Introduction to Python Programming

Overview

Syllabus

Courses

• 256 reviews

  5 weeks, 9-10 hours a week, 9-10 hours a week

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  This course starts from the beginning, covering the basics of how a computer interprets lines of code; how to write programs, evaluate their output, and revise the code itself; how to work with variables and their changing values; and how to use mathematical, boolean, and relational operators.

  By the end of this course, you'll be able to write small programs in Python that use variables, mathematical operators, and logical operators. For example, you could write programs that carry out complex mathematical operations, like calculating the interest rate necessary to reach a savings goal, recommending apparel options based on weather patterns, or calculating a grade based on multiple percentages.

  Structurally, the course is comprised of several parts. Instruction is delivered via a series of short (2-3 minute) videos. In between those videos, you'll complete both multiple choice questions and coding problems to demonstrate your knowledge of the material that was just covered.

• 59 reviews

  5 weeks, 9-10 hours a week, 9-10 hours a week

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  Building on your prior knowledge of variables and operators, this course gets into the meat of programming. Organized into five chapters, this course starts by covering the fundamentals of what control structures are and what they do, then moves on to four common control structures in Python. Conditionals let you modify what your program does based on the values of incoming variables. Loops let you repeat tasks for multiple values or while certain conditions hold true. Functions let you encapsulate complex reasoning into reusable chunks of code. Error handling lets you intelligently recover from anticipated and unanticipated glitches.

  By the end of this course, you'll be able to write complex programs in Python that perform useful reasoning. For example, you could write a program that calculates your weight on other planets, calculates the standard deviation of a series of numbers, or checks for the validity of an incoming password.

  Structurally, the course is comprised of several parts. Instruction is delivered via a series of short (2-3 minute) videos. In between those videos, you'll complete both multiple choice questions and coding problems to demonstrate your knowledge of the material that was just covered.

• 48 reviews

  5 weeks, 9-10 hours a week, 9-10 hours a week

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  Build on your existing knowledge of conditionals, loops, and functions by studying more about complex Python data structures, including strings, lists, dictionaries, and file input and output. Organized into five chapters, this course starts by covering the basics of data structures, then moves on to these four common data structures in Python:

  • Strings let you perform far more complex reasoning with text.
  • Lists let you process long lists of data, and even lists of lists of data for more complex reasoning.
  • Dictionaries let you more clearly code for complex types of data, and even simulate some basic elements of object-oriented programming.
  • File input and output brings your programs to life, allowing you to persist data across executions of the same program.

  By the end of this course, you'll be able to write even more complex programs in Python that process and persist complex data structures. For example, you'll be able to write an ongoing gradebook application that tracks and updates your average over time, a program to calculate the net force based on several force magnitudes and directions, or a program that can turn a string like this into a StRiNg LiKe tHiS.

  Structurally, the course is comprised of several parts. Instruction is delivered via a series of short (2-3 minute) videos. In between those videos, you'll complete both multiple choice questions and coding problems to demonstrate your knowledge of the material that was just covered.

• 107 reviews

  5 weeks, 9-10 hours a week, 9-10 hours a week

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  Complete your introductory knowledge of computer science with this final course on objects and algorithms. Now that you've learned about complex control structures and data structures, learn to develop programs that more intuitively leverage your natural understanding of problems through object-oriented programming. Then, learn to analyze the complexity and efficiency of these programs through algorithms. In addition, certify your broader knowledge of Introduction to Computing with a comprehensive exam.

  By the end of this course, you'll be able to write programs in Python that leverage your more natural understanding of data structures by creating objects to represent the structures you work with most often. For example, if you were creating a class roster application, you'll learn how to create an object representing a student's name, ID number, and attendance record. Then, you'll be able to create applications that leverage sorting and searching algorithms to sort that roster alphabetically, search for a particular student, and evaluate the efficiency of both those operations.

  Structurally, the course is comprised of several parts. Instruction is delivered via a series of short (2-3 minute) videos. In between those videos, you'll complete both multiple choice questions and coding problems to demonstrate your knowledge of the material that was just covered. These exercises count for 20% of your grade. Then, after each major chapter, you'll complete a problem set of collected, more challenging problems. These count for 40% of your grade. Finally, you'll complete a final course exam, which counts for the remaining 40% of your grade.

Taught by

David Joyner

Tags

• united states