Industry Applications & Capstone in Academia
This course is designed for final-year students, researchers, and professionals seeking real-world research experience. It blends AI tools with practical projects across health, finance, and data science. Learners will build a research portfolio, analyze real data, and prepare for academic or industry roles.
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- Basic understanding of research concepts
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Access to AI tools (ChatGPT, DeepSeek, Julius AI)
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Microsoft Excel or Google Sheets
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Internet connection and a laptop or desktop
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Willingness to complete hands-on activities
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Final-year university students working on thesis or capstone projects
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Graduate-level students in fields like health, economics, education, environmental science, and fintech
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Research assistants, data analysts, or junior professionals seeking industry-relevant skills
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Anyone preparing for academic defenses, job interviews, or professional project presentations
- Description
- Curriculum
- Reviews
- Grade
This capstone course is designed to help students transition from academic knowledge to practical, real-world applications in research, industry, and career development. Through 13 carefully designed modules, learners will engage in activities such as clinical trial data analysis, social network mapping, climate modeling, fintech forecasting, thesis defense prep, portfolio development, and more.
By the end of the course, students will have produced a publishable research project, developed a professional LinkedIn portfolio, and built confidence in using research for real-life problem-solving.
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5
Introduction to biostatistics -
6
Basics – Epidemiology & Biostatistics
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7
Introduction to Biostatistics -
8
Descriptive Statistics -
9
Mean, Median, Mode, Variance & SD (With Examples)
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10
Quiz on Descriptive Statistics
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11
Introduction – What is the Mean?
Lesson Goal:
To help you understand what the mean is, how to calculate it, and where it fits in real life—using simple examples you see every day.
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12
Let’s Practice Together -
13
Calculating Mean, Median, and Mode by Hand
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14
Calculating Mean, Median, and Mode by excel
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15
Assignment
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16
Outliers
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17
How to Find Outliers with Excel
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18
Assignment Questions
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19
Dispersion
By the end of this lesson, you will be able to:
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Understand what dispersion means in statistics
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Explain why knowing the “spread” of data is important in medical and health research
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Recognize the key types of dispersion (Range, Variance, and Standard Deviation)
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20
Standard Deviation, Variance, Range and Interquartile Range - Measures of dispersion
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21
Range, Variance, Standard Deviation in Excel
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22
Normal Distribution & Bell Curve
By the end of this lesson, students will be able to:
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Explain what a normal distribution is and why it matters in biostatistics
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Recognize the shape of a bell curve
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Use Excel to create a histogram and fit a normal curve
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Apply understanding of “normality” to variables like BMI and cholesterol
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23
How to Plot a Normal Distribution (Bell Curve) in Excel – with Shading!
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24
Skewness - Right, Left & Symmetric Distribution - Mean, Median, & Mode With Boxplots - Statistics
By the end of this lesson, you should be able to:
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Define skewness and kurtosis in simple terms
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Understand how these concepts describe data shape
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Identify skewness/kurtosis in Excel charts
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Interpret what skewness and kurtosis tell us about clinical datasets
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25
How to Create Skewed Bell Curve in Excel
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26
Assignment: Creating a Skewed Bell Curve in Excel
