Coding For The Professional Non-Developer

Learn the basics of coding and the fundamentals of programming concepts using Python

What you'll learn
Introduction to computers
Introduction to programming
Data systems
Python

Requirements
No requierments or prerequisites needed.
Wanting to learn something new

Description
This course is for professional data scientists, data processors and GIS professionals who want to automate their workflows and speed up production.No prior knowledge of coding is needed. All the concepts and special words will be explained during the introduction part of the course. Later more in-depth explanations will be given for more involved topics.The last part of the course will be an introduction to Python with is a programing language that is commonly used in workflow automatization in a variety of software. Although we will be using Python as the main practical coding language there are examples of other coding languages used throughout the course. When you understand the basics of coding it is possible to figure out what different programming languages do even if you can understand it all making it possible to learn others.Python is a good choice for a beginner coding language because it does not use a compiler it is an interpreted language which means that one line at a time is converted to machine code making an overarching program structure unnecessary although functions, classes and more can be used later when you are more familiar with its use and want to do more complex coding.No software-specific procedures and functions will be covered because there is such a large area of the data market when python is used within other software that has its dedicated functions. This course will teach you the basics of coding. Even if you are not planning to use Python in the end.

Overview
Section 1: Introduction

Lecture 1 Introduction

Lecture 2 Computer Basics

Lecture 3 Python 2 or 3

Lecture 4 Data Storage

Section 2: Programming

Lecture 5 Operators

Lecture 6 Variables, Keywords and Names

Lecture 7 Statments

Lecture 8 Python Getting Started

Lecture 9 Basic Types in Python

Lecture 10 Variables in Python

Lecture 11 Basic Operators in Python

Lecture 12 Python Recourses for this Course

Section 3: Data Types and Data Systems

Lecture 13 Numeric Data Systems

Lecture 14 Data Types and Data Structures

Lecture 15 Python Nomeric Data Types

Lecture 16 Python String Data Type

Lecture 17 Python List Data Type

Lecture 18 Python Dictionary Data Type

Lecture 19 Python Tuple Data Type

Lecture 20 Python Set Data Type

Lecture 21 Python Date Time Data Type

Lecture 22 Ptheon Array Data Type

Section 4: Program Flow Controle

Lecture 23 Subroutines

Lecture 24 Conditional Statements

Lecture 25 Loops

Lecture 26 Objects Orientated

Lecture 27 Python Functions 1

Lecture 28 Python Functions 2

Lecture 29 Python Functions 3

Lecture 30 Python If, Elsif and Else

Lecture 31 Python Error Handling

Lecture 32 Python Loops: For Loop

Lecture 33 Python Loops: While Loop

Lecture 34 Python Classes Part 1

Lecture 35 Python Classes Part 2

Lecture 36 Python Dataclasses

Section 5: Notebooks

Lecture 37 NoteBooks

Lecture 38 Jupyter Notebook Markdown

Lecture 39 Python Working With Files

Lecture 40 Introduction to Dataframes

Lecture 41 Dataframes Data Cleanup

Lecture 42 DataFrames Data Analyses: Group Data

Lecture 43 Conclusion

Non-developer professionals who want to learn programming to improve productivity and atomize thee workflows,People who want to learn the basics of computer programming

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