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After completing the Python Programming Course assessments, learners qualify for a CPD QS accredited certificate from One Education.
The certificate is available in two formats: a PDF version for £9 or a printed hard copy delivered by post for £15.
Python Programming: Beginner To Expert
Python Programming: Beginner to Expert introduces Python from the basics through to advanced concepts. This course covers syntax, data structures, functions, and real-world applications, helping learners build a strong understanding of Python programming for personal development and technical skill growth.
Python Programming: Beginner To Expert
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Overview of Python Programming Course
This Python Programming course introduces beginners to core concepts, inspired by Python Institute guidance, covering syntax, data types and operators while building confidence through structured lessons and practical examples practice.
Learning progresses through control flow, functions, scripting, NumPy and Pandas, reflecting approaches seen on Pluralsight, DataCamp, LinkedIn Learning, Real Python and SoloLearn for developing practical, job-ready Python skills efficient programming.
Advanced OOP, error handling and career guidance prepare learners for real-world development, supporting progression into Python roles by strengthening problem-solving ability, portfolio readiness and confidence for professional programming environments globally.
Learning Outcomes of Python Programming Course
- Understand Python programming fundamentals, syntax rules, and core programming concepts.
- Write efficient Python code using variables, data types, and operators confidently.
- Apply control flow techniques including loops and conditional statements effectively.
- Develop reusable programs using Python functions and modular coding practices.
- Handle user input, exceptions, and errors to build reliable Python applications.
- Work with libraries such as NumPy and Pandas for data manipulation tasks.
- Implement object-oriented programming principles to design structured applications.
- Build a strong foundation for pursuing further study or entry-level Python roles.
Method Of Assessment
Learners complete an assignment designed to evaluate their understanding of the course content. The assignment is reviewed by qualified tutors who provide personalised feedback, allowing learners to demonstrate their applied knowledge and skills.
Certification
Quality Licence Scheme Endorsed Certificate
Learners also have the option to order a Quality Licence Scheme (QLS) Endorsed Certificate as additional proof of achievement. The QLS Endorsed Certificate can be delivered by post for £129, with an additional £10 postage charge for international students.
Endorsement
This course has been endorsed by the Quality Licence Scheme for its high-quality, non-regulated provision and training programmes. This course is not regulated by Ofqual and is not an accredited qualification. Your training provider will be able to advise you on any further recognition, for example progression routes into further and/or higher education. For further information please visit the Learner FAQs on the Quality Licence Scheme website.
Why Study This Python Programming Course?
Python is one of the most in-demand programming languages across technology, business, and data-driven industries. Its simplicity and versatility make it a preferred choice for beginners, while its power supports advanced applications such as data analysis, automation, and software development.
Studying a Python Programming course strengthens problem-solving skills, builds technical confidence, and opens pathways into modern digital careers. CPD certification highlights commitment to continuous learning and adds practical value to professional profiles across multiple sectors.
Course Duration
The Python Programming Course is designed with a total learning period of 3 weeks and 4 days. This timeframe allows learners to progress steadily through the course content while balancing other commitments, ensuring sufficient time to build confidence and practical understanding throughout the programme.
Requirements
The Python Programming course has straightforward and accessible entry requirements. Learners only need basic computer skills, logical thinking, and an interest in programming or technology. No prior coding experience is required. The course is delivered fully online and can be accessed from any internet-enabled device, allowing learners to study comfortably from home with complete flexibility.
Career Path
- Python Developer: £35,000 – £65,000 per year
- Junior Software Developer: £25,000 – £35,000 per year
- Data Analyst (Python): £30,000 – £50,000 per year
- Automation Engineer: £32,000 – £55,000 per year
- Backend Developer: £38,000 – £70,000 per year
- Machine Learning Engineer (Entry to Mid-Level): £40,000 – £75,000 per year
Frequently Asked Questions
Yes, the course is designed for learners with no prior programming experience and starts with Python fundamentals before moving to advanced concepts.
You will gain practical skills in Python syntax, data handling, problem-solving, scripting, and working with popular libraries such as NumPy and Pandas.
Yes, the course includes practical examples and exercises to help learners understand how Python is used in real-world scenarios.
Completion time varies by learner, but most students finish the course within a few weeks depending on their study schedule.
The course helps build in-demand Python skills that can support career development in fields such as data analysis, automation, and software development.
Yes, a CPD-accredited certificate is available upon successful completion of the course and assessment.
Course Curriculum
| Module 01: Introduction to Python Programming from A-Z | |||
| Intro To Python Section Overview | 00:05:00 | ||
| What is Python Programming | 00:09:00 | ||
| Who is This Course For | 00:05:00 | ||
| Python Programming Marketplace | 00:00:00 | ||
| Python Job Opportunities | 00:05:00 | ||
| How To Land a Python Job Without a Degree | 00:08:00 | ||
| Python Programmer Job Roles | 00:09:00 | ||
| Python from A-Z Course Structure | 00:04:00 | ||
| Module 02: Getting Familiar with Python | |||
| Getting Familiar with Python Section Overview | 00:06:00 | ||
| Installing Python on Windows | 00:10:00 | ||
| Anaconda and Jupyter Notebooks Part 1 | 00:08:00 | ||
| Anaconda and Jupyter Notebooks Part 2 | 00:16:00 | ||
| Comments | 00:05:00 | ||
| Python Syntax | 00:02:00 | ||
| Line Structure | 00:03:00 | ||
| Line Structure Exercise | 00:07:00 | ||
| Joining Lines | 00:00:00 | ||
| Multiple Statements on a Single Line | 00:05:00 | ||
| Indentation | 00:08:00 | ||
| Module 03: Basic Data Types | |||
| Basic Data Types Section Overview | 00:08:00 | ||
| String Overview | 00:10:00 | ||
| String Manipulation | 00:07:00 | ||
| String Indexing | 00:04:00 | ||
| String Slicing | 00:08:00 | ||
| Printing | 00:10:00 | ||
| Python Variables | 00:08:00 | ||
| Integers and Floats | 00:08:00 | ||
| Booleans | 00:05:00 | ||
| Mini Project 1 : Letter Counter | 00:20:00 | ||
| Module 04: Python Operators | |||
| Python Operators Section Overview | 00:04:00 | ||
| Comparison Operators | 00:09:00 | ||
| Arithmetic Operators | 00:08:00 | ||
| Assignment Operators | 00:04:00 | ||
| Logical Operators | 00:13:00 | ||
| Identity Operators | 00:05:00 | ||
| Membership Operators | 00:02:00 | ||
| Bitwise Operators | 00:08:00 | ||
| Module 05: Advanced Data Types | |||
| Python Advanced Data Types Section Overview | 00:11:00 | ||
| Sets | 00:06:00 | ||
| List Overview | 00:05:00 | ||
| List Slicing and Indexing | 00:04:00 | ||
| Tuples | 00:02:00 | ||
| Dictionaries | 00:11:00 | ||
| When to use each one? | 00:05:00 | ||
| Compound Data Types | 00:03:00 | ||
| Module 06: Control Flow Part 1 | |||
| Control Flow Part 1 Section Overview | 00:15:00 | ||
| Intro to Control Flow | 00:01:00 | ||
| Basic Conditional Statements | 00:14:00 | ||
| More Conditional Statements | 00:00:00 | ||
| For Loops | 00:10:00 | ||
| While Loops | 00:12:00 | ||
| Module 07: Control Flow Part 2 | |||
| Control Flow Part 2 Section Overview | 00:02:00 | ||
| Break Statements | 00:08:00 | ||
| Continue Statements | 00:05:00 | ||
| Zip Function | 00:07:00 | ||
| Enumerate Function | 00:04:00 | ||
| List Comprehension | 00:04:00 | ||
| Module 08: Python Functions | |||
| Python Functions Section Overview | 00:03:00 | ||
| Intro to Functions | 00:02:00 | ||
| Python help Function | 00:03:00 | ||
| Defining Functions | 00:09:00 | ||
| Variable Scope | 00:08:00 | ||
| Doc Strings | 00:04:00 | ||
| Module 09: User Input and Error Handling | |||
| User Input and Error Handling Section Overview | 00:02:00 | ||
| Introduction to error handling | 00:03:00 | ||
| User Input | 00:04:00 | ||
| Syntax Errors | 00:04:00 | ||
| Exceptions | 00:11:00 | ||
| Handling Exceptions Part 1 | 00:08:00 | ||
| Handling Exceptions Part 2 | 00:08:00 | ||
| Module 10: Python Advanced Functions | |||
| Python Advanced Functions Section Overview | 00:05:00 | ||
| Lambda Functions | 00:05:00 | ||
| Functions args and kwargs | 00:10:00 | ||
| Iterators | 00:08:00 | ||
| Generators and Yield | 00:12:00 | ||
| Map Function | 00:14:00 | ||
| Filter Function | 00:00:00 | ||
| Module 11: Python Scripting and Libraries | |||
| Python Scripting and Libraries Section Overview | 00:04:00 | ||
| What is a script | 00:01:00 | ||
| What is an IDE | 00:17:00 | ||
| What is a text editor? | 00:12:00 | ||
| From Jupyter Notebook to VScode Part 1 | 00:15:00 | ||
| From Jupyter Notebook to VScode Part 2 | 00:05:00 | ||
| Importing Scripts | 00:03:00 | ||
| Standard Libraries | 00:04:00 | ||
| Third Party Libraries | 00:06:00 | ||
| Module 12: NumPy | |||
| NumPy Section Overview | 00:04:00 | ||
| Intro to NumPy | 00:04:00 | ||
| Why use NumPy? | 00:04:00 | ||
| NumPy Arrays | 00:10:00 | ||
| Reshaping, Accessing, and Modifying | 00:07:00 | ||
| Slicing and Copying | 00:06:00 | ||
| Inserting, Appending, and Deleting | 00:10:00 | ||
| Array Logical Indexing | 00:04:00 | ||
| Broadcasting | 00:08:00 | ||
| Module 13: Pandas | |||
| Intro to Pandas | 00:17:00 | ||
| Pandas Series | 00:17:00 | ||
| Pandas Series Manipulation | 00:17:00 | ||
| Pandas DataFrame | 00:17:00 | ||
| Pandas DataFrame Manipulation | 00:13:00 | ||
| Dealing with Missing Values | 00:10:00 | ||
| Module 14: Introduction to OOP | |||
| Functional vs OOP | 00:06:00 | ||
| OOP Key Definitions | 00:04:00 | ||
| Create your First Class | 00:12:00 | ||
| How to Create and Use Objects | 00:06:00 | ||
| How to Modify Attributes | 00:12:00 | ||
| Module 15: Advanced OOP | |||
| Python Decorators | 00:27:00 | ||
| Property Decorator | 00:09:00 | ||
| Class Method Decorator | 00:07:00 | ||
| Static Methods | 00:10:00 | ||
| Inheritance from A to Z | 00:21:00 | ||
| Module 16: Starting a Career in Python | |||
| Python Career Section Overview | 00:06:00 | ||
| Getting Started with Freelancing | 00:09:00 | ||
| Building A Brand | 00:12:00 | ||
| Personal Branding | 00:13:00 | ||
| Importance of Having Website/Blog | 00:04:00 | ||
| Do’s and Don’ts of Networking | 00:06:00 | ||
| Top Freelance Websites | 00:08:00 | ||
| Creating A Python Developer Resume | 00:06:00 | ||
| Resources | |||
| Resources – Python Programming: Beginner To Expert | 00:00:00 | ||
| Assignment | |||
| Assignment – Python Programming: Beginner To Expert | 3 weeks, 4 days | ||
| Order Your Certificate | |||
| Order Your Certificate QLS | 00:00:00 | ||
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