605.206.81 - Introduction to Programming Using Python

Course Structure

This is an online, asynchronous course with the content divided into 14 1-week Modules. The only synchronous component of the course is Office Hours, which you can read more about in the Office Hours section below. Modules officially begin on Monday at 12:01AM EST and end on Sunday at 11:59:00 PM EST (though we typically release Modules 1-2 days early). You are free to complete each Module at your own pace within a given week, but we strongly recommend not waiting until the weekend to get started. All due dates are available through the Canvas Calendar, but the general rule of thumb is that each Module’s work is due by 11:59:00 PM EST on Sundays.

NOTE: Modules 1-3 start at a slightly gentler pace to help students gain a solid foundation and become comfortable getting around in Python. The pace gradually picks up beginning with Module 4 and we’ll continue operating at that pace until the course’s conclusion. The star rating provided in the Course Outline will be useful for helping you plan for the expected level-of-effort each week.

Textbooks

When building this course, we tried to use materials that would help reduce the cost to you, the students. This course does not require a textbook and is based on Readings from a popular Python resource called RealPython. The lecture slides loosely follow their material for a decent portion of the course and the weekly Readings provided on Canvas link to articles that were hand-selected to coincide with that week’s materials. If you’re interested in other useful online resources for Python, please let us know.

Required Software

We will make use of a few free tools in this course that are available for most hardware platforms:

• Python 3.9+, Microsoft VS Code, JetBrains PyCharm, REPL

There are 3 officially supported IDE’s for developing code in this course: PyCharm, VS Code, and REPL (replit.com). You can find instructions for downloading and installing the tool of your choice under the “Installing Python” section on Canvas under Module 1.

Student Coursework Requirements

It is expected that most Modules will take approximately 9-12 hours per week to complete, on average; some may take more, and some may take less. This estimate also varies from student-to-student. Here is an approximate breakdown: Readings (~1-2 hours per week), Video Lectures (~2 hours per week), and Programming Assignments (approximately 6-8 hours per week), Quizzes (~1 hour).

NOTE: if you begin to find a particular Module is taking well beyond the estimated 9-12, please be sure to reach out and contact us for help. Extra effort may be required some weeks, but we don’t want it to take you past the point of frustration. We hope you’ll give each Assignment an honest effort, but please know we’re here to support you and reach out with any questions!

Grading Policy

Syllabus, Course Outline, and Office Hours Quiz (7.5%)

This Syllabus, Course Outline, and Office Hours guide contain a lot of important information including how to be successful in this course. During Module 1 you will complete an open-book, untimed Syllabus, Course Outline, and Office Hours Quiz to help ensure you’ve caught the major themes of the course.

Quizzes (12.5%)

There will be a weekly Quiz to reinforce the concepts from that week’s Lecture and Assignment. The Quizzes will focus more on specific facts from Readings and Lectures (as opposed to the Assignments which will give you more general experience with applying concepts). Questions will be multiple choice, True/False, fill-ins, matching, short answer, etc. Quizzes will be 10 questions long, closed book, and students will have 60 minutes to complete them. If you are not happy with your grade you will have the option to retake each Quiz once during the Module it was assigned. The higher of your two attempts will be taken as your final grade on the Quiz. Our hope is that you’ll be able to focus on learning the key concepts and not have to worry as much about the stress of test-taking. Feel free to refer to any relevant course materials in-between attempts, but please do not access them while taking the Quiz.

NOTE: Quizzes are auto graded by Canvas to give a rough indication of how you performed on the quiz. The grade provided to you by the auto-grader may NOT accurately reflect your final score. ALL Quizzes are graded MANUALLY after Attempts #1 and #2 have been taken OR after the due date has passed. This is to ensure that correct answers which are not caught by the auto-grader are properly scored. To let you know when the quizzes have been manually graded, you will receive a comment on your quiz which reads “Your quiz has been manually graded.” All Quizzes are graded manually before the end of the next Module. Please avoid questions regarding quizzes until they have been manually graded.

Final Exam (25% of Final Grade Calculation)

To provide some flexibility and allow you to play to your strengths, we’ll be offering 3 versions of the Final Exam of which you must only complete one:

• Canvas + Programming Assignment: this version of the Final Exam will include a Canvas portion similar to the Midterm Exam and the weekly Quizzes as well as a Programming Assignment portion where you’ll solve a problem in computational geometry. We estimate the difficulty of the programming portion to be ***/****.
• Programming-only Option 1: this version of the Final Exam includes a Programming Assignment in Quantum Computation and will allow you to use skills from each Module to implement a working quantum simulator. We estimate the difficulty of this assignment to be ****.
• Programming-only Option 2: this version of the Final Exam includes a Programming Assignment in Counting Cards and will allow you to use skills from each Module to implement a program able to play blackjack and count cards. We estimate the difficulty of this assignment to be ****.

The Final Exam must be submitted by 11:59:00 PM EST on the due date. Late Final Exams will not be accepted due to final grades being due to the registrar.

Assignments (55% of Final Grade Calculation)

Most weeks, students will have a Python Programming Assignment designed to give you practice with that Module’s concepts and techniques. The estimated level-of-effort required for each Programming Assignment has been provided for you in the Course Outline and will increase gradually throughout the semester. Each assignment will be graded as follows:

		Excellent (90-100)	Good (80-89)	Satisfactory (70-79)	Unsatisfactory (70 >)
Program Correctness	50%	Code compiles successfully and produces correct results for all inputs. The program does not produce any runtime issues and makes use of relevant concepts from the module.	Code compiles successfully and produces mostly correct results for all inputs. The program does not produce any runtime issues.	Code compiles successfully and produces some correct results for all inputs. Program may encounter a runtime error.	Code does not compile successfully, produces multiple incorrect results, and/or suffers from multiple runtime errors.
Code Quality/Style	15%	Cleanly written and follows PEP-8 guidelines. Nicely organized, makes good use of whitespace, and appropriately named variables, methods, and classes.	Generally, follows PEP-8 guidelines. Mostly well-organized, slight over- or under-used whitespace, very	Misses most PEP-8 styling guidelines. Excessive use of whitespace. Poorly chosen names for variables, methods, and classes.	Omits PEP-8 styling guidelines. Significant misuse (or omission) of whitespace or comments. Arbitrarily named variables.
Documentation	15%	All relevant code is commented in appropriate detail. Different types of comments are used appropriately. readme.txt is provided and gives a clear and concise description of the approach taken.	Most relevant code is commented in appropriate detail. Too many/too few comments provided. readme.txt is mostly clear and the approach taken is mostly correct.	Multiple necessary comments are missing. Comments are routinely too long/too short. Readme.txt is somewhat clear or the approach taken is not correct.	Few to no comments are provided. Comments contain little to no useful information. Readme.txt is missing or the approach taken is incorrect for the problem to be solved.
Assignment Specification	10%	All required files are submitted in the required format, named correctly, and program outputs are in the proper format. All Assignment instructions have been followed.	Minor errors in required files or files submitted in an incorrect format, named incorrectly, or small errors in the program outputs.	Major errors in required files or files submitted in an incorrect format, named incorrectly, or major errors in the program outputs.	Submission does not meet most of the submission requirements or formats. Outputs are unintelligible.
Demonstrates Course Concepts	10%	Solution makes full use the Module’s contents and borrows minimally from outside approaches	Most major concepts are demonstrated; minimal use of out-of-scope concepts	Majority of concepts are not exercised; heavy use of out-of-scope techniques	Primary concepts are abandoned for techniques well outside the scope of the module

The Programming Assignments have been designed to help you translate what you learned in the Readings/Video lectures into using those concepts to create solutions in Python. Therefore, please do your best not to stray too far away from the concepts and techniques taught during that Module. If you would like to try an approach that involves a skill we have not covered (list comprehension instead of a for loop to build a list, a new Python library, etc.) please consult with us through Teams or email first.

We will post our solutions on Canvas (Module X Assignment solution will be posted under Module X) each week for you to review, usually on Thursday night after we review them during Office Hours or once everyone has submitted the assignment. The solutions are provided to help you review and resolve any portions of your solution that did not quite work, but we ask that you please do not share these solutions publicly. Similarly, we see our Assignments pop-up on Chegg, CourseHero, and other similar sites each semester. Posting an Assignment, which is the IP of JHU, publicly is a violation of course policy. A take-down notice will be issued and incidents will be referred to the University.


Final Grading

Assignments are due according to the dates posted in your Canvas course site. You may check these due dates in the Course Calendar or the Assignments in the corresponding modules. We generally do not directly grade spelling and grammar. However, egregious violations of the rules of the English language will be noted without comment. Consistently poor performance in either spelling or grammar is taken as an indication of poor written communication ability that may detract from your grade. A grade of A indicates achievement of consistent excellence and distinction throughout the course—that is, conspicuous excellence in all aspects of assignments and discussion in every week. A grade of B indicates work that meets all course requirements on a level appropriate for graduate academic work. These criteria apply to both undergraduates and graduate students taking the course. EP uses a +/- grading system (see “Grading System”, Graduate Programs catalog, p. 10). You should contact your Program Chair for guidance on the breakdown used by your program.

98-100 = A+
94-97 = A
90–93 = A−
87–89 = B+
84–86 = B
80–83 = B−
77–79 = C+
74-76 = C
70-73 = C-
<70 = F
Final grades will be determined by the following weighting:

Category	% of Grade
Syllabus, Course Outline, and Office Hours Quiz	7.5%
Quizzes	12.5%
Assignments	55%
Final Exam	25%

NOTE: we will accept questions/concerns about grading, and make any necessary changes, up until the time your Final Exam has been submitted. After that time, we will only make modifications to the grading of the Final Exam itself.

Course Policies

Late Coursework/Extension Policy

We’ve had to evolve this policy over time to ensure fairness to all students and integrity of the grades. All late work will incur a 7.5% deduction for each day late. Late work is defined as any work submitted after the prescribed due date and time (all times are given in Eastern Standard Time). So, please give some thought to any vacations, work travel, appointments, etc. you might have coming up that may conflict with course milestones and let us know in advance of the affected Module. We certainly understand that things come up from time-to-time and please know we’re happy to accommodate your situation to the fullest extent possible. However, based on past experience, we require official documentation for unexpected lateness (doctor’s note, work orders, etc.)

Academic Policies

Deadlines for Adding, Dropping and Withdrawing from Courses

Students may add a course up to one week after the start of the term for that particular course. Students may drop courses according to the drop deadlines outlined in the EP academic calendar (https://ep.jhu.edu/student-services/academic-calendar/). Between the 6th week of the class and prior to the final withdrawal deadline, a student may withdraw from a course with a W on their academic record. A record of the course will remain on the academic record with a W appearing in the grade column to indicate that the student registered and withdrew from the course.

Academic Misconduct Policy

All students are required to read, know, and comply with the Johns Hopkins University Krieger School of Arts and Sciences (KSAS) / Whiting School of Engineering (WSE) Procedures for Handling Allegations of Misconduct by Full-Time and Part-Time Graduate Students.

This policy prohibits academic misconduct, including but not limited to the following: cheating or facilitating cheating; plagiarism; reuse of assignments; unauthorized collaboration; alteration of graded assignments; and unfair competition. Course materials (old assignments, texts, or examinations, etc.) should not be shared unless authorized by the course instructor. Any questions related to this policy should be directed to EP’s academic integrity officer at ep-academic-integrity@jhu.edu.

Students with Disabilities - Accommodations and Accessibility

Johns Hopkins University values diversity and inclusion. We are committed to providing welcoming, equitable, and accessible educational experiences for all students. Students with disabilities (including those with psychological conditions, medical conditions and temporary disabilities) can request accommodations for this course by providing an Accommodation Letter issued by Student Disability Services (SDS). Please request accommodations for this course as early as possible to provide time for effective communication and arrangements.

For further information or to start the process of requesting accommodations, please contact Student Disability Services at Engineering for Professionals, ep-disability-svcs@jhu.edu.

Student Conduct Code

The fundamental purpose of the JHU regulation of student conduct is to promote and to protect the health, safety, welfare, property, and rights of all members of the University community as well as to promote the orderly operation of the University and to safeguard its property and facilities. As members of the University community, students accept certain responsibilities which support the educational mission and create an environment in which all students are afforded the same opportunity to succeed academically. 

For a full description of the code please visit the following website: https://studentaffairs.jhu.edu/policies-guidelines/student-code/

Classroom Climate

JHU is committed to creating a classroom environment that values the diversity of experiences and perspectives that all students bring. Everyone has the right to be treated with dignity and respect. Fostering an inclusive climate is important. Research and experience show that students who interact with peers who are different from themselves learn new things and experience tangible educational outcomes. At no time in this learning process should someone be singled out or treated unequally on the basis of any seen or unseen part of their identity. 
 
If you have concerns in this course about harassment, discrimination, or any unequal treatment, or if you seek accommodations or resources, please reach out to the course instructor directly. Reporting will never impact your course grade. You may also share concerns with your program chair, the Assistant Dean for Diversity and Inclusion, or the Office of Institutional Equity. In handling reports, people will protect your privacy as much as possible, but faculty and staff are required to officially report information for some cases (e.g. sexual harassment).

Course Auditing

When a student enrolls in an EP course with “audit” status, the student must reach an understanding with the instructor as to what is required to earn the “audit.” If the student does not meet those expectations, the instructor must notify the EP Registration Team [EP-Registration@exchange.johnshopkins.edu] in order for the student to be retroactively dropped or withdrawn from the course (depending on when the "audit" was requested and in accordance with EP registration deadlines). All lecture content will remain accessible to auditing students, but access to all other course material is left to the discretion of the instructor.