Introduction to Computing in Python 7

Introduction to Computing in Python 7 - David Joyner
Introduction to Computing in Python 7 - David Joyner

On this pc science course, you’ll find out about foundational computing rules, comparable to how one can write and browse pc code and how one can run and debug code.

You’ll find out about programming ideas in Python and the way they reveal computing rules and area purposes that use programming ideas and computing rules in actual purposes.

The course may also cowl:

  • procedural programming
  • management buildings
  • knowledge buildings
  • superior subjects in algorithms and object-oriented programming

This course builds on a customized textbook written for the category and on-line course supply and offers ample interplay and formative analysis. The course teaches each the idea and implementation of core computing ideas in a extremely interactive, multi-modal method.

What you’ll study

  • The elemental design cycle of pc science and pc programming: writing code, executing it, deciphering the outcomes, and revising the code primarily based on the outcomes.
  • Utilization of the elemental atoms of programming: variables, mathematical operators, logical operators, and boolean arithmetic.
  • Management buildings for growing dynamic packages: conditionals, loops, features, and error dealing with.
  • The core knowledge buildings for creating helpful packages: strings, lists, dictionaries, and file manipulation.
  • Previews of the following large subjects in pc science: object-oriented programming and pc algorithms.

Overview

This course begins from the start, protecting the fundamentals of how a pc interprets strains of code; how one can write packages, consider their output, and revise the code itself; how one can work with variables and their altering values; and how one can use mathematical, boolean, and relational operators.

By the top of this course, you’ll write small packages in Python that use variables, mathematical operators, and logical operators. For instance, you may write packages that perform advanced mathematical operations, like calculating the rate of interest essential to succeed in a financial savings objective, recommending attire choices primarily based on climate patterns, or calculating a grade primarily based on a number of percentages.

Structurally, the course is comprised of a number of elements. Instruction is delivered by way of a collection of quick (2-Three minute) movies. In between these movies, you may full each a number of alternative questions and coding issues to reveal your data of the fabric that was simply lined.

Syllabus

Chapter 1: Computing. The basics of how computer systems work, what program code is, and how one can get setup for the remainder of the course.

Chapter 2: Programming. The fundamental rules of pc programming: writing and working code, evaluating outcomes, and compiling vs. executing.

Chapter 3: Debugging. The frequent outcomes of working program code, and how one can use these outcomes to tell revision of your code.

Chapter 4: Procedural Programming. The elemental method to program code: writing sequences of strains of code that run with the intention to accomplish an goal.

Chapter 5: Variables. Creating and modifying variables, tracing how their values might change as a program runs, and understanding the function of knowledge sorts.

Chapter 6: Logical Operators. Working with relational (better than, lower than, equal to) and logical (and, or, not) operators to make selections in code.

Chapter 7: Mathematical Operators. Including addition, subtraction, multiplication, division, modulus, and exponents to your code, and seeing how they work with sudden knowledge sorts.

Taught by : David Joyner

Sale page : https://www.coursetalk.com/providers/edx/courses/introduction-to-computing-using-python