Data Preprocessing and Feature Engineering for Machine Learning
Overview The Data Preprocessing and Feature Engineering for Machine Learning Course is a CPD-accredited, fully online programme designed for learners who want to develop practical skills in preparing data and improving machine learning model performance. This course introduces essential techniques used to transform raw data into meaningful information for artificial …
Overview
Overview
The Data Preprocessing and Feature Engineering for Machine Learning Course is a CPD-accredited, fully online programme designed for learners who want to develop practical skills in preparing data and improving machine learning model performance. This course introduces essential techniques used to transform raw data into meaningful information for artificial intelligence systems.
Throughout the course, you will explore data cleaning, data transformation, handling missing values, feature selection, feature extraction, data encoding, scaling methods, and machine learning preparation workflows. You will learn how high-quality data and effective feature engineering techniques influence the accuracy and reliability of machine learning models.
This course is ideal for aspiring data scientists, machine learning learners, Python developers, analysts, and technology professionals looking to strengthen their AI skills. With flexible online learning, CPD accreditation, and practical data techniques, it helps learners build confidence in preparing datasets for real-world machine learning applications.
Key highlights:
- Understand machine learning data preparation
- Learn data cleaning and transformation techniques
- Explore feature engineering methods
- Improve machine learning model performance
- Flexible self-paced online learning with lifetime access
- CPD-accredited for data science development
- Apply preprocessing techniques to ML projects
Accreditation & Recognition
The Data Preprocessing and Feature Engineering for Machine Learning Course is CPD-accredited, supporting learners who want to develop practical data science and artificial intelligence skills. The course provides structured learning focused on preparing datasets and improving machine learning workflows.
- 100% online and flexible learning experience
- Designed for data science learners
- Includes CPD-accredited certificate upon completion
- Supports progression into machine learning careers
Assessment & Certification
Your understanding of data preprocessing and feature engineering is assessed through an online multiple-choice assessment designed to evaluate your knowledge of data preparation methods, feature selection, transformation techniques, and machine learning workflows. You will receive instant results after completion and can retake the assessment if required. Upon successful completion, you can order your CPD Accredited certificate as evidence of your data science learning and professional development achievement.
Who Is This Course For?
- Aspiring data scientists learning ML techniques
- Machine learning learners improving skills
- Python developers working with data
- Analysts preparing datasets for AI
- Professionals developing data science knowledge
Career Opportunities & Progression
- Data Scientist (£40,000 – £70,000)
- Machine Learning Engineer (£45,000 – £80,000)
- Data Analyst (£30,000 – £55,000)
- AI Engineer (£45,000 – £85,000)
- Data Engineer (£40,000 – £70,000)
Key Skills You’ll Gain
- Cleaning and preparing machine learning data
- Handling missing and inconsistent information
- Applying feature engineering techniques
- Selecting useful machine learning features
- Transforming data for AI models
- Improving model accuracy and performance
- Developing professional data workflows
Why Study with Royal Open College
Royal Open College is a trusted CPD-accredited training provider committed to helping learners develop practical and career-focused skills. Our online courses combine flexible study options with industry-relevant knowledge, allowing learners to build confidence and progress professionally.
- Expert-designed courses focused on practical skills
- 100% online learning with flexible access
- Affordable training with transparent pricing
- Trusted by learners developing future-ready skills
Enrol today in the Data Preprocessing and Feature Engineering for Machine Learning Course to strengthen your data science knowledge, improve your machine learning workflow skills, and prepare for modern AI opportunities.
Curriculum
Curriculum
- 4 Sections
- 21 Lessons
- Lifetime Access
- Data Preprocessing3 Items
- Data Preprocessing in Python16 Items
- 2.1Preprocessing Data in Python: Preparing Your Dataset for ML Models
- 2.2Applying Data Preprocessing Techniques: From Raw Data to ML-Ready Datasets
- 2.3Importing Datasets Using Pandas read_csv(): Machine Learning Basics
- 2.4Using Pandas iloc for Feature Selection in ML Data Preprocessing
- 2.5Building X and Y Vectors for ML Model Training: Preprocessing Data
- 2.7Imputing Missing Data in Python with SimpleImputer and Numerical Columns
- 2.8Transforming Categorical Features for ML Algorithms with One-Hot Encoding
- 2.9Handling Categorical Data: One-Hot Encoding with ColumnTransformer
- 2.10Preprocessing Categorical Data with One-Hot and Label Encoding Techniques
- 2.11Preparing Data for Machine Learning: Training vs Test Sets
- 2.12Creating Training and Test Sets in Python for ML Models
- 2.13Splitting Data into Training and Test Sets: Best Practices in Python
- 2.14Understanding Why Feature Scaling in ML Is Crucial for Data Preprocessing
- 2.15Scaling Numeric Features in Python for ML Preprocessing
- 2.16Implementing Feature Scaling: Fit and Transform Methods Explained
- 2.17Applying the Same Scaler to Training and Test Sets in Python
- Practice Lab1 Item
- Claim Your Certificate1 Item






