Course Overview
Structured into 20 modules and 40 interactive lectures, this Python for Data Analysis course covers key areas such as:
- Python fundamentals: variables, data types, control flow, and functions
- Data analysis using NumPy and Pandas
- Data visualisation using Matplotlib, Seaborn, and Plotly
- Interactive plotting and dashboard-ready visuals
- Machine Learning with scikit-learn: regression, classification, clustering
- Advanced techniques: PCA, recommender systems, NLP (Natural Language Processing)
- Final capstone project using real-world data
Whether you’re a beginner in coding or transitioning into data analytics, this CPD-accredited Python course gives you the tools, confidence, and certification to begin a rewarding career in data.
Enrol Now and Start Building Your Future in Data Analytics!
Learning Outcomes
By completing this Python for Data Analysis course, you will:
- Set up your Python programming environment using Jupyter, Anaconda, or Google Colab
- Write clean, functional Python code for data manipulation and automation
- Perform data wrangling with NumPy and Pandas
- Create professional visualisations using Matplotlib, Seaborn, and Plotly
- Build machine learning models like linear regression, decision trees, and SVMs
- Apply K-means clustering and dimensionality reduction techniques
- Analyse unstructured data with NLP (Natural Language Processing) using NLTK
- Complete a real-world capstone project in data analysis and visualisation
- Earn a CPD-accredited Python certificate recognised in the UK and internationally
Why Enrol in This Course?
By enrolling in the Python for Data Analysis course, you’ll learn programming and analytics skills that are in high demand across industries. This course aligns with current UK data analysis job market trends and offers:
- CPD accreditation and industry-relevant certification
- Lifetime access to all learning materials and future updates
- Full compatibility with desktop, mobile, and tablet
- No prior experience required—perfect for complete beginners
- Real-world applications across business, healthcare, fintech, and education
Whether you’re aiming to become a Python developer, data analyst, or AI professional, this course puts you on the right track.
Who is This Course for?
This Python for Data Analysis course is ideal for:
- Aspiring data analysts, machine learning engineers, and Python developers
- Students and graduates seeking technical skills for modern careers
- Business professionals aiming to work smarter with data
- Beginners who want to learn programming with no prior coding experience
- Tech enthusiasts exploring automation, AI, and visual analytics
With this Python diploma, you can confidently apply for data-related jobs or begin freelance/remote work in data analysis and visualisation.
Prerequisites for This Course
There are no formal prerequisites to enrol in the Python for Data Analysis course. It is suitable for:
- Beginners with zero programming background
- Professionals transitioning into data-related roles
- University students looking to boost employability
Anyone with a laptop and internet connection
Certification
Upon completing the course and passing the final exam, you will receive a CPD QS Accredited Certificate from Apex Learning. This certification demonstrates your knowledge and skills as a nursing assistant in the UK. The Digital version of the certificate is available for £9.99 only, and you can order a hard copy of the certificate for £14.99 only.
Career Path
Completing the Python for Data Analysis course opens the door to several high-paying and future-proof roles in the UK tech and data sectors, including:
- Python Developer
Write, test, and deploy Python scripts and applications.
Average UK Salary: £40,000 – £70,000 - Data Analyst
Interpret business data to make data-driven decisions.
Average UK Salary: £30,000 – £50,000 - Machine Learning Engineer
Design, build, and train machine learning models.
Average UK Salary: £50,000 – £80,000 - Data Scientist
Use Python to solve complex problems, visualise data, and build predictive models.
Average UK Salary: £55,000 – £90,000 - Business Intelligence Analyst
Provide actionable insights from data visualisation and analysis.
Average UK Salary: £35,000 – £60,000
With Python as your foundation, you can explore careers in AI, fintech, marketing analytics, automation, and more.
Python for Data Analysis | CPD Accredited Python Programming Course Online – UK
The demand for Python developers and data professionals in the UK has surged by over 30% in the past year. From finance and healthcare to tech and retail, Python has become the most sought-after skill in the world of data. The Python for Data Analysis course is a CPD-accredited, fully online training programme designed for anyone who wants to learn Python programming, data wrangling, data visualisation, and machine learning from the ground up.
This Python programming course provides essential skills to work confidently with real datasets, automate analysis, and build predictive models using libraries like NumPy, Pandas, Matplotlib, Seaborn, Plotly, and scikit-learn.
Course Overview
Structured into 20 modules and 40 interactive lectures, this Python for Data Analysis course covers key areas such as:
- Python fundamentals: variables, data types, control flow, and functions
- Data analysis using NumPy and Pandas
- Data visualisation using Matplotlib, Seaborn, and Plotly
- Interactive plotting and dashboard-ready visuals
- Machine Learning with scikit-learn: regression, classification, clustering
- Advanced techniques: PCA, recommender systems, NLP (Natural Language Processing)
- Final capstone project using real-world data
Whether you’re a beginner in coding or transitioning into data analytics, this CPD-accredited Python course gives you the tools, confidence, and certification to begin a rewarding career in data.
Enrol Now and Start Building Your Future in Data Analytics!
Learning Outcomes
By completing this Python for Data Analysis course, you will:
- Set up your Python programming environment using Jupyter, Anaconda, or Google Colab
- Write clean, functional Python code for data manipulation and automation
- Perform data wrangling with NumPy and Pandas
- Create professional visualisations using Matplotlib, Seaborn, and Plotly
- Build machine learning models like linear regression, decision trees, and SVMs
- Apply K-means clustering and dimensionality reduction techniques
- Analyse unstructured data with NLP (Natural Language Processing) using NLTK
- Complete a real-world capstone project in data analysis and visualisation
- Earn a CPD-accredited Python certificate recognised in the UK and internationally
Why Enrol in This Course?
By enrolling in the Python for Data Analysis course, you’ll learn programming and analytics skills that are in high demand across industries. This course aligns with current UK data analysis job market trends and offers:
- CPD accreditation and industry-relevant certification
- Lifetime access to all learning materials and future updates
- Full compatibility with desktop, mobile, and tablet
- No prior experience required—perfect for complete beginners
- Real-world applications across business, healthcare, fintech, and education
Whether you’re aiming to become a Python developer, data analyst, or AI professional, this course puts you on the right track.
Who is This Course for?
This Python for Data Analysis course is ideal for:
- Aspiring data analysts, machine learning engineers, and Python developers
- Students and graduates seeking technical skills for modern careers
- Business professionals aiming to work smarter with data
- Beginners who want to learn programming with no prior coding experience
- Tech enthusiasts exploring automation, AI, and visual analytics
With this Python diploma, you can confidently apply for data-related jobs or begin freelance/remote work in data analysis and visualisation.
Prerequisites
There are no formal prerequisites to enrol in the Python for Data Analysis course. It is suitable for:
- Beginners with zero programming background
- Professionals transitioning into data-related roles
- University students looking to boost employability
Anyone with a laptop and internet connection
Assessment Method
Assessment for the course is conducted through an automated multiple-choice exam. A score of 60% is required to pass and earn the CPD Accredited Certificate. Reflective assignments are provided to enhance your learning, with expert tutor feedback available.
Certification
Upon completing the course and passing the final exam, you will receive a CPD QS Accredited Certificate from Apex Learning. This certification demonstrates your knowledge and skills as a nursing assistant in the UK. The Digital version of the certificate is available for £9.99 only, and you can order a hard copy of the certificate for £14.99 only.
Career Path
Completing the Python for Data Analysis course opens the door to several high-paying and future-proof roles in the UK tech and data sectors, including:
- Python Developer
Write, test, and deploy Python scripts and applications.
Average UK Salary: £40,000 – £70,000 - Data Analyst
Interpret business data to make data-driven decisions.
Average UK Salary: £30,000 – £50,000 - Machine Learning Engineer
Design, build, and train machine learning models.
Average UK Salary: £50,000 – £80,000 - Data Scientist
Use Python to solve complex problems, visualise data, and build predictive models.
Average UK Salary: £55,000 – £90,000 - Business Intelligence Analyst
Provide actionable insights from data visualisation and analysis.
Average UK Salary: £35,000 – £60,000
With Python as your foundation, you can explore careers in AI, fintech, marketing analytics, automation, and more.
Frequestly Asked Questions
What is the Python for Data Analysis course?
A CPD-accredited online course that teaches Python programming, data analytics, data visualisation, and machine learning techniques.
Do I need any experience with coding?
No. This course is designed for complete beginners and includes setup and foundational programming lectures.
What tools will I learn in this Python course?
You’ll work with Python libraries such as NumPy, Pandas, Matplotlib, Seaborn, Plotly, Scikit-learn, and NLTK.
Will I learn machine learning in this course?
Yes. The course covers supervised and unsupervised learning algorithms using real datasets.
Is this Python certificate recognised?
Yes. The certificate is CPD QS Accredited and respected by employers across the UK and internationally.
Can I study on my mobile or tablet?
Absolutely. This course is 100% online and mobile-friendly.
How do I get my certificate?
You will receive your digital certificate after passing the final exam. Hard copies can be ordered.
How do I enrol?
Click ‘Enrol Now’ on our website and start immediately.
Course Curriculum
- 20 sections
- 40 lectures
- 00:00:00 total length
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Welcome & Course Overview 00:07:00 -
Set-up the Environment for the Course (lecture 1) 00:09:00
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Set-up the Environment for the Course (lecture 2) 00:25:00
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Two other options to setup environment 00:04:00
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Python data types Part 1 00:21:00
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Python Data Types Part 2 00:15:00
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Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 1) 00:16:00
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Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 2) 00:20:00
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Python Essentials Exercises Overview 00:02:00
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Python Essentials Exercises Solutions 00:22:00
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What is Numpy? A brief introduction and installation instructions. 00:03:00
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NumPy Essentials – NumPy arrays, built-in methods, array methods and attributes. 00:28:00
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NumPy Essentials – Indexing, slicing, broadcasting & boolean masking 00:26:00
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NumPy Essentials – Arithmetic Operations & Universal Functions 00:07:00
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NumPy Essentials Exercises Overview 00:02:00
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NumPy Essentials Exercises Solutions 00:25:00
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What is pandas? A brief introduction and installation instructions. 00:02:00
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Pandas Introduction 00:02:00
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Pandas Essentials – Pandas Data Structures – Series 00:20:00
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Pandas Essentials – Pandas Data Structures – DataFrame 00:30:00
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Pandas Essentials – Handling Missing Data 00:12:00
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Pandas Essentials – Data Wrangling – Combining, merging, joining 00:20:00
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Pandas Essentials – Groupby 00:10:00
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Pandas Essentials – Useful Methods and Operations 00:26:00
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Pandas Essentials – Project 1 (Overview) Customer Purchases Data 00:08:00
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Pandas Essentials – Project 1 (Solutions) Customer Purchases Data 00:31:00
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Pandas Essentials – Project 2 (Overview) Chicago Payroll Data 00:04:00
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Pandas Essentials – Project 2 (Solutions Part 1) Chicago Payroll Data 00:18:00
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Matplotlib Essentials (Part 1) – Basic Plotting & Object Oriented Approach 00:13:00
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Matplotlib Essentials (Part 2) – Basic Plotting & Object Oriented Approach 00:22:00
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Matplotlib Essentials (Part 3) – Basic Plotting & Object Oriented Approach 00:22:00
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Matplotlib Essentials – Exercises Overview 00:06:00
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Matplotlib Essentials – Exercises Solutions 00:21:00
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Seaborn – Introduction & Installation 00:04:00
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Seaborn – Distribution Plots 00:25:00
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Seaborn – Categorical Plots (Part 1) 00:21:00
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Seaborn – Categorical Plots (Part 2) 00:16:00
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Seborn-Axis Grids 00:25:00
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Seaborn – Matrix Plots 00:13:00
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Seaborn – Regression Plots 00:11:00
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Seaborn – Controlling Figure Aesthetics 00:10:00
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Seaborn – Exercises Overview 00:04:00
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Seaborn – Exercise Solutions 00:19:00
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Pandas Built-in Data Visualization 00:34:00
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Pandas Data Visualization Exercises Overview 00:03:00
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Panda Data Visualization Exercises Solutions 00:13:00
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Plotly & Cufflinks – Interactive & Geographical Plotting (Part 1) 00:19:00
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Plotly & Cufflinks – Interactive & Geographical Plotting (Part 2) 00:14:00
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Plotly & Cufflinks – Interactive & Geographical Plotting Exercises (Overview) 00:11:00
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Plotly & Cufflinks – Interactive & Geographical Plotting Exercises (Solutions) 00:37:00
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Project 1 – Oil vs Banks Stock Price during recession (Overview) 00:15:00
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Project 1 – Oil vs Banks Stock Price during recession (Solutions Part 1) 00:18:00
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Project 1 – Oil vs Banks Stock Price during recession (Solutions Part 2) 00:18:00
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Project 1 – Oil vs Banks Stock Price during recession (Solutions Part 3) 00:17:00
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Project 2 (Optional) – Emergency Calls from Montgomery County, PA (Overview) 00:03:00
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Introduction to ML – What, Why and Types….. 00:15:00
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Theory Lecture on Linear Regression Model, No Free Lunch, Bias Variance Tradeoff 00:15:00
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scikit-learn – Linear Regression Model – Hands-on (Part 1) 00:17:00
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scikit-learn – Linear Regression Model Hands-on (Part 2) 00:19:00
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Good to know! How to save and load your trained Machine Learning Model! 00:01:00
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scikit-learn – Linear Regression Model (Insurance Data Project Overview) 00:08:00
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scikit-learn – Linear Regression Model (Insurance Data Project Solutions) 00:30:00
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Theory: Logistic Regression, conf. mat., TP, TN, Accuracy, Specificity…etc. 00:10:00
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scikit-learn – Logistic Regression Model – Hands-on (Part 1) 00:17:00
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scikit-learn – Logistic Regression Model – Hands-on (Part 2) 00:20:00
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scikit-learn – Logistic Regression Model – Hands-on (Part 3) 00:11:00
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scikit-learn – Logistic Regression Model – Hands-on (Project Overview) 00:05:00
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scikit-learn – Logistic Regression Model – Hands-on (Project Solutions) 00:15:00
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Theory: K Nearest Neighbors, Curse of dimensionality …. 00:08:00
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scikit-learn – K Nearest Neighbors – Hands-on 00:25:00
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scikt-learn – K Nearest Neighbors (Project Overview) 00:04:00
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scikit-learn – K Nearest Neighbors (Project Solutions) 00:14:00
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Theory: D-Tree & Random Forests, splitting, Entropy, IG, Bootstrap, Bagging…. 00:18:00
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scikit-learn – Decision Tree and Random Forests – Hands-on (Part 1) 00:19:00
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scikit-learn – Decision Tree and Random Forests (Project Overview) 00:05:00
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scikit-learn – Decision Tree and Random Forests (Project Solutions) 00:15:00
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Support Vector Machines (SVMs) – (Theory Lecture) 00:07:00
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scikit-learn – Support Vector Machines – Hands-on (SVMs) 00:30:00
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scikit-learn – Support Vector Machines (Project 1 Overview) 00:07:00
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scikit-learn – Support Vector Machines (Project 1 Solutions) 00:20:00
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scikit-learn – Support Vector Machines (Optional Project 2 – Overview) 00:02:00
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Theory: K Means Clustering, Elbow method ….. 00:11:00
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scikit-learn – K Means Clustering – Hands-on 00:23:00
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scikit-learn – K Means Clustering (Project Overview) 00:07:00
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scikit-learn – K Means Clustering (Project Solutions) 00:22:00
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Theory: Principal Component Analysis (PCA) 00:09:00
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scikit-learn – Principal Component Analysis (PCA) – Hands-on 00:22:00
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scikit-learn – Principal Component Analysis (PCA) – (Project Overview) 00:02:00
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scikit-learn – Principal Component Analysis (PCA) – (Project Solutions) 00:17:00
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Theory: Recommender Systems their Types and Importance 00:06:00
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Python for Recommender Systems – Hands-on (Part 1) 00:18:00
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Python for Recommender Systems – – Hands-on (Part 2) 00:19:00
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Natural Language Processing (NLP) – (Theory Lecture) 00:13:00
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NLTK – NLP-Challenges, Data Sources, Data Processing ….. 00:13:00
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NLTK – Feature Engineering and Text Preprocessing in Natural Language Processing 00:19:00
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NLTK – NLP – Tokenization, Text Normalization, Vectorization, BoW…. 00:19:00
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NLTK – BoW, TF-IDF, Machine Learning, Training & Evaluation, Naive Bayes … 00:13:00
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NLTK – NLP – Pipeline feature to assemble several steps for cross-validation… 00:09:00
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Resources- Python for Data Analysis 00:00:00
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Claim Your Certificate 00:00:00
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ALL COURSES FOR - £99 This course includes:
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Duration:1 day
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Access:1 year access
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Level:
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CPD Points:10
