Learn to code in easy steps II
Video: .mp4 (1280x720, 30 fps(r)) | Audio: aac, 48000 Hz, 2ch | Size: 543 MB
Genre: eLearning Video | Duration: 7 lectures (53 mins) | Language: English
Python Coding
Video: .mp4 (1280x720, 30 fps(r)) | Audio: aac, 48000 Hz, 2ch | Size: 543 MB
Genre: eLearning Video | Duration: 7 lectures (53 mins) | Language: English
Python Coding
To download steps I: https://avxhm.se/ebooks/learn-to-code-in-easy-steps.html
What you'll learn
How to code using Python
Requirements
Basic understanding of computing terminology - Previous course - Learn to code in easy steps
Description
Learn to code in easy steps II
Hello and welcome to this introduction to coding course. This course builds on our 1st course - Learn to code in easy steps.
In this course we will be covering the following
· Subroutines including variable scope
· Arrays – 1 dimensional and 2 dimensional arrays
· Mathematical Operations – arithmetic and relational operators
· Error – exploration of methods to identify and fix logic, syntax and runtime errors
· Boolean logic
This will enable you to develop your knowledge and skills in easily absorbed, manageable steps. The first lesson, subroutines, will enable you to apply the theory of decomposition, an essential component of computational thinking. This lesson is related to our very 1st lesson; (1st course - Learn to code in easy steps) Introduction to computational thinking. Concepts will be reinforced by completing a worksheet.
The second lesson will explore improving the efficiency of programs or algorithms by using arrays. This relates to our 2nd lesson in the previous course that discussed the efficiency of algorithms. You will be asked to complete a number of tasks to ‘embed’ this learning. The remaining lessons will proceed in a similar fashion with targeted quizzes, activities and homework tasks to reinforce what is being taught.
By the end of the course you will have learned the basics of how to write quality programs using subroutines, arrays and Boolean logic. You will be able to use this knowledge to tackle more advanced programming courses.
Who this course is for:
Students wanting to learn Python programming