Certification
Certification in Applying Regression, Classification, and Model Evaluation Techniques
Get certified in Machine Learning Fundamentals,demonstrate the ability to prepare data, build and assess regression and classification models, and deliver actionable predictions using Python for practical business and technology solutions.
The exam
Take the certification exam
Multiple-choice questions about the course. Pass with 70% or more and your certificate is issued at once, with a public page and an "Add to LinkedIn" button.
What the exam covers
2 questions from each of the 12 chapters of the course
20 multiple-choice questions, drawn fresh for every attempt. Pass with 70% or more.
- 01Introduction to machine learning2:49
- 02Beyond data analysis9:15
- 03Why ML: applications16:43
- 04Data science vs ML vs AI7:16
- 05ML pipeline and supervised learning17:54
- 06Unsupervised and other paradigms6:35
- 07Classification vs regression13:58
- 08Introduction to linear regression27:06
- 09Simple linear regression and evaluation122:43
- 10Multiple linear regression112:48
- 11Bias, variance and regularisation71:08
- 12Hyperparameter tuning and model selection52:59
The "Machine Learning for Beginners: Regression, Classification, and Model Evaluation (Video Course)" certification introduces you to the fundamental concepts and tools powering modern technology. Gain practical skills in data preparation, model training, and evaluation, empowering you with increased productivity, a future-proof career, and improved decision-making abilities. Enroll today to build a solid foundation in machine learning that equips you for real-world challenges.
This certification covers the following topics:
- Understanding Supervised Learning
- Data Splitting: Training, Validation, and Testing Sets
- Types of Machine Learning Tasks: Classification
- Measuring Model Performance: Error Metrics
- Linear Regression: Predictive Modeling
- Goodness of Fit: R-squared and Adjusted R-squared
- Preparing Data: Handling Categorical Variables and Feature Scaling
- Correlation and Multicollinearity
- Overfitting and Underfitting: Model Optimization
- Regularization: Ridge and Lasso Regression
- Hyperparameter Tuning
- Practical Implementation with Python Libraries
Jobs this certification suits
Our AI checked this certification against 500 jobs; these get the most out of it. Each job links to its learning path.