Machine Learning Fundamentals
Master the fundamentals of machine learning with this comprehensive course. Learn essential algorithms, data preprocessing techniques, and model evaluation methods. Perfect for beginners who want to understand the core concepts of ML and build a solid foundation for advanced studies.
Dr. Emily Rodriguez
Senior Data Scientist & ML Researcher
30-Day Money-Back Guarantee
This course includes:
- 32 hours of content
- Downloadable resources
- Certificate of completion
- Full lifetime access
- Access on mobile and TV
What you'll learn
Course content
Introduction to Machine Learning
5 lectures • 2 hours
- What is Machine Learning
- Types of ML
- Applications
- ML Workflow
- Tools and Libraries
Data Preprocessing
8 lectures • 4 hours
- Data Cleaning
- Feature Engineering
- Data Scaling
- Handling Missing Values
- Outlier Detection
- Data Transformation
- Feature Selection
- Dimensionality Reduction
Supervised Learning
12 lectures • 8 hours
- Linear Regression
- Logistic Regression
- Decision Trees
- Random Forest
- Support Vector Machines
- Naive Bayes
- K-Nearest Neighbors
- Model Evaluation Metrics
- Cross-Validation
- Hyperparameter Tuning
- Ensemble Methods
- Model Selection
Unsupervised Learning
6 lectures • 4 hours
- Clustering Algorithms
- K-Means
- Hierarchical Clustering
- DBSCAN
- Principal Component Analysis
- Association Rules
Model Evaluation & Validation
7 lectures • 4 hours
- Bias and Variance
- Overfitting and Underfitting
- Cross-Validation Techniques
- Performance Metrics
- ROC Curves
- Confusion Matrix
- Model Interpretability
Real-World Projects
10 lectures • 10 hours
- Customer Segmentation
- Predictive Analytics
- Recommendation System
- Image Classification
- Natural Language Processing
- Time Series Analysis
- Anomaly Detection
- Model Deployment
- Production Considerations
- Best Practices
Requirements
- Basic knowledge of Python programming
- Understanding of high school mathematics (algebra, calculus)
- Familiarity with basic statistics concepts
- No prior machine learning experience required
Instructor
Dr. Emily Rodriguez
Senior Data Scientist & ML Researcher
Dr. Emily Rodriguez is a leading expert in machine learning and artificial intelligence with over 10 years of experience in both academia and industry. She holds a PhD in Computer Science from Stanford University and has published numerous papers on ML algorithms and applications.