Python for Machine Learning Engineers
Building Machine Learning Models with Python for Real-World Applications
(includes training and materials)
Training Delivery Mode:
- Physical Classroom
- Live Virtual Training
Course Overview
The Python for Machine Learning Engineers course is a practical, hands-on programme designed to equip aspiring and early-career machine learning professionals with the Python skills required to build, evaluate, and optimise machine learning models.
This course bridges the gap between Python programming and applied machine learning, focusing on real-world data handling, model development, and performance optimisation. Participants will work with industry-standard libraries and tools to develop supervised and unsupervised learning models while gaining a strong understanding of the end-to-end machine learning workflow.
The programme emphasises experiential learning, ensuring participants gain practical exposure through coding labs, real datasets, and applied exercises aligned with professional and industry expectations.
This course is practice-driven, industry-aligned, and certification-focused, ensuring participants gain both hands-on machine learning skills and recognised Python credentials.
Course Module
- Introduction to Python for Machine Learning
- Data Handling with Python
- Data Visualization
- Introduction to Machine Learning
- Advanced Supervised Learning Models
- Unsupervised Learning
- Model Evaluation and Optimization
What You Will Learn
By the end of this course, participants will be able to:
- Use Python effectively for machine learning tasks
- Handle, clean, and prepare data for ML workflows
- Visualise data to support feature understanding and selection
- Build supervised and unsupervised machine learning models
- Evaluate model performance using appropriate metrics
- Optimise models through tuning and validation techniques
- Apply best practices in machine learning model development
- Prepare for entry-level Python certification
Who This Course Is For
This course is ideal for individuals looking to build or strengthen machine learning engineering skills using Python, including:
- Aspiring Machine Learning Engineers
- Data Scientists and Data Analysts transitioning into ML roles
- Software Engineers interested in machine learning
- AI and Data Science Students
- Professionals seeking a strong ML foundation using Python
- Technical professionals preparing for advanced AI/ML programmes
Basic Python knowledge is recommended, though motivated beginners can also benefit.
Career Benefits
Participants who complete this course will be able to:
- Build and evaluate machine learning models using Python
- Support AI and data science initiatives within organisations
- Transition into machine learning engineering or data science roles
- Strengthen technical portfolios with applied ML projects
- Progress confidently into advanced AI and ML training programmes
Tools, Frameworks, Or Standards Covered
- Python 3.x
- NumPy
- Pandas
- Matplotlib
- Seaborn
- Plotly
- Scikit-Learn
- Jupyter Notebooks
Certification
Participants who successfully complete the course will receive:
Certificate of Completion in Python for Machine Learning Engineers
Issued by SCILS Management Centre
Participants will also be prepared for:
PCEP-30-02: PCEP – Certified Entry-Level Python Programmer