Machine Learning A-Z™: Hands-On Python & R In Data Science
Published:
This certification represents completion of one of the most comprehensive machine learning courses available, covering both Python and R programming languages. The course provides hands-on experience with a wide range of machine learning algorithms and techniques.
Course Specifications
- Provider: SuperDataScience
- Instructors: Hadelin de Ponteves, Kirill Eremenko
- Platform: Udemy Inc
- Scope: A-Z comprehensive machine learning curriculum
- Languages: Python and R
Curriculum Coverage
Machine Learning Fundamentals
- Regression algorithms (Linear, Polynomial, SVR, Decision Trees, Random Forest)
- Classification algorithms (Logistic Regression, K-NN, SVM, Kernel SVM, Naive Bayes, Decision Trees, Random Forest)
- Clustering techniques (K-Means, Hierarchical Clustering)
- Association Rule Learning (Apriori, Eclat)
Advanced Topics
- Reinforcement Learning (Upper Confidence Bound, Thompson Sampling)
- Natural Language Processing
- Deep Learning (Artificial Neural Networks, Convolutional Neural Networks)
- Dimensionality Reduction (PCA, LDA, Kernel PCA)
Model Selection and Evaluation
- Model selection and boosting
- Cross-validation and performance metrics
Practical Skills
- Data preprocessing and feature engineering
- Model building and evaluation
- Hyperparameter tuning
- Real-world project implementation
Programming Languages
Both Python and R implementations covered:
- Python: Using scikit-learn, TensorFlow, Keras
- R: Using caret, ggplot2, and other R packages
Verification
This certification can be verified by viewing the certificate PDF.