Python Programming & Coding - CPD Certified

Why Study This Python Programming & Coding Diploma?

• According to industry insights, Python is one of the most sought-after programming languages, with a rising demand for Python developers in fields ranging from web development to data science and artificial intelligence.
• According to the UK Tech Salaries 2023 report by CodeinWP, Python developers earn an average salary of £55,000 per year.
• The demand for Python developers globally is expected to grow by 30% in the next five years.
• According to Indeed, the number of job postings for Python developers in the UK has increased by 50% in the past year.

Learning Outcomes:

• Delve into the foundational Python structures: strings, lists, and dictionaries.
• Familiarise yourself with Python's Object-Oriented Programming (OOP) concepts.
• Discover the process of crafting a Python program from the ground up.
• Grasp how to compute, fetch, and store data utilising Python variables.
• Master Functions in Python.

CPDQE Accreditation:

This Python Programming & Coding Diploma is CPDQE accredited. CPD is a globally recognised parameter for continuous professional development acknowledged by thousands of professional bodies, employers and academic institutions in the UK and around the world.

Dual Certificates:

After completing this Python Programming & Coding Diploma, you will receive a course completion certificate from Reed. Also, you will receive an Accredited Certificate of Completion from SkillArts.

Accredited Certificate of Completion From SkillArts

Digital certificate - Included

Reed Courses Certificate of Completion

Digital certificate - Included

SkillArts Official Transcript

Digital certificate - £3

• Python Programming: Course Intro 04:37

  • 1: Python Programming: Promo Preview 04:37

• Python Coding 101 51:11

  • 2: Python: Intro To Python Programming 05:20
  • 3: Python: What is Python Programming 09:30
  • 4: Python: Who is This Course For 04:33
  • 5: Python: Marketplace 05:46
  • 6: Python: Job Opportunities 04:43
  • 7: Python: Job Roles 08:41
  • 8: Python: Course Structure 04:18
  • 9: Python: Getting a python job w.o degree 08:20

• Getting Familiar With Python 1:15:05

  • 10: Python: Getting Familiar With Python (section overview) 05:56
  • 11: Python: Installing Python on Windows 09:36
  • 12: Python: Anaconda and Jupyter Notebooks 1 07:30
  • 13: Python: Anaconda and Jupyter Notebooks 2 16:24
  • 14: Python: Comments 05:01
  • 15: Python: Python Syntax 02:13
  • 16: Python: Line Structure 02:43
  • 17: Python: Line Structure 07:11
  • 18: Python: Joining Lines 05:00
  • 19: Python: Multiple Statements on a Single Line 04:52
  • 20: Python: Indentation 07:39
  • 21: Care for a feedback? 01:00

• Python Data Types 1:29:27

  • 22: Python: Basic Data Types (section overview) 08:25
  • 23: Python: Strings Overview 09:50
  • 24: Python: String Manipulation 07:17
  • 25: Python: String Indexing 04:28
  • 26: Python: String Slicing 08:16
  • 27: Python: Printing 09:48
  • 28: Python: Python Variables 08:09
  • 29: Python: Integers and Float 08:26
  • 30: Python: Booleans 04:53
  • 31: Python: Mini-Project 1 - Letter Counter (1) 19:55

• Python Operators 52:35

  • 32: Python: Operators (section overview) 04:11
  • 33: Python: Comparison Operators 09:20
  • 34: Python: Arithmetic Operators 08:17
  • 35: Python: Assignment Operators 03:40
  • 36: Python: Logical Operators 12:36
  • 37: Python: Identity Operators (Need slide update as (Equality is misspelled) 04:41
  • 38: Python: Membership Operators 02:01
  • 39: Python: Bitwise Operators 07:49

• Python Advanced Data Types 45:55

  • 40: Python: Python Advanced Data Types (section overview) 10:37
  • 41: Python: List Overview 04:38
  • 42: Python: List Indexing and Slicing 04:25
  • 43: Python: Tuples 02:20
  • 44: Python: Sets 06:01
  • 45: Python: Dictionary 10:40
  • 46: Python: When to use each one 04:31
  • 47: Python: Compound Data Types 02:43

• Python Control Flow 1 56:14

  • 48: Python: Control Flow Part 1 (section overview) 15:00
  • 49: Python: Intro to Control Flow 00:56
  • 50: Python: Basic Conditional Statements 13:38
  • 51: Python: For Loops 09:50
  • 52: Python: While Loops 11:46
  • 53: Python: More Conditional Statements 05:04

• Python Control Flow 2 31:03

  • 54: Python: Control Flow Part 2 (section overview) 02:28
  • 55: Python: Break Statements 07:59
  • 56: Python: Continue Statements 04:51
  • 57: Python: Zip Function 07:20
  • 58: Python: Enumerate Function 03:58
  • 59: Python: List Comprehension 04:27

• Intro to Functions 29:41

  • 60: Python: Python Functions (section overview) 02:49
  • 61: Python: Intro to Functions 02:16
  • 62: Python: Help Function 03:11
  • 63: Python: Defining Functions 09:29
  • 64: Python: Variable Scope 08:12
  • 65: Python: Doc Strings 03:44

• User Input and Error Handling 41:05

  • 66: Python: Error Handling and User Input (section overview) 01:48
  • 67: Python: Intro to Error Handling 02:48
  • 68: Python: User Input 04:21
  • 69: Python: Syntax Errors 04:00
  • 70: Python: Exceptions 11:22
  • 71: Python: Handling Exceptions 1 08:29
  • 72: Python: Handling Exceptions 2 08:17

• Advanced Functions of Python Programming 1:03:12

  • 73: Python: Advanced Functions (section overview) 05:10
  • 74: Python: Lambda Functions 05:29
  • 75: Python: Functions args and kwargs 10:01
  • 76: Python: Iterators 08:12
  • 77: Python: Generators and Yield 11:53
  • 78: Python: Map Functions 14:24
  • 79: Python: Filter 08:03

• Scripting and Libraries 1:07:39

  • 80: Python: Scripting and Libraries (section overview) 04:29
  • 81: Python: What is a script. 01:24
  • 82: Python: What is an IDE 17:20
  • 83: Python: What is a text editor 11:46
  • 84: Python: From jupyter notebook to vs code 1 14:45
  • 85: Python: From jupyter notebook to vs code 2 05:03
  • 86: Python: Importing Scripts 03:04
  • 87: Python: Standard Libraries 04:13
  • 88: Python: Third Party Libraries 05:35

• NumPy 58:06

  • 89: Python: Numpy section overview 04:07
  • 90: Python: What is NumPy 04:28
  • 91: Python: Why NumPy 04:09
  • 92: Python: NumPy Arrays 10:23
  • 93: Python: Reshaping, Modifying and Accessing NumPy arrays 07:19
  • 94: Python: Slicing and Copying 05:52
  • 95: Python: Inserting , Deleting, Appending 09:45
  • 96: Python: Logical Indexing 03:43
  • 97: Python: Broadcasting 08:20

• Pandas 1:30:20

  • 98: Python: Pandas 16:43
  • 99: Python: Pandas Series 16:58
  • 100: Python: Pandas DataFrame 17:04
  • 101: Python: Pandas Data Frame Manipulation 12:54
  • 102: Python: Dealing with Missing Values 10:09
  • 103: Python: Pandas Series Manipulation 16:32

• Intro To OOP 41:01

  • 104: Python: Functional vs OOP 06:16
  • 105: Python: OOP key defintions 04:04
  • 106: Python: Create your First Class 12:09
  • 107: Python: How to create and use Objects 06:04
  • 108: Python: Modifying Attributes 12:28

• Advanced OOP 1:14:07

  • 109: Python: Decorators 27:09
  • 110: Python: Property Decorator 08:43
  • 111: Python: Class Methods Decorator 07:11
  • 112: Python: Static Methods Decorators 10:28
  • 113: Python: Inheritance 20:36

• Career in Python 1:05:22

  • 114: Python: Starting a Career in Python Overview 05:55
  • 115: Python: Getting Started with Freelancing 09:26
  • 116: Python: Building a Brand 11:56
  • 117: Python: Personal Branding 13:08
  • 118: Python: Importance of Website Blog 04:22
  • 119: Python: Networking Do_s Don_ts 05:31
  • 120: Python: Top Freelance Sites 08:04
  • 121: Python: Creating a Python Developer Resume 06:00
  • 122: Thank You ! 01:00

• Python Programming: Final Exam 03:00

  • 123: Python Programming: Final Exam 03:00

• Claim Your Free Certificate 01:00

  • 124: Claim Your Free Certificate 01:00

Python Programming & Coding Course Syllabus:

• Python Coding Fundamentals
• Python Programming Introduction
• Advanced Python Programming
• Python for Beginners
• Python Job Market Insights
• Python Career Pathways
• Python Course Framework
• Securing a Python Role Without a Degree
• Python Installation Guide
• Python with Anaconda and Jupyter
• Python Commenting Techniques
• Python Syntax Essentials
• Python Line Structure Mastery
• Python Statements and Indentation
• Python Data Types Deep Dive
• Python Strings and Manipulation
• Python Variables and Data Structures
• Python Operators Comprehensive Guide
• Python Advanced Data Types
• Python Control Flow Mechanisms
• Python Functions Explained
• Python Error Handling Strategies
• Python Advanced Functions
• Python Scripting Essentials
• Python Libraries Overview

• Python & Data Scientist
• Financial Analyst
• Python Developer
• Python Data Analyst
• Individuals new to Python programming language
• Data Scientists transitioning to Python from other analytical tools
• Aspiring Python Data Analysts
• Newcomers to Python development and coding

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