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Regular version of the site
Bachelor 2019/2020

Introduction to Programming

Category 'Best Course for Career Development'
Area of studies: Applied Mathematics and Information Science
When: 1 year, 1, 2 module
Mode of studies: Full time
Language: English
ECTS credits: 8

Course Syllabus

Abstract

The training course “Introduction to Programming” is offered to students of Bachelor Program “HSE and University of London Double Degree Programme in Data Science and Business Analytics” at the Faculty of Computer Science of the National Research University — Higher School of Economics (HSE). The course is classified as a compulsory subject; it is a two-module course (semester A quartiles 1 and 2). The course is divided into two logical parts, which do not basically depend on each other. The first part is given during semester A quartile 1 under the responsibility of Dr. Tamara Voznesenskaya. The second part is given during semester A quartile 2 under the responsibility of Lect. Sergey Shershakov. The first part of the course is intended to be taught during the first module (quartile) of the program, so it starts from the very beginning and takes into account, that some of the students may have zero experience in programming. The lectures and practical classes are closely inter-related. The lectures are primarily intended to introduce new topics, whereas the practical classes are intended for solving specific problems by coding programs in Python. The second part of the course is intended to be taught during the third module (quartile) of the program. It is dedicated to the base features of the C++ programming language and C++ Standard Library (STL). The part covers all necessary topics that are needed to start developing a modern CLI1-applications in C++14. The lectures and practical classes are closely inter-related. The lectures are primarily intended to introduce new topics, whereas the practical classes are intended for solving specific problems by coding programs in C++.
Learning Objectives

Learning Objectives

  • One of the objectives of this course is for the students to will study the methodology of programming.
  • During this course, the students will develop algorithmic thinking.
  • During this course, the students will study approaches and toolkits for the development of Python applications.
  • During this course, the students will study approaches and toolchains for the development of C++-applications.
  • During this course, the students will practice application debugging and deployment with respect to various platforms and toolchains.
Expected Learning Outcomes

Expected Learning Outcomes

  • Students will learn basic concepts and methods of software development.
  • Students will acquire skills in Python programming to formalize and solve simple development tasks.
  • Students will learn to select the most appropriate toolset for app development.
  • Students will practice application debugging and deployment with respect to various platforms and toolchains.
  • Students will learn to analyze a problem to be implemented in the form of a C++-application.
  • Students will learn to design app architecture with respect to problem decomposition and known limitations.
  • Students will learn to create a testbed environment for essential testing of the application.
Course Contents

Course Contents

  • Introduction.
  • Dynamic typing. Operations of sequence, selection, and iteration.
  • Float in the computer memory, rounding and other aspects. Strings.
  • Strings. Tkinter GUI.
  • Functions and recursion. Lambda-functions. Named parameters.
  • Tuples. Lists. Function map. Methods Split and Join.
  • Zen of python. PEP-8. Documenting code (PEP-257). Files. Exceptions and errors. Program debugging.
  • Sets. Dictionaries.
  • Sort and found. Introduction into the complexity theory.
  • Elements of functional programming. Function Enumerate. Module Functools.
  • Object-oriented programming. Main ideas: encapsulation, inheritance and polymorphism. Operator Overriding. Function Isinstance. Examples.
  • Python for data analysis. Overview.
  • Introduction to C++.
    Introduction to C++. C++ program structure. Statements. Programs and modules. Toolchains and building C++ Programs.
  • Data types and Objects.
    Datatypes and Objects. Primitive, composite and user datatypes. Scope of variables (objects). Constants. Basic input/output. Introduction to streams.
  • Control flow statements.
    Control flow statements: conditional (if, switch); loops (while, do..while, for).
  • Expressions and Operators.
    Expressions. Operations and operators. Operator precedence. Logical and Bitwise operations.
  • Functions and procedures.
    Procedural decomposition. Functions and procedures. Formal and Actual Parameters of a Function. Function return value. Function signature. Passing parameters to a function by value and by reference. Function overloading. Operator overloading.
  • C++ Memory model.
    Memory model of a C++ program. Addresses and pointers. Difference between pointer and reference. Stack- and heap-memory. Object life-cycle.
  • Classes.
    Classes overview. Class members: methods and fields. Access modifiers: public, protected, private. Classes vs. structures. Te (.) “dot” and (->) “arrow” operators. Constructors. Destructor. Safe array. Copy constructor. Copy operation. Copy-and-swap idiom. Rule of three.
  • Strings.
    Strings in C++. Null-terminated string. std: string class. Unicode supporting. String streams. Approaches to deal with strings.
  • Standard library (STL).
    Standard library (STL) overview. Containers and adapters. Algorithms. Iterators. “for-each” loop for iterating collections/containers. stl::vector<T> and C-style arrays. Dynamic resizing of a vector. Standard library components. Sequence containers: vector, list, dequeue∗. Associative containers: map, set, unordered_map, unordered_set. Adapters: stack, priority_queue. Main std algorithms.
  • Operator overloading.
    More on operator overloading. Bitwise operations. std::bitset<N> class.
  • Templates.
    Templates: classes and functions. Header-only approach. typename and inner types. Templates and duck-typing. Concepts. std template framework. Lambda functions.
  • Exceptions and Move semantics.
    Exceptions. RAII idiom. Smart pointers. Move semantics. Rvalue reference. Rule of five.
  • Inheritance.
    Te Tree Pillars of Object-Oriented Programming: Encapsulation, Inheritance, Polymorphism. Single inheritance. Virtual and pure-virtual methods. Abstract classes and interface classes.
  • Object-Oriented Analysis and Design.
    Introduction to Object-Oriented Analysis and Design. Class relationships.
  • C++ plus Python.
    Binding c++ and python together.
Assessment Elements

Assessment Elements

  • non-blocking 1st module Ongoing Assessment
    The ongoing assessment grade is accumulated throughout all the classes and is related to a participant’s activity. An ongoing control structure is individual for every class. During the classes, there are some activities available for students to be involved in. They include (but are not limited by) writing code and developing applications, evaluating practical problems, solving tests, answering questions and so on.
  • non-blocking 2nd module Ongoing Assessment
    The ongoing assessment grade is accumulated throughout all the classes and is related to a participant’s activity. An ongoing control structure is individual for every class. During the classes, there are some activities available for students to be involved in. They include (but are not limited by) writing code and developing applications, evaluating practical problems, solving tests, answering questions and so on.
  • non-blocking 1st module Exam
    First part exam, which takes place at the end of the first quartile.
  • non-blocking 2nd module Exam
    The second part exam, which takes place at the end of the second quartile.
  • non-blocking Regular tests
    Students’ skills in programming are tested using automated testing. This way, a student is assigned an individual task, prepares it by using a personal computer and, then, submits it by using a special service, such as Yandex.Contest or a repository-based tool. The specific solution is subject to further clarification
  • non-blocking Individual Home-based tasks
    Students’ skills in programming are tested using automated testing. This way, a student is assigned an individual task, prepares it by using a personal computer and, then, submits it by using a special service, such as Yandex.Contest or a repository-based tool. The specific solution is subject to further clarification.
Interim Assessment

Interim Assessment

  • Interim assessment (1 module)
    0.4 * 1st module Exam + 0.6 * 1st module Ongoing Assessment
  • Interim assessment (2 module)
    0.4 * 2nd module Exam + 0.6 * 2nd module Ongoing Assessment
Bibliography

Bibliography

Recommended Core Bibliography

  • Davis, S. R. (2014). C++ For Dummies (Vol. 7th ed). Hoboken: For Dummies. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=784132
  • Gregoire, M. (2018). Professional C++ (Vol. Fourth edition). Indianapolis, IN: Wrox. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1729638
  • Pilgrim, M. (2009). Dive Into Python 3. New York: Apress. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=326208

Recommended Additional Bibliography

  • Olsson, M. (2015). C Quick Syntax Reference. [New York]: Apress. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=944034