Programme Description
Aquaculture is an art and science that deals with farming of aquatic organisms (e.g. fishes, shrimps, seaweeds, echinoderms, and crocodiles). Aquaculture and Aquatic Sciences is an essential knowledge and practice in enhancing the sustainable availability of fish resources and maintaining the aquatic ecological goods and services. Aquaculture uses artificial techniques for rearing of both aquatic plants and animals in a confined artificial environment whether earthen ponds, concrete ponds, tanks, raceways, pens, or floating cages. On the other hand, aquatic environment like lakes, rivers and ocean provides food and income to fisherfolk at local level and contributes to national export and global food security. World human population is increasing while many natural resources are not increasing at the same rate; causing depletion of such resources in their natural settings. Following this, there is a need to establish artificial production of natural resources that are over utilized by human population in order to reduce pressure on natural resources. Furthermore, it is important to train experts who can lead others in such operations. Fish is one of the natural resources that are highly utilized by human in an unsustainable way, thus causing depletion of different species of fish. However, many species of fresh water fishes can be farmed. Thus, it is important to train people on basic principles of fish farming to improve food security as well as generation of household income. Notwithstanding the human related impacts to fish populations, global climate change is also contributing substantively to the decline of fish population due to changes in water body environment (e.g. salinity, temperature, dissolved oxygen) which may affect plankton that fishes feed on. Inland water bodies (lakes and rivers) are polluted by heavy metals from mining industries which causes health hazards to human who feed on fishes and other aquatic resources. Therefore, it is important to farm fishes in local areas where such pollution cannot contaminate such local ponds. The BSc. Aquaculture and Aquatic Science Programme emphasize on practical production of fish in local areas where contamination is minimal in order to improve food security as well as household income. The Bachelor of Science in Statistics is geared towards producing graduates who are well versed with the skills necessary to assist in planning, decision making, and research within various institutions. The curriculum provides training in general statistical techniques, specialized statistical methods, aspects of statistical management which enable graduates to be employed as statisticians in any corporate or public sectors or in academic institutions. In addition, they can also serve as bank officers, quality control officers, economists and other related professionals.
Learning Outcomes
- Apply concepts, theories, and methodologies to tackle emerging problems related to aquaculture and aquatic science.
- Access, analyse, synthesize, and evaluate information objectively and act professionally and ethically towards clients, the public, and agency personnel in the aquaculture sector.
- Apply knowledge to advice authority in sustainable utilization of aquatic resources, proper management, and policy development.
- Conduct research in aquaculture and aquatic science fields to generate sustainable solutions for aquatic resource utilization.
- Apply hands-on experience in aquatic sampling inventory and measurement techniques.
- Apply modern technology, products, and services to optimize production of aquatic products. After the completion of the programme, graduates are expected to:
- Demonstrate the ability to handle and manipulate data for decision making processes.
- Manage statistical activities at different offices and institutions: public or private.
- Plan and conduct sample surveys and experimental designs.
- Demonstrate the ability to write reports and provide statistical service consultancy.
- Demonstrate competence in using various statistical software packages for data analysis.
- Demonstrate ability to identify, design, and manage different social and economic projects.
Programme Structure
Year 1
Semester One
| Code |
Course Title |
Status |
Credits |
| AA 111 |
General Aspects in Aquaculture and Aquatic Sciences |
Core |
7.5 |
| BI 112 |
Invertebrate Zoology |
Core |
1E+1 |
| BI 113 |
Ecology I |
Core |
7.5 |
| DS 102 |
Development Perspective |
Core |
7.5 |
| CH 115 |
Chemistry for Life Science |
Core |
1E+1 |
| LG 102 |
Communication Skills |
Core |
7.5 |
| MT 110 |
Introduction to Information and Communication Technology |
Core |
7.5 |
| BI 111 |
Introductory Cell Biology and Genetics |
Core |
1E+1 |
Semester Two
| Code |
Course Title |
Status |
Credits |
| AA 121 |
Practical Training, I |
Core |
7.5 |
| BI 122 |
Chordate Zoology |
Core |
1E+1 |
| BI 126 |
Introduction to Parasitology |
Core |
7.5 |
| BI 125 |
Environmental Science |
Core |
7.5 |
| BI 304 |
Estuarine and Wetland Ecology |
Core |
7.5 |
| AA 123 |
Aquatic Environment and Biodiversity |
Core |
7.5 |
| AA 124 |
Principles and Practices of Swimming and Snorkeling |
Core |
7.5 |
| BI 124 |
Introduction to Microbiology |
Elective |
7.5 |
Year 2
Semester One
| Code |
Course Title |
Status |
Credits |
| AA 216 |
Mollusc and Crustacean Culture |
Core |
7.5 |
| AA 212 |
Aquatic Microbiology |
Core |
7.5 |
| AA 213 |
Fish Nutrition and Feed Technology |
Core |
7.5 |
| BI 215 |
Biostatistics I |
Core |
1E+1 |
| AA 215 |
Mangrove and Seagrass Ecosystems |
Core |
7.5 |
| AA 211 |
Principles of Aquaculture |
Core |
7.5 |
| AA 219 |
Aquatic Pathology |
Core |
7.5 |
| AA 214 |
Fish Processing Technology and Quality Assurance |
Core |
7.5 |
| BI 213 |
Ecology II |
Elective |
1E+1 |
Semester Two
| Code |
Course Title |
Status |
Credits |
| AA 221 |
Non-Food Aquaculture |
Core |
7.5 |
| BI 222 |
Introduction to Research Methodology |
Core |
7.5 |
| AA 224 |
Oceanography |
Core |
7.5 |
| AA 226 |
Practical Training II |
Core |
7.5 |
| AA 227 |
Aquatic Field Practical |
Core |
7.5 |
| AA 225 |
Aquatic Resources and Management |
Core |
7.5 |
| AA 228 |
Algal Biology and Culture |
Core |
7.5 |
| AA 222 |
Mariculture |
Elective |
7.5 |
Year 3
Semester One
| Code |
Course Title |
Status |
Credits |
| AA 318 |
Research Project |
Core |
7.5 |
| AA 311 |
Fish Genetics and Breeding |
Core |
1E+1 |
| AA 314 |
Larviculture and Larval Food Production |
Core |
7.5 |
| AA 315 |
Introduction to Remote Sensing and GIS |
Core |
7.5 |
| AA 317 |
Law of the Sea and Inland Waters |
Core |
1E+1 |
| AA 316 |
Aquatic Pollution and Management |
Core |
1E+1 |
| AA 319 |
Coral Reef Biology and Ecology |
Elective |
7.5 |
| AA 313 |
Aquatic Toxicology |
Elective |
7.5 |
Semester Two
| Code |
Course Title |
Status |
Credits |
| AA 320 |
Research Project* |
Core |
7.5 |
| EM 306 |
Small Business and Entrepreneurship |
Core |
1E+1 |
| AA 323 |
Seed Production and Hatchery Management |
Core |
1E+1 |
| BI 301 |
Ichthyology |
Core |
7.5 |
| BI 327 |
Environmental and Social Impact Assessment |
Core |
7.5 |
| AA 325 |
Integrated Coastal Zone Management |
Core |
1E+1 |
| AA 324 |
Aquaculture and Environment |
Elective |
7.5 |
| BI 306 |
Conservation Biology |
Elective |
7.5 |
Year 1
Semester One
| Code |
Course Title |
Status |
Credits |
| ST 1100 |
Statistical Computing |
Core |
9 |
| ST 1101 |
Basic Statistics |
Core |
9 |
| CP 111 |
Principles of Programming |
Core |
9 |
| MT 1101 |
Foundations of Analysis |
Core |
9 |
| MT 1102 |
Linear Algebra and Applications |
Core |
10.5 |
| LG 102 |
Communication Skills |
Core |
7.5 |
| DS 102 |
Development Perspectives |
Core |
7.5 |
Semester Two
| Code |
Course Title |
Status |
Credits |
| ST 1201 |
Probability Theory |
Core |
9 |
| ST 1202 |
Operations Research I |
Core |
9 |
| ST 1203 |
Basic Demographic Models |
Core |
9 |
| MT 1201 |
Mathematical Analysis I |
Core |
9 |
| MT 1202 |
Ordinary Differential Equations |
Core |
9 |
| EN 126 |
Statistical Methods in Economics I |
Core |
7.5 |
| CP 123 |
Introduction to High Level Programming |
Core |
9 |
Year 2
Semester One
| Code |
Course Title |
Status |
Credits |
| ST 2101 |
Probability Distributions |
Core |
10.5 |
| ST 2102 |
Statistical Inference |
Core |
10.5 |
| ST 2103 |
Statistical Methods for Quality Control |
Core |
9 |
| ST 2104 |
Operations Research II |
Core |
9 |
| ST 2105 |
Research Methods and Practice |
Core |
7.5 |
| ST 2299 |
Practical Training I |
Core |
7.5 |
| EN 216 |
Statistical Methods in Economics II |
Core |
7.5 |
Semester Two
| Code |
Course Title |
Status |
Credits |
| ST 2201 |
Sampling Theory and Methods |
Core |
9 |
| ST 2202 |
Regression Analysis I |
Core |
9 |
| ST 2203 |
Actuarial Statistics |
Core |
9 |
| ST 2204 |
Non-Parametric Methods |
Core |
9 |
| ST 2205 |
Time Series and Forecasting |
Core |
9 |
| ST 2206 |
Financial Statistics |
Core |
7.5 |
| CP 121 |
Introduction to Database Systems |
Core |
9 |
Year 3
Semester One
| Code |
Course Title |
Status |
Credits |
| ST 3101 |
Design and Analysis of Experiments |
Core |
9 |
| ST 3102 |
Introduction to Multivariate Analysis |
Core |
10.5 |
| ST 3104 |
Categorical Data Analysis |
Core |
7.5 |
| ST 3105 |
Stochastic Processes |
Core |
9 |
| IM 315 |
Management Information Systems for Statisticians |
Core |
7.5 |
| EME 211 |
Small Business Management and Entrepreneurship |
Core |
9 |
| ST 3299 |
Practical Training II |
Core |
7.5 |
Semester Two
| Code |
Course Title |
Status |
Credits |
| ST 3201 |
Biostatistics and epidemiology |
Core |
10.5 |
| ST 3202 |
Applied Spatial Statistics |
Core |
9 |
| ST 3296 |
Statistical Project |
Core |
10.5 |
| ST 3206 |
Regression Analysis II |
Core |
10.5 |
| ST 3204 |
Panel Data Analysis |
Elective |
10.5 |
| ST 3205 |
Statistical Methods for Projects Evaluation |
Elective |
10.5 |
| CS 329 |
Big Data Analysis |
Elective |
9 |
| CP 224 |
Database Management System |
Elective |
9 |
Special Programme Requirements
• PT requirement, semester II: Year I and Year II. • Field Requirement, semester II: Year II. • Special Project (Research Report) semester I and II: Year III.Bachelor of Science in • The first Field Practical Training (FPT) will be conducted at the end of first academic year, where students will be required to attend PT at The University of Dodoma (in- house practical training sessions) for four weeks. Students will be given practical training on some software on computing laboratory. The cost for this training per student is TZS 300,000 for four weeks. • The second Field Practical Training (FPT) will be conducted in different government and private institutions for eight weeks at the end of second year academic year. The cost for this training per student is TZS 600,000 for eight weeks. • Special Project (ST 320 Statistics Project) will be done from the beginning of Semester II of Year III. The cost for the Special Project per each student is TZS 300,000 for one semester. • Special Faculty requirement in Semester I of Year I. The amount per student is TZS 100,000.
