Certification
Certification: Applied Machine Learning with Python and Scikit-Learn
Show the world you have AI skills—gain hands-on experience building machine learning models with Python and Scikit-Learn. Strengthen your CV and demonstrate your readiness for real-world AI challenges with this industry-recognized certification.
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.
- 01Introduction3:32
- 02Problem statement and data3:55
- 03EDA and visualisation42:11
- 04Linear regression with one feature47:02
- 05Multiple regression and categorical features47:18
- 06Logistic regression180:10
- 07Decision trees and random forests100:13
- 08Regularisation and tuning21:08
- 09Approaching ML projects161:02
- 10Gradient boosting with XGBoost137:00
- 11Clustering90:18
- 12End-to-end ML project246:45
The Certification: Applied Machine Learning with Python and Scikit-Learn provides a practical pathway to mastering essential machine learning techniques using industry-standard tools. Learners will gain skills such as increased productivity, improved decision-making, and enhanced adaptability to the evolving field of data science. Enroll today to unlock new career opportunities and stay ahead in the world of applied machine learning.
This certification covers the following topics:
- Linear Regression and Model Building
- Exploratory Data Analysis and Feature Selection
- Decision Trees
- Random Forests
- Gradient Boosting Machines (GBMs) with XGBoost
- Clustering Techniques
- Dimensionality Reduction with Principal Component Analysis (PCA)
- Practical Model Deployment with Flask and GitHub
- Feature Engineering in Machine Learning
- K-fold Cross-Validation and Model Evaluation Metrics
- Hyperparameter Tuning
- Handling Missing Data and Imbalanced Datasets
- Preventing Overfitting
- Ensemble Learning
- Model Interpretability and Ethical Considerations
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.