DNU FTF Introduction to Computer Science Course

This repository is used to store materials, lectures, labs of the dnu ftf introduction to computer science course.

Presequences

The lectures and labs of this course will be presented in a form of jupyter notebooks. The presequences should be done by any student of this course to successfully get in touch with a course` materials. List of required presequences is following:

• anaconda3 install;
• git install;
• acquaintance with jupyter environment;
• telegram bot registration;

Anaconda3 Install

1. Visit anaconda official website. Download anaconda version respectively to OS used (windows \ linux \ mac);
2. Install anaconda3 via installing menu, use default checks and accept all popups. video for dummies;
3. Use start menu of windows \ linux \ mac to find the Anaconda Navigator. Execute it;
4. Using the Anaconda Navigator, launch NOTEBOOK icon;
5. Make sure it was launched, you will see the browser opened with a new page, which contains explorer-like file system view;
6. You are brilliant!

GIT Install

Git is a must have tool for the version control. It will be used to clone and update current repository in seek of new lectures and labs.

• Visit the github installation guide and follow the steps listed here, according to your OS;
• Use start menu of your os to find the ANACONDA PROMT executabe file, run it;
• After the console opened, print following:

git clone https://github.com/kirienkomaxym/dnu_ftf_cs 

Expected result should be a following promt output (nums may differ):

remote: Enumerating objects: 3, done.
remote: Counting objects: 100% (3/3), done.
remote: Compressing objects: 100% (2/2), done.
remote: Total 3 (delta 0), reused 0 (delta 0), pack-reused 0                                                            
Receiving objects: 100% (3/3), done.

• After this, print following:

jupyter notebook

• You will see jupyter explorer, using which, navigate to the dnu_ftf_cs directory;
• Click on the README.md file, you will see this guide in a unformatted view;
• DONE!

Jupyter Environment Acquaintance

Jupyter is an environment that will be used for the reviewing the lectures and labs. Also it will be used for performing the assignments. In this step, you will launch your first notebook and run test code.

• Use start menu of your os to find the ANACONDA PROMT executabe file, run it;
• Navigate to the folder with repository youve cloned before, example (Windows):

if you have stored the github project on another drive, please use

d: (or another drive name, I have letter o)

(base) C:\Users\kirie>o:
(base) O:\>cd O:\Projects\dnu_ftf_cs
(base) O:\Projects\dnu_ftf_cs>

• Launch Jupyter Notebook wih:

jupyter notebook

• Using the jupyter explorer, select the asquaintance_notebook;
• Perform the actions that are described inside the notebook;

TG Bot Registration

• launch telegram and find the bot
• print /register and follow the instructions

Course Structure

Lectures

• Lecture 1: Compliers & Interpreters, I/O, Variables, Data Types;
• Lecture 2: Logic Statements, If/Elif/Else, Loops, Indentation
• Lecture 3: Functions, Generators, Decorators
• Lecture 4: Objects, OOP
• Lecture 5: Errors, Files, Logging, Libraries, Imports
• Lecture 6: IDEs, Testing, Unit-Testing, Debugging
• Lecture 7: Async Basics, API Basics

Labs

• Lab1: Data Types: Strings, Numbers, Bytes, Boolean;
• Lab2: Data Types: Lists, Dictionaries, Tuples, Sets;
• Lab3: Functions: Function Syntax, Return, Arguments, Scope;
• Lab4: Functions: Recursion, Yield, Generators, Decorators;
• Lab5: Objects: Objects Creating, Methods, Fields, UML-Diagramming;
• Lab6: Objects: Dunders, Static and Classmethods;
• Lab7: Objects: Inheritance, Poly, Encapsulation
• Lab8: Errors, Try/Except/Finally, Logging;
• Lab9: Libraries, Imports, IDEs;
• Lab10: Testing, Assert, Unit-Testing, Test-Driven-Development;
• Lab11: Libraries: Numpy, Matplotlib;
• Lab12: Libraries: Scikit, Pandas;
• Lab13: Yields again, Select, Async;
• Lab14: APIs, REST, WebSocket;

Programming Assignments

• PS1: Data Types: Strings, Numbers, Bytes, Boolean;
• PS2: Data Types: Lists, Dictionaries, Tuples, Sets
• PS3: Logic Statements, If/Elif/Else, Loops, Indentation
• PS4: Functions
• PS5: Recursion, Decorators, Yields
• PS6: OOP
• PS7: OOP
• PS8: OOP
• PS9: OOP
• PS9: Testing
• PS10: Numpy
• PS11: Scikit
• PS12: Pandas
• PS13: Async

Assignment Grades & Exam

TBD