CSCI2040: Introduction to Python

General Expectations: Student/Faculty Expectations on Teaching and Learning

Teacher: Prof. John C.S. Lui

This is a 2-unit course which provides an introduction to Python. It is designed to give students fluency in Python, its programming paradigm (such as object-oriented programming and functional programming style), its data structures, as well as various modules and libraries (e.g., NumPy, SciPy, mathplotlib,..etc). The course consists of both lectures and labs with students doing sample Python problems. Problem-based Python assignments will be given which require significant time on Python programming.

IMPORTANT: We assume you have some programming experience and background.

Note that Python is one of the "TOP THREE" programming languages nowaday. Many companies are now using Python (e.g., Google, Facebook, Tencent,..etc), and Python is considered an essential programming language for big data analytics and machine learning. In fact, for the course CSCI3320 (Fundamentals of Machine Learning), it uses the Python language.

Important reminder: Students need to spend time to read resources on the Internet, do the homework, attend the lectures and labs so to understand and keep pace with this course.

Teaching Assistants

• Mr. Wang Xuchuang Office hour: Thurs. 10:00 am to noon. Office, HSH Eng Bldg, Room 120. (Email: xcwang@cse.cuhk.edu.hk)
• Miss Shiyuan Zheng Office hour: Wed. 02:00-04:00 pm. Office, HSH Eng Bldg, Room 120. (Email: syzheng@cse.cuhk.edu.hk)
• Miss. Maoli Liu Office hour: Fri. 10:00 am t0 noon. Office, HSH Eng Bldg, Room 120. (Email: mlliu@cse.cuhk.edu.hk)

• Exploring Python by Timothy A. Budd ( Main textbook )
• Think Python: How to Think Like a Computer Scientist, by Allen B. Downey
• Python for Informatics: Exploring Information, by Chuck Severance
• Python Tutorial
• Python Programming at Youtube
• There are also abundant resources available on the web. As I often said, ''The knowledge available on the web is only valuable to those who are intellectually curious and disciplined. ''

Usefule Links:

• The Python 2 Standard Library
• The Python 2 Tutorial
• The Python 3 Standard Library
• The Python 3 Tutorial

Course Grades:

• Programming exercises: 40%
• Exam: 60% Important note: Students need to get at least 30% in the final exam to pass, independent of their performance in programming exercises.
  

IMPORTANT REMINDERS !!!!!!

• No lab during the first week of classes. The first lab will be held on the week of Sept XXth, 2020.
• FINAL EXAM: It will be on December 5th, 2020 (morning). The venue will be decided later.

Policies:

• No late homework, programming assignments or projects will be accepted;
• For those students who don't study hard, well, please watch this video: "Wise saying from Gandalf, wizard from the Lord of the Rings" Yes, you will fail if you don't work hard in this course.

• Introduction: installation, variables, operators, control, list..., etc.
• Variables, strings, numbers, basic operations.
• Lists and tuples and their operators.
• Functions
• Conditional statement (e.g., if)
• Loops and input functions
• Terminal applicattions and Pickle
• Dictionaries
• Object-Oriented Programming (OOP)
• Functional Programming (FP)
• Regular expressions and processing
• Modules
• Files and various utilities (e.g., system, compression)
• Introduction to Numpy and Scipy
• Visualization (e.g., mathplotlib)
• Optional topics
  • Templates in Python
  • Argparse in Python
  • MultiThreading in Python
  • Networking in Python
  • C Extension in Python
  • PyCrypto in Python
  • A brief look at machine learning
• Special topic: Blockchains (if time allows)

• Tip on how to setup Eclipse and PyDev: (help file)

Lecture Notes (Lecture Notes are available at CUHK Blackboard (https://blackboard.cuhk.edu.hk/))

Lecture 0: Introduction and setup

Lecture 1: Variables, Strings, and Numbers

Lecture 2: Lists and Tuples

Lecture 3: Functions

Lecture 4: If statement and its usage

Lecture 5: Loops and Input Functions

Lecture 6: Terminal apps and Pickle

Lecture 7: Dictionaries

Lecture 8: Functions (advanced topic)

Lecture 9: Object-oriented Programming

Lecture 10: Functional Programming

Lecture 11: Regular Expressions and its processing

Lecture 12: Files and utilities

Lecture 13: NumPy and SciPy

Lecture 14: Visualization

Lecture 14: Optional topics (if time allows)

• Templates in Python
• Argparse in Python
• Multithreading in Python
• Networking in Python
• C Extension in Python
• Cryptography in Python

Lecture 15: Advanced topics: Blockchains (if time allows)

Lab Exercises

Please go to the "Blackboard" to access the specification and testing script of all labs.