A project based course that looks under the hood at data structures and algorithms to see how they work. In addition to implementing these structures in an application; students will build them from scratch, analyze their complexity, and benchmark their performance to gain an understanding of their tradeoffs and when to use them in practice. Students will write scripts, functions, and library modules to use text processing tools like regular expressions, construct and sample probability distributions to create a Markov language model and gain insight into how grammar works and natural language processing techniques.
Term 3 Course Dates: Wednesday, January 23 – Wednesday, March 6, 2019
Class Times: Monday & Wednesday 3:30–5:20pm
| Class | Date | Topics |
|---|---|---|
| 1 | Wednesday, January 23 | Strings & Random Numbers |
| 2 | Monday, January 28 | Histogram Data Structures |
| 3 | Wednesday, January 30 | Probability & Sampling |
| 4 | Monday, February 4 | Flask Web App Development |
| 5 | Wednesday, February 6 | Application Architecture |
| 6 | Monday, February 11 | Generating Sentences |
| 7 | Wednesday, February 13 | Arrays & Linked Lists |
| 8 | Tuesday, February 19 | Hash Tables |
| 9 | Wednesday, February 20 | Hash Tables Continued |
| 10 | Monday, February 25 | Algorithm Analysis |
| 11 | Wednesday, February 27 | Higher Order Markov Chains |
| 12 | Monday, March 4 | Regular Expressions |
| 13 | Wednesday, March 6 | Written Assessment (Final Exam) |
- Weeks to Completion: 7
- Total Seat Hours: 37.5 hours
- Total Out-of-Class Hours: 75 hours
- Total Hours: 112.5 hours
- Units: 3 units
- Delivery Method: Residential
- Class Sessions: 13 classes, 7 labs
Students must pass the following course and demonstrate mastery of its competencies:
By the end of this course, students will be able to:
- write Python programs that read and write text files and manipulate strings
- build web apps with the Flask framework and deploy to the web using Heroku
- construct and sample probability distributions based on observed word frequencies
- create Markov language models and use them to generate new sentences
- write library code organized into separate independent modules with low coupling
- run unit tests that assert functions and classes exhibit the correct behavior
- implement core data structures including singly linked list and hash table
- analyze complexity of iterative algorithms and data structures with visual loop counting
- use regular expressions to parse and clean up text and tokenize words and sentences
Students will complete the following guided project tutorial in this course:
To pass this course, students must meet the following requirements:
- Actively participate in class and abide by the attendance policy
- Make up all classwork from all absences
- Complete the required project tutorial
- Pass the project according to the associated project rubric
- Pass the summative assessment (final exam)
Just like any job, attendance at Make School is required and a key component of your success. Attendance is being onsite from 9:30am to 5:30pm each day, attending all scheduled sessions including classes, huddles, coaching and school meetings, and working in the study labs when not in a scheduled session. Working onsite allows you to learn with your peers, have access to support from TAs, instructors and others, and is vital to your learning.
Attendance requirements for scheduled sessions are:
- No more than two unexcused absences ("no-call-no-shows") per term in any scheduled session.
- No more than four excused absences (communicated in advance) per term in any scheduled session.
Failure to meet these requirements will result in a Participation Improvement Plan (PIP). Failure to improve after the PIP is cause for not being allowed to continue at Make School.
- Academic Honesty
- Accomodation Policy
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- Diversity Statement
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