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Machine Learning Python Course
Unlock the power of data with our Machine Learning Python Course, tailored for Business Intelligence professionals. Delve into data exploration and analysis, master preprocessing techniques, and harness the potential of machine learning algorithms such as linear regression and decision trees. Learn feature engineering, model training, and evaluation, and optimise your models with hyperparameter tuning. Conclude with model deployment and documentation, ensuring your skills are ready for real-world application. Join now to elevate your BI expertise!
- Master model deployment: Save, load, and document models for seamless integration.
- Enhance feature engineering: Create interaction features and extract date insights.
- Optimise model training: Implement train-test splits and evaluate with metrics.
- Explore data effectively: Analyse data structures and load datasets using Pandas.
- Refine preprocessing skills: Normalise, scale, and encode categorical data efficiently.

4 to 360 hours flexible workload
certificate recognised by MEC
What will I learn?
Unlock the power of data with our Machine Learning Python Course, tailored for Business Intelligence professionals. Delve into data exploration and analysis, master preprocessing techniques, and harness the potential of machine learning algorithms such as linear regression and decision trees. Learn feature engineering, model training, and evaluation, and optimise your models with hyperparameter tuning. Conclude with model deployment and documentation, ensuring your skills are ready for real-world application. Join now to elevate your BI expertise!
Elevify advantages
Develop skills
- Master model deployment: Save, load, and document models for seamless integration.
- Enhance feature engineering: Create interaction features and extract date insights.
- Optimise model training: Implement train-test splits and evaluate with metrics.
- Explore data effectively: Analyse data structures and load datasets using Pandas.
- Refine preprocessing skills: Normalise, scale, and encode categorical data efficiently.
Suggested summary
Before starting, you can change the chapters and the workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
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