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Complete Python Programming
Blackboard Learning

Python programming, python basic data, python advanced data and much more

Summary

Price
£19 inc VAT
Study method
Online, On Demand
Duration
14.9 hours · Self-paced
Qualification
No formal qualification
Certificates
  • Reed Courses Certificate of Completion - Free
Additional info
  • Tutor is available to students

Overview

Python is a dynamically semantic, interpreted, object-oriented, high-level programming language. Its high-level built-in data structures make it ideal for fast application development and as a scripting or glue language for connecting existing components. Python's concise, easy-to-learn syntax prioritizes readability, which lowers software maintenance costs. The edit-test-debug cycle is really quick because no compilation is required. A defect or incorrect input will never trigger a segmentation fault in a Python application, so debugging them is simple. Python is widely used for web and software development, task automation, data analysis, and data visualization. Due to its relative ease of learning, Python has been used by many non-programmers, such as accountants and scientists, for a variety of common tasks, such as arranging finances.

By completing this Complete Python Programming, you will gain more knowledge along with practical tips and advice that will help you learn every aspect of the Learn Python Programming from A-Z Course. This Learn Python Programming from A-Z course gives you the courage to pursue a career as a Python programmer or in careers related to Python programming.

This Complete Python Programming is designed with many relevant video classes, PDFs, and exercises. So, after completing this Complete Python Programming, you will be completely ready with all the requirements to be a web developer in today’s job market.

Certificates

Reed Courses Certificate of Completion

Digital certificate - Included

Will be downloadable when all lectures have been completed.

Curriculum

1
section
116
lectures
14h 57m
total

    • 1: 1. Control Flow Part 1 (section overview) 15:01
    • 2: 1. Control Flow Part 2 (section overview) 02:29
    • 3: 1. Error Handling and User Input (section overview) 01:49
    • 4: 1. Intro To Python Programming 05:21
    • 5: 1. Python Advanced Functions (section overview) 05:11
    • 6: 1. Python Functions (section overview) 02:50
    • 7: 1. Scripting and Libraries (section overview) 04:30
    • 8: 1.1 What is Python Programming 09:30
    • 9: 1.2 Installing Python on Windows 09:36
    • 10: 1.3 Anaconda and Jupyter Notebooks 1 07:31
    • 11: 1.4 Python Marketplace 05:47
    • 12: 1.5 Who is This Course For 04:33
    • 13: 1.6 Python Job Opportunities 04:43
    • 14: 1.7 Python Job Roles 08:41
    • 15: 1.8 Python Course Structure 04:19
    • 16: 1. Getting Familiar With Python (section overview) 05:56
    • 17: 2.2 Anaconda and Jupyter Notebooks 2 16:24
    • 18: 2.3 Strings Overview 09:50
    • 19: 2.4 Comments 05:01
    • 20: 2.5 Python Syntax 02:13
    • 21: 2.6 Line Structure 02:44
    • 22: 2.6.2 Line Structure 07:12
    • 23: 2.7 Joining Lines 05:00
    • 24: 2.8 Printing 09:48
    • 25: 2.9 Multiple Statements on a Single Line 04:52
    • 26: 2.10. Indentation 07:40
    • 27: 1. Python Operators (section overview) 04:12
    • 28: 3.1 Python Variables 08:10
    • 29: 3.2 Integers and Float 08:26
    • 30: 3.3 Comparison Operators 09:20
    • 31: 3.4 String Manipulation 07:18
    • 32: 3.5 String Indexing 04:28
    • 33: 3.6 String Slicing 08:17
    • 34: 3.7 Booleans 04:54
    • 35: 4.1 Arithmetic Operators 08:17
    • 36: 4.2 Assignment Operators 03:40
    • 37: 4.3 Getting a python job w.o degree 08:20
    • 38: 4.4 Logical Operators 12:37
    • 39: 4.5 Identity Operators (Need slide update as (Equality is misspelled) 04:41
    • 40: 4.6 Membership Operators 02:02
    • 41: 4.7 Bitwise Operators 07:50
    • 42: 1. Python Advanced Data Types (section overview) 10:37
    • 43: 5.1 List Overview 04:39
    • 44: 5.2 List Indexing and Slicing 04:26
    • 45: 5.3 Tuples 02:20
    • 46: 5.4 For Loops 09:51
    • 47: 5.5 Dictionary 10:40
    • 48: 5.6 When to use each one 04:31
    • 49: 5.7 Compound Data Types 02:44
    • 50: 6.1 Intro to Control Flow 00:57
    • 51: 6.2 Basic Conditional Statements 13:39
    • 52: 6.3 More Conditional Statements 05:04
    • 53: 6.5 While Loops 11:47
    • 54: 7.1 Break Statements 08:00
    • 55: 7.2 Continue Statements 04:52
    • 56: 7.3 Zip Function 07:20
    • 57: 7.4 Enumerate Function 03:58
    • 58: 7.5 List Comprehension 04:28
    • 59: 8.1 Intro to Functions 02:17
    • 60: 8.2 Python Help Function 03:12
    • 61: 8.3 Defining Functions 09:29
    • 62: 8.4 Variable Scope 08:13
    • 63: 8.5 DocStrings 03:44
    • 64: 9.1 Intro to Error Handling 02:48
    • 65: 9.2 User Input 04:22
    • 66: 9.3 Syntax Errors 04:00
    • 67: 9.4 Exceptions 11:23
    • 68: 9.5 Handling Exceptions 1 08:29
    • 69: 9.6 Handling Exceptions 2 08:18
    • 70: 10.1 Lambda Functions 05:29
    • 71: 10.2 Functions args and kwargs 10:02
    • 72: 10.3 Iterators 08:13
    • 73: 10.4 Generators and Yield 11:53
    • 74: 10.5 Map Functions 14:24
    • 75: 10.6 Filter 08:03
    • 76: 11.1 What is a script. 01:24
    • 77: 11.2 What is an IDE 17:20
    • 78: 11.3 What is a text editor 11:46
    • 79: 11.4 from jupyter notebook to vscode 1 14:45
    • 80: 11.5 from jupyter notebook to vscode 2 05:03
    • 81: 11.6 Importing Scripts 03:05
    • 82: 11.7 Standard Libraries 04:13
    • 83: 11.8 Third Party Libraries 05:35
    • 84: 1. Numpy section overview 04:08
    • 85: 12.1 What is NumPy 04:28
    • 86: 12.2 Why NumPy 04:10
    • 87: 12.3 NumPy Arrays 10:24
    • 88: 12.4 Reshaping, Modifying and Accessing NumPy arrays 07:20
    • 89: 12.5 Slicing and Copying 05:53
    • 90: 12.6 Inserting , Deleting, Appending 09:45
    • 91: 12.7 Logical Indexing 03:44
    • 92: 12.8 Broadcasting 08:20
    • 93: 12.1 Pandas 16:44
    • 94: 12.2 Pandas Series 16:59
    • 95: 12.4 Pandas DataFrame 17:04
    • 96: 12.5 Pandas DataFrame Manipulation 12:55
    • 97: 12.6 Dealing with Missing Values 10:09
    • 98: 13.3 Pandas Series Manipulation 16:32
    • 99: 15.1 Functional vs OOP 06:16
    • 100: 15.2 OOP key defintions 04:04
    • 101: 15.3 Create your First Class 12:09
    • 102: 15.4 How to create and use Objects 06:04
    • 103: 15.5 Modifying Attributes 12:29
    • 104: 16.1 Python Decorators 27:09
    • 105: 16.2 Property Decorator 08:44
    • 106: 16.3 Class Methods Decorator 07:11
    • 107: 16.4 Static Methods Decorators 10:29
    • 108: 16.5 Inheritance 20:36
    • 109: 1. Starting a Career in Python Overview 05:56
    • 110: a. Getting Started with Freelancing 09:26
    • 111: b. Building a Brand 11:57
    • 112: c. Personal Branding 13:09
    • 113: d. Importance of Website Blog 04:22
    • 114: e. Networking Do_s Don_ts 05:31
    • 115: f. Top Freelance Sites 08:05
    • 116: g. Creating a Python Developer Resume 06:01

Course media

Description

You will have the best guidelines given by our expert trainers who are experienced in Python programming. Under the supervision of these trainers, along with the provided video classes and PDFs, you can unleash your Python programming skills to the top and have a strong position in the job market.

What will you learn from this course:

  • Circuit design: What you need to know
  • Arduino real-time plotting with Python: Tailoring your approach to maximize impact
  • Mastering Arduino coding

Program content:

  • Section 1: Introduction to Complete Python Programming
  • Intro To Python Section Overview
  • What is Python Programming?
  • Who is This Course For?
  • Python Programming Marketplace
  • Python Job Opportunities
  • How to Land a Python Job w/o a Degree
  • Python Programmer Job Roles
  • Section 2: Getting Familiar with Python
  • Getting Familiar with Python Overview
  • Installing Python on Windows
  • Anaconda and Jupyter Notebooks Part 1
  • Anaconda and Jupyter Notebooks Part 2
  • Python Syntax
  • Python Line Structure
  • Line Structure Exercise
  • Python Comments
  • Joining Lines in Python
  • Working with Multiple Statements on a Single Line
  • Indentation
  • Section 3: Python Basic Data Types
  • Python Basic Data Types Overview
  • Python Variables
  • Integers and Floats
  • String Overview
  • String Manipulation
  • String Indexing
  • String Slicing
  • Working with Boolean
  • Printing Function
  • Mini Project - Letter Counter
  • Section 4: Python Operators
  • Python Operators Overview
  • Arithmetic Operators
  • Assignment Operators
  • Comparison Operators
  • Logical Operators
  • Identity Operators
  • Membership Operators
  • Bitwise Operators
  • Section 5: Python Advanced Data Types
  • Python Advanced Data Types Overview
  • Python Lists
  • List Slicing and Indexing
  • Python Tuples
  • Python Sets
  • Python Dictionaries
  • When To Use Each One?
  • Compound Data Types
  • Section 6: Python Control Flow Part 1
  • Python Control Flow Part 1 Overview
  • Intro To Control Flow
  • More Conditional Statements
  • For Loops
  • While Loops
  • Section 7: Python Control Flow Part 2
  • Python Control Flow Part 2 Overview
  • Break Statements
  • Continue Statements
  • Zip Function
  • Enumerate Function
  • List Comprehension
  • Section 8: Python Functions
  • Python Function Overview
  • Intro To Functions
  • Python Help Functions
  • Defining Functions
  • Variable Scope
  • Doc Strings
  • Section 9: User Input and Error Handling
  • User Input and Error Handling Overview
  • Intro To Error Handling
  • User Input
  • Syntax Errors
  • Exceptions
  • Handling Exceptions Part 1
  • Handling Exceptions Part 2
  • Section 10: Python Advanced Functions
  • Python Advanced Function Overview
  • Lambda Functions
  • Functions args and kwargs
  • Python Iterators
  • Generators and Yield
  • Map Function
  • Filter Function
  • Section 11: Python Scripting and Libraries
  • Python Scripting and Libraries Overview
  • What is a Script?
  • What is an IDE?
  • What is a Text Editor?
  • From Jupyter Notebook to VScode Part 1
  • From Jupyter Notebook to VScode Part 2
  • Importing Scripts
  • Standard Libraries
  • Third-Party Libraries
  • Section 12: NumPy
  • NumPy Overview
  • Intro To NumPy
  • Why Use NumPy
  • NumPy Arrays
  • Reshaping, Accessing, and Modifying
  • Slicing and Copying
  • Inserting, Appending, and Deleting
  • Array Logical Indexing
  • Broadcasting
  • Section 13: Pandas
  • Intro To Pandas
  • Pandas Series
  • Pandas Series Manipulation
  • Pandas DataFrame
  • Pandas DataFrame Manipulation
  • Dealing with Missing Values
  • Section 14: Intro To OOP
  • Functional vs OOP
  • OOP Key Definitions
  • Create Your First Class
  • How to Create and Use Objects
  • How To Modify Attributes
  • Section 15: Advanced OOP
  • Python Decorators
  • Property Decorator
  • Class Method Decorator
  • Static Methods
  • Inheritance from A-Z
  • Section 16: Starting a Career in Python
  • Python Career Overview
  • Getting Started with Freelancing
  • Building a Brand
  • Personal Branding
  • Importance of Having a Website/Blog
  • Networking
  • Top Freelance Websites
  • Creating a Python Developer Resume

Blackboard Learning is an online learning platform by which students from any corner of the world can learn his/her desired course. Using online learning, we assist students in realizing their full potential and advancing their careers. Today, our goal is to be the world's leading provider of online learning experiences with a global impact. By leveraging online learning, we assist students in preparing for bright futures in world-changing jobs. We provide a wide range of categories including Accounting & IT, Programming, Creative, and more. Our courses are designed to stretch students intellectually through state-of-the-art online learning.

Who is this course for?

  • For people looking to progress their career into a Python programmer.
  • For those who want to become web developers, as well as looking to further develop their skills and knowledge.
  • People who want to perform better in Python-related careers.
  • Those who are passionate about python related skills.
  • Learners who desire to be more efficient in Python programming.

Requirements

No prior knowledge or experience required

Career path

  • Circuit designing
  • Lambda functions
  • Vectorizing and cosine similarity
  • Data visualisation

Questions and answers

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Legal information

This course is advertised on Reed.co.uk by the Course Provider, whose terms and conditions apply. Purchases are made directly from the Course Provider, and as such, content and materials are supplied by the Course Provider directly. Reed is acting as agent and not reseller in relation to this course. Reed's only responsibility is to facilitate your payment for the course. It is your responsibility to review and agree to the Course Provider's terms and conditions and satisfy yourself as to the suitability of the course you intend to purchase. Reed will not have any responsibility for the content of the course and/or associated materials.

FAQs

Study method describes the format in which the course will be delivered. At Reed Courses, courses are delivered in a number of ways, including online courses, where the course content can be accessed online remotely, and classroom courses, where courses are delivered in person at a classroom venue.

CPD stands for Continuing Professional Development. If you work in certain professions or for certain companies, your employer may require you to complete a number of CPD hours or points, per year. You can find a range of CPD courses on Reed Courses, many of which can be completed online.

A regulated qualification is delivered by a learning institution which is regulated by a government body. In England, the government body which regulates courses is Ofqual. Ofqual regulated qualifications sit on the Regulated Qualifications Framework (RQF), which can help students understand how different qualifications in different fields compare to each other. The framework also helps students to understand what qualifications they need to progress towards a higher learning goal, such as a university degree or equivalent higher education award.

An endorsed course is a skills based course which has been checked over and approved by an independent awarding body. Endorsed courses are not regulated so do not result in a qualification - however, the student can usually purchase a certificate showing the awarding body's logo if they wish. Certain awarding bodies - such as Quality Licence Scheme and TQUK - have developed endorsement schemes as a way to help students select the best skills based courses for them.
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