- Meeting Time: Fridays 2:30 – 5:25 pm
- Classroom: Vertical Campus 6-140
- Instructor: Anh Luong — 11-250 A — email@example.com
- Office Hours: Thursdays 4 – 5 pm & by appointment
- Textbook: Starting Out with Python by Tony Gaddis, 4th edition, 2015, Package ISBN-13: 9780134652559 (3rd edition or used books are okay too).
- Software: Python 3.7 (let me know if you have trouble installing)
The course serves as an introduction to Python programming for analytics, targeted at students with no programming knowledge. As such, the class will first focus on basic programming concepts. Once the students are comfortable with the basics, they will learn how to use Python for data analytics tasks such as data scraping, wrangling, and analysis. Upon successful completion of this course, students will be able to:
- Apply the fundamentals of programming and develop a computational approach to solving problems
- Write and run programs in the programming language Python
- Demonstrate literacy in practical data science (including the use of Python programming language) in enterprises
- Describe the critical role that data science plays in different organizations
- Develop programs in a suitable programming language (Python) that help in data analytics
Please note that this syllabus is subject to change. Changes will be notified through announcements on the course website, via email and Blackboard.
In-class sessions will typically be composed of:
- Code Demos
- In-class Exercises
Homework assignments will be a combination of several or all of the following:
- Readings and/or Videos
- Datacamp Videos + Exercises
- Online Quizzes
- Other Coding Exercises
You are required to regularly check their Baruch emails, Blackboard, and the course website to keep track of what is going on in the class. Important information about the class, assignment details and policies will be regularly announced via Blackboard, the course website, and Baruch emails and you are expected to be up to date with these announcements.
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- REQUIRED: Starting Out with Python by Tony Gaddis, 4th edition, 2015, Package ISBN-13: 9780134652559 (3rd edition or used books are okay too).
- Python for data analysis [electronic resource from Baruch Library available free of cost to us] / Wes McKinney, O’Reilly, ©2013.
- Python Data Analytics: Data Analysis and Science Using Pandas, Matplotlib, and the Python Programming Language, by Fabio Nelli Apress 2015 ISBN:9781484209592 [electronic resource from Baruch Library available free of cost to us]
Academic Integrity Statement
The Paul H. Chook Department of Information Systems and Statistics fully supports Baruch College’s policy on Academic Honesty, which states, in part:
“Academic dishonesty is unacceptable and will not be tolerated. Cheating, forgery, plagiarism, and collusion in dishonest acts undermine the college’s educational mission and the students’ personal and intellectual growth. Baruch students are expected to bear individual responsibility for their work and to uphold the ideal of academic integrity. Any student who attempts to compromise or devalue the academic process will be sanctioned.”
Additional information can be found at http://www.baruch.cuny.edu/academic/academic_honesty.html.
Deliverables that are required to be completed individually should not involve collaboration with other students. Deliverables that are required to be completed in a team should not involve collaboration across teams. Unauthorized collaborative work will result in appropriate disciplinary action. Academic sanctions in this class will range from a grade of F on the assignment to a grade of F in the course. A report of suspected academic dishonesty will be sent to the Office of the Dean of Students.