knowledge from data draws upon research in statistics, databases, pattern recognition, machine learning, data visualization, optimization, and high-performance computing, to deliver advanced business intelligence and web discovery solutions.

2       Learning Outcomes

A. Knowledge and Understanding

At the end of the programme students should be able to demonstrate knowledge and understanding of

1. Principles applied in the development of Data Mining and Knowledge Discovery.
2. Current standards of practice used in developing Data Mining for systems.
3. Use of software quality metrics and benchmarks in the development computer algorithms based on Data Mining and Knowledge Discovery.

B. Cognitive/ Intellectual Skills/ Application of Knowledge

At the end of the programme students should be able to:

1.  Apply data mining software engineering standards, metrics and bench marks to produce innovative designs of computer, software data mining systems and components.

2.  Critically assess data pre-processing and exploration techniques to specified Data Mining and Knowledge Discovery work done by others.

C. Communication/ICT/Numeracy/Analytic Techniques/Practical Skills

At the end of the programme students should be able to: 

1. Specify data mining models prepare relevant technical documents.

2. Prepare technical reports and deliver technical presentations on Knowledge sharing at an advanced level.

3.  Analyse, evaluate and interpret existing data mining algorithms and apply them to the solution of practical real problems.

4.      Use appropriate software tools and packages appropriate to Data Mining and Knowledge Discovery analysis and research.

D. General transferable skills

At the end of the programme students should be able to:

1. Involve in research and development on Data Mining and Knowledge Discovery.

2. Carry out independently a sustained investigation and research in Knowledge 

Discovery.

3. Draft &Evaluate, select and interpret patterns and knowledge discovered as a result of applying Knowledge Discoverydocuments effectively (written, verbal, drafting, sketching etc.)

3       Indicative Content

• Data Mining Overview

Background to data mining; Understanding the differences between data, information and knowledge; Objectives of data mining; Knowledge Discovery in databases; Data Mining Applications - Marketing, Finance, Banking, Fraud detection, Manufacturing, Telecommunications, discovering knowledge on the Internet. Current state of data mining.

• Principles of Data Mining

Data mining process/approaches e.g. Crisp-DM, SEMMA; Categories of data mining problems; Evaluation and interpretation of output patterns.

• Data Mining Model Functions

Investigate some of the following supervised and unsupervised techniques: classification, clustering, dependency modelling, sequence modelling, data summarisation, and change and deviation analysis/anomaly detection. Matching the model function(s) to the data mining problem at hand.

• Data Mining Model Representations

Using a data mining tool to mine the data, investigate some of the following data mining representations: decision trees and rules; neural networks; machine learning; case-based reasoning; data visualisation: clustering, hierarchies, and self-organised networks, geo-positioning/landscaping.

• Interpretation & Refinement

Interpreting patterns, removing redundant patterns, translating patterns, refining the data mining process based on knowledge learned. Testing and validating the accuracy of the models using various techniques e.g. simple split, k-fold cross-validation, bootstrapping.

• Data Mining Software

Using data mining and forecasting software (e.g. SAS, RapidMiner, R, SPSS) to manipulate algorithms, build and test models for a variety of data sets.

4       Learning and Teaching Strategy

A course handbook will be provided in advance and this will contain in depth information relating to the course content. This will give an opportunity to the students to prepare the course. The lecture materials will be posted on the web page that will also contain comprehensive web links for further relevant information. The module will be delivered through lectures, tutorial/practice sessions and group discussions. In addition to the taught element, students will be expected to undertake a range of self-directed learning activities.

Students should be able to compare and contrast the differences between the major data mining tasks, in terms of their assumptions, requirement for a specific kind of data, and the different kinds of knowledge discovered by algorithms performing different kinds of task.

The students should also be able to identify which data mining task and which algorithm is the most appropriate for a given data mining project, taking into account both the nature of the data to be mined and the goals of the user of the discovered knowledge

5       Assessment Strategy

In-Course and End of Module assessment add up to 100% and includes:

• Fundamental concepts-seminar, oral examination
• Basis of project management –seminar, oral examination
• Project management –seminar, oral examination
• Management of development project-seminar, oral examination
• Project-group assignment, written report and seminar 

As this is a Theoretical and Practical module: The Final assessment shall include 50% of continuous and 50% of End of Module assessment.

The assessments shall be made 50% each for practical and theoretical aspects.

For Example:

one quiz (5%), one/two practical assignment (10%), one mini project for presentation (10%), one tutorial session (5%), short practical test (10%) and a short written test (10%) followed by final assessment (50%) of End of Module Examination divided equally into practical viva-voce and theoretical examination.

6       Assessment Criteria:

For the assignment, criteria will be drawn up appropriate to the topic, based on the learning outcomes.

Databases are fundamental building blocks of most IS systems, and there are a range of advanced developments in the database area. This course covers database concepts and the use of relational database systems. This course emphasizes implementation issues of relational database systems, and provides an insight into some of the recent developments in database technology, such as distributed databases, object-oriented databases and concurrency etc.

The owner of the course is Mr. Eric HITIMANA. An Assistant Lecturer

Quality information is at the heart of decision making and the running of all organisations. Information and data, as corporate resources, are shared between many groups and individuals. This there is a need for these resources to be properly administered and managed. A database system, is the major component for enabling the achievement of these needs. The course intends to provide the principles, knowledge, understanding and skills needed by a computing professional to positively contribute to the success of running a business and enabling it to achieve its mission and objectives. The main aims of this course is to introduce students to the requisite theory and practice of database technology and the applications of the technology in generic and specific domains.

Hello BIT II Students, University of Rwanda, Department of Business Information Technology.

As the Module Leader, I would like to welcome you all to this module which will run in the 1st Trimester of the Academic Year 2019-2020.

A database system is a major component for enabling the achievement of these needs. The course intends to provide the principles, knowledge, understanding, and skills needed by a computing professional to positively contribute to the success of running a business and enabling it to achieve its mission and objectives. The main aims of this course are to introduce students to the requisite theory and practice of database technology and the applications of the technology in generic and specific domains.

Successful completion of this module will enhance the student's ability to:

1. Give an appreciation of the role of methodologies in designing and implementing information systems, and to consider and compare different methodologies.
2. Learn and apply methodologies for conceptual, logical and physical database design.
3. Acquire skills in solving business problems using the fundamentals of database modeling, enterprise analysis, and design.
4. Provide knowledge of the modeling techniques required to construct fully validated systems and to enable the student to apply these techniques.
5. Introduce implementation and management issues as well as database programming languages and standards using various database management.

In summary, having successfully completed the module, students should be able to:

1. Understand about the relational database systems
2. Querying the databases
3. Management of databases

Both theoretical concepts and practical sessions using MS Access and MySQL as the DBMS software will be covered in this module.

Once again, welcome to this module of Database Technology.

Module Leader