Linguistics 2195 Python Programming for Language Researchers Course Home (Spring 2019)
Table of Contents:
Instructor: Chongwon Park, Ph.D. (TA: Trevor Winger)
Google group address: ling2195_002s19d@d.umn.edu
Office Hours: 10:00 - 10:55AM, MW (H420S)
Class Time: 3:00 - 3:50PM, MWF (Sports and Health Center 208)
The Quick Python Book -- 3rd Edition (Naomi Ceder, Manning)
Natural Language Processing with Python (Steven Bird, Ewan Klein, and Edward Loper, O'Reilly)
The aim of this course is to learn computer programming using Python within the context of linguistic analysis. Students will learn basic concepts of programming. After learning how to create basic code using the said concepts, students will create more domain specific programs to clean up and reformat a large set of text data. The learning outcomes of this course are: [1] Designining short programs (scripts) that incorporate basic concepts in Python programming, such as variables, types, expressions, etc.; [2] Understanding the data structures of Python; [3] Performing morpho-syntactic analyses of English sentences using NLTK or other packages; [4] Evaluating the efficiency and/or accuracy of different types of linguistic analysis tools such as NLTK parser and Stanford parser; [5] Creating a program that generates syntactic analyses of a selected text from the Gutenberg Project or COCA.
You will have a total of 10 assignments and 3 exams. All assignments and exams consist of problem-solving questions.
It is important for you to be present for every class. Every homework assignment should be turned in on the due date (or before the due date) in class. Evaluation will be based on the following weight. IMPORTANT: I DO NOT accept late assignments (no exceptions). E-mail submissions WILL NOT be accepted.
Number |
Points |
Total |
|
Homework |
10 |
5 (per homework) |
50 |
Exam 1 |
1 |
10 |
10 |
Exam 2 |
1 |
15 |
15 |
Exam 3 |
1 |
25 |
25 |
Total |
100 |
While students are expected to attend every single class period, there are circumstances that lead to excused absence from the classroom. Excused absences are defined at http://www.duluth.umn.edu/vcaa/ExcusedAbsence.html. To be eligible for an excused absence, students must provide written documents such as doctor's notes and advisor's letters. To encourage your attendance, for each class you miss 1 point will be deducted, but if your attendance is perfect (any absences being excused) you will receive 3 bonus points.
Course Schedule for Spring 2019:
Date |
Topic |
Assignments and Due Dates |
Required Reading |
Jan. 16 (W) | Introduction |
||
Jan. 18 (F) | Basics |
Ceder, Ch. 4 |
|
Jan. 21 (M) | No Class |
||
Jan. 23 (W) | List, tuples, and sets |
Ceder, Ch. 5 |
|
Jan. 25 (F) | Strings |
Assignment, Due Feb. 1 (F) |
Ceder, Ch. 6 |
Jan. 28 (M) | Dictionaries |
Ceder, Ch. 7 |
|
Jan. 30 (W) | Contron flow |
Ceder, Ch. 8 |
|
Feb. 1 (F) | Control flow |
Assignment 2, Due Feb. 8 (F) |
Ceder, Ch. 8 |
Feb. 4 (M) | Functions |
Ceder, Ch. 9 |
|
Feb. 6 (W) | Functions |
Ceder, Ch. 9 |
|
Feb. 8 (F) | Functions |
Assignment 3, Due Feb. 15 (F) |
Ceder, Ch. 9 |
Feb. 11 (M) | Modules and scoping rules |
Ceder, Ch. 10 |
|
Feb. 13 (W) | Reading and writing files |
Ceder, Ch. 13 |
|
Feb. 15 (F) | Exceptions |
Assignment 4, Due Feb. 22 (F) |
Ceder, Ch. 14 |
Feb. 18 (M) | Classes and OOP |
Ceder, Ch. 15 |
|
Feb. 20 (W) | Classes and OOP |
Ceder, Ch. 15 |
|
Feb. 22 (F) | Regular Expressions |
Ceder, Ch. 16 |
|
Feb. 25 (M) | Regular Expressions |
Assignment 5, Due Mar. 4 (M) |
Ceder, Ch. 16 |
Feb. 27 (W) | Basic file wrangling |
Ceder, Ch. 20 |
|
Mar. 1 (F) | Processing data files |
Ceder, Ch. 21 |
|
Mar. 4 (M) | Processing data files |
Ceder, Ch. 21 |
|
Mar. 6 (W) | Exam 1 |
Ceder, Ch. 1 ~ Ch. 16 |
|
Mar. 8 (F) | Data over network |
Assignment 6, Due Mar. 18 (M) |
Ceder, Ch. 22 |
Mar. 11 (M) | No Class |
||
Mar. 13 (W) | No Class |
||
Mar. 15 (F) | No Class |
||
Mar. 18 (M) | Data over network |
Ceder, Ch. 22 |
|
Mar. 20 (W) | Saving Data |
Ceder, Ch. 23 |
|
Mar. 22 (F) | Saving Data |
Assignment 7, Due Mar. 29 (F) |
Ceder, Ch. 23 |
Mar. 25 (M) | Processing raw text |
Bird et al., Ch. 3 |
|
Mar. 27 (W) | Processing raw text |
Bird et al., Ch. 3 |
|
Mar. 29 (F) | Processing raw text |
Assignment 8, Due Apr. 5 (F) |
Bird et al., Ch. 3 |
Apr. 1 (M) | Categorizing and tagging words |
Bird et al., Ch. 5 |
|
Apr. 3 (W) | Categorizing and tagging words |
Bird et al., Ch. 5 |
|
Apr. 5 (F) | Categorizing and tagging words |
Assignment 9, Due Apr. 12 (F) |
Bird et al., Ch. 5 |
Apr. 8 (M) | Analyzing sentence structures |
Bird et al. Ch. 8 |
|
Apr. 10 (W) | Analyzing sentence structures |
Bird et al., Ch. 8 |
|
Apr. 12 (F) | Exam 2 |
Bird et al., Ch 3 and Ch 5 |
|
Apr. 15 (M) | Analyzing sentence structures |
Bird et al., Ch. 8 |
|
Apr. 17 (W) | No Class |
||
Apr. 19 (F) | No Class |
||
Apr. 22 (M) | No class |
||
Apr. 24 (W) | Building feature-based grammars |
Assignment 10, Due May 1 (W) |
Bird et al., Ch. 9 |
Apr. 26 (F) | Building feature-based grammars |
Bird et al., Ch. 9 |
|
Apr. 29 (M) | Building feature-based grammars |
Bird et al., Ch. 9 |
|
May 1 (W) | Analyzing the meaning of sentences |
Bird et al., Ch. 10 |
|
May 3 (F) | Analyzing the meaning of sentences |
Bird et al., Ch. 10 |
|
Final Exam (Take-home) |
Due May 10, 2019 (4PM) |
Comprehensive |
Academic dishonesty tarnishes UMD's reputation and discredits the accomplishments of students. UMD is committed to providing students every possible opportunity to grow in mind and spirit. This pledge can only be redeemed in an environment of trust, honesty, and fairness. As a result, academic dishonesty is regarded as a serious offense by all members of the academic community. In keeping with this ideal, this course will adhere to UMD's Student Academic Integrity Policy, which can be found at http://www.d.umn.edu/conduct/integrity. This policy sanctions students engaging in academic dishonesty with penalties up to and including expulsion from the university for repeat offenders.
Appropriate Classroom Conduct:
The instructor will enforce and students are expected to follow the University's Student Conduct Code (http://www.d.umn.edu/conduct/code). Appropriate classroom conduct promotes an environment of academic achievement and integrity. Disruptive classroom behavior that substantially or repeatedly interrupts either the instructor's ability to teach, or student learning, is prohibited. Disruptive behavior includes inappropriate use of technology in the classroom. Examples include ringing cell phones, text-messaging, watching videos, playing computer games, checking email, surfing the Internet, or Facebooking (or facebooking) on your computer instead of note-taking or other instructor-sanctioned activities.