Higher Certificate in Bioscience

Code: 120666 • NQF 5 • 120 credits (≈ 1200 hours)

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Programme: Bachelor of Commerce in Tourism Management
Programmes & Pricing
About this programme

Provides foundational knowledge and practical techniques in bioscience. Prepares learners for roles such as laboratory technician or assistant, or for further studies in biological sciences.

Modules
  • Bioethics and Communication – 18 credits(≈ 180 hours)
    Code: ELO6
    Covers scientific communication and ethical standards.
  • Biostatistics – 17 credits(≈ 170 hours)
    Code: ELO3
    Applies problem-solving and reasoning in bioscience.
  • Introduction to Biotechnology – 17 credits(≈ 170 hours)
    Code: ELO2
    Explores development and evolution of scientific knowledge in bioscience.
  • Laboratory Techniques in Experimental Bioscience – 17 credits(≈ 170 hours)
    Code: ELO7
    Applies ICT and data analysis in bioscience labs.
  • Principles of Cell Biology – 17 credits(≈ 170 hours)
    Code: ELO1
    Covers core bioscience concepts and principles.
  • Professional Skills Development – 17 credits(≈ 170 hours)
    Code: ELO5
    Supports self-evaluation and learning strategies.
  • Project Planning – 17 credits(≈ 170 hours)
    Code: ELO4
    Develops teamwork and project collaboration skills.
Learning Outcomes (28)
Linked to modules: 28 of 28
  • 1.1: Identify, describe, and explain core concepts and principles of the bioscience discipline.
  • 1.2: Discuss the relationships among the bioscience core concepts and principles.
  • 1.3: Identify the range and limits of the core bioscience concepts and principles.
  • 1.4: Apply the core bioscience concepts and principles to standard problems.
  • 2.1: Examine the significance of contested scientific knowledge in a contemporary context.
  • 2.2: Apply the generally accepted scientific information and ideas to solve problems in bioscience.
  • 3.1: Reflect on thinking and reasoning processes in the bioscience field.
  • 3.2: Apply logical thinking and identify naive and flawed scientific reasoning.
  • 3.3: Develop a self-conscious capacity to judge when a problem has been adequately solved.
  • 3.4: Formulate, analyse, and solve concrete and abstract problems, in familiar and unfamiliar contexts.
  • 3.5: Apply knowledge of theory to real-world contexts.
  • 3: Apply ICT appropriate to the bioscience discipline, e.g., for computational applications; simulation applications; pattern recognition; automation and control; managing large volumes of data.
  • 4.1: Successfully and effectively contribute to group work within various activities during module assignments.
  • 4.2: Communicate the outcomes of scientific group work effectively and respect the contributions of each group member.
  • 4.3: Apply organisational skills in managing group work.
  • 5.1: Apply appropriate study skills in learning from text, note-taking, summarising, analysis, and synthesis.
  • 5.2: Develop and use effective learning strategies which suit personal needs and contexts in both summative and formative assessment procedures.
  • 5.3: Apply effective time management by completing and submitting tasks/assignments within the agreed time frame.
  • 6.1: Correctly use scientific language to produce clear and coherent written documents in line with scientific conventions.
  • 6.2: Use statistical measurements appropriately and critically and illustrate an understanding by means of the conclusions presented.
  • 6.3: Present verbal scientific information in front of others.
  • 6.4: Use appropriate referencing conventions, avoid plagiarism, and respect intellectual property.
  • 6.5: Correctly and appropriately use non-verbal forms in various module assignments and present information using visual aids and PowerPoint Slide Shows.
  • 6.6: Produce a report on a laboratory project according to accepted standards.
  • 7.1: Perform tasks related to basic computer literacy skills within a laboratory setting.
  • 7.2: Critically assess the validity of ICT solutions for problems posed by the bioscience discipline.
  • 7.3: Apply ICT appropriate to the bioscience discipline, e.g., for computational applications; simulation applications; pattern recognition; automation and control; managing large volumes of data.
  • nan
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