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Fundamentals of Data Science

Fundamentals of Data Science
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  2. SUMMER@AUC
  3. College Bound: AUC
  4. Fundamentals of Data Science

Liberal Arts Education

Unlock the power of information and lead the next wave of global innovation.

Through engaging lectures, hands-on computer labs, practical activities and real dataset applications, students will discover how data can be transformed into valuable insights that drive decisions and innovation. Whether you are planning a career in science, technology, business, or any data-driven industry, this course will provide a strong and exciting foundation in the rapidly growing world of data science.

 

Learning Outcomes

  • Demonstrate a deeper understanding of statistics relevant to the domain
  • Demonstrate an understanding of the fundamentals of R
  • Demonstrate an ability to use some of the relevant tools and features of R
  • Demonstrate a further understanding of techniques for data gathering, preparation and integration
  • Be familiar with more details of Exploratory Data Analysis, with a deeper understanding of data analysis
  • Demonstrate an understanding and usage of some basic machine learning algorithms
  • Be familiar with some data visualization techniques in R
  • Exhibit and ability to apply learned concepts using a case study and submit (write) an end of term project
  • Exhibit maturity with some of the ethical issues surrounding the domain.


Duration and Location

  • July 26 - August 13, 2026
  • Application Deadline: One week before the course starts
  • Sessions will run daily from 9 am - 3 pm
  • AUC New Cairo campus
  • Fridays and Saturdays off

 

Apply Now


Fees

  • $1,000 (price includes field trips) - This amount is equivalent to half the price of a regular undergraduate course.
  • 10% discount offered for siblings.
  • Egyptian students can pay the equivalent amount in Egyptian pounds.


Current AUC Equivalent

This course is one of the required courses for the Data Science major.

Note: Program requirements may change by the time the student applies to AUC. If this course is no longer a requirement for the major, it will be counted as an elective course.


Course Transfer

  • Upon taking this course, you will receive a certificate of completion from AUC.
  • The course is equivalent to 3 credit hours. Only students who pass the course will be able to transfer these 3 credits when they enroll at AUC. In case of transferring the course to other universities, their transfer assessments will apply. 


Requirements

  • An English writing sample (at least 750 words): essay or reflection.
  • A copy of your report card for the past two years of school.
  • A recommendation letter from a high-school teacher within the past academic year, if available.


Transportation 

The AUC Bus Service is available for extra fees. Details on the schedule will be shared before the program’s start date.


Accommodation

Accommodation is offered at the University Residences in case needed. 


About the Instructor

Sara Osama
Sara Osama is an assistant professor in the Statistics Department, Faculty of Economics and Political Science at Cairo University. She is also an adjunct faculty member in the Department of Mathematics and Actuarial Science at The American University in Cairo (AUC). Osama has taught a variety of courses in data analysis, statistics and computational tools. She is passionate about helping students develop practical skills that prepare them for the growing opportunities in data science. With expertise in statistics and data science, Osama has a strong interest in applying data-driven approaches to solve real-world problems and promote evidence-based decision making.


AUC Refund Policy

A 100% refund of the program fees will be granted if the request is submitted at least two weeks before the course start date, or if the request is due to one of the following reasons:

  • Course cancellation
  • Medical withdrawal
  • Visa denial

A 75% refund will be granted if the request is submitted within the last two weeks before the course start date.

No refund will be issued if the request is submitted after the end of the last working day (4 pm) and before classes begin, including the weekend prior to the course start date, or after the course has begun.