Python (Machine Learning & Programming) - QLS Endorsed

Imperial Academy

The demand for Python developers and machine learning specialists is growing exponentially, with the global artificial intelligence and machine learning market projected to expand by over 35% annually. Python continues to be the most widely used programming language, powering applications across data science, finance, healthcare, and technology. Professionals skilled in these areas can expect salaries ranging from £35,000 to £70,000 per year depending on experience and role.

This course is ideal for aspiring programmers, data enthusiasts, tech entrepreneurs, and professionals seeking to enhance computational and analytical skills. Career paths include Python developer, machine learning technician, data analyst, AI support specialist, and automation developer. The training equips learners with in-demand programming knowledge and machine learning principles to solve real-world challenges effectively.

Learners will develop core skills in Python programming, algorithm development, data analysis, and predictive modelling. This course provides a strong foundation in coding logic, computational thinking, and intelligent system applications, helping participants gain confidence and professional competence.

Enrol today to acquire high-demand skills that prepare you for a successful career in Python programming and machine learning.

This bundle comprises the following courses:

QLS Endorsed Courses:

• Course 01: Certificate in Machine Learning with Python at QLS Level 3
• Course 02: Diploma in Python Programming at QLS Level 5

CPD QS Accredited Courses:

• Course 03: Azure Machine Learning
• Course 04: Complete Python Machine Learning & Data Science Fundamentals
• Course 05: Machine Learning Model Using AWS SageMaker Canvas
• Course 06: Statistics & Probability for Data Science & Machine Learning
• Course 07: 2021 Data Science & Machine Learning with R from A-Z

After completing this course, you will be able to:

• Write structured Python scripts that perform logical operations, manage data, and execute computational tasks efficiently in diverse technical environments.
• Apply programming concepts to design algorithms that solve complex problems, optimise workflows, and support data-driven applications consistently.
• Analyse datasets using Python techniques to extract insights, identify trends, and generate actionable information effectively for decision-making.
• Develop basic machine learning models that classify data, predict outcomes, and identify patterns reliably using standard methodologies.
• Evaluate algorithm performance by testing, tuning, and adjusting models to improve accuracy, reliability, and stability in practical applications.
• Implement Python-based solutions to automate tasks, process information, and enhance operational efficiency across various digital contexts effectively.
• Use analytical thinking to break problems into manageable steps, design logical solutions, and develop computational strategies successfully.
• Interpret machine learning workflows to understand data preparation, training, and evaluation processes for reliable model implementation efficiently.
• Apply coding best practices to improve readability, maintainability, and long-term efficiency of scripts and computational projects effectively.
• Integrate programming and machine learning methods to deliver consistent, reliable outputs supporting data-driven and intelligent system applications confidently.