This eight-hour workshop introduces students to the data science workflow using Python. The workshop will cover four topics: The Python language essentials, data transformation, data visualization and modeling. The workshop will cover mainstream Python packages including Pandas, Altair, and Scikit-learn among others. Each topic is covered in one two-hour flipped classroom session. The sessions are centered around data-related problems. Students will work in groups to answer questions and gain understanding of selected data sets. As a workshop project, students will turn in an interactive notebook that presents a comprehensive analysis of a selected data set. The notebook should cover all learned topics including data transformation, visualization and modeling. Extensive preparation prior to every session is required. A basic understanding of statistics and computer programming is required too.
Instructor: Hani Safadi Email: hanisaf@uga.edu Phone: 706-542-3341
Office: Benson C420 Office hours: Mondays and Wednesdays 10:30 – 11:10am and 1:10 – 1:50pm
Location: Correll 0315 Time: 2:00-4:00pm
Webpage: https://github.com/hanisaf/python-bootcamp
Slack workspace: https://uga-python-bootcamp.slack.com
Dates: Wednesdays January 16, January 23, January 30, February 6 2019
Basic knowledge of computer programming and statistics
- Python language fundamentals
- Data management and transformation
- Information visualization
- Modeling and machine learning
There are no books required for this course. The following two free books by Jake VanderPlas are useful:
- A Whirlwind Tour of Python: a fast-paced introduction to essential features of the Python language.
- Python Data Science Handbook: a complete coverage for modern Python tools for researchers and data scientists.
Python 3.7 or higher is required. The easy way to install it is with Anaconda distribution. Several other packages including Pandas, Altair and Scikit-learn are needed among others. These packages can be downloaded and installed by downloading the requirements.txt file in this repo then running the following command:
- pip install -r requirements.txt
Alternatively, the code of this repository can be run online with Binder. Please note that Binder is a third-party site and there are no guarantees about the service.
Several other companies provide cloud services for running Python notebooks.
Attendance and participation are required for this course.
- 30% quizzes
- 70% project
- A minimum grade of 70% is required for passing
As a University of Georgia student, you have agreed to abide by the University's academic honesty policy, "A Culture of Honesty, " and the Student Honor Code. All academic work must meet the standards described in "A Culture of Honesty." Lack of knowledge of the academic honesty policy is not a reasonable explanation for a violation. Questions related to course assignments and the academic honesty policy should be directed to the instructor.
The course syllabus is a general plan for the course; deviations announced to the class by the instructor may be necessary.