Swift Lessons: Data Science Machine Learning
Discover a wide range of topics and in-depth lessons designed to help you build a solid understanding of Data Science Machine Learning.
Core Data Science
- Introduction to Data Science
- Statistics Basics
- Probability Fundamentals
- Data Cleaning and Preprocessing
- Data Exploration and Analysis
- Data Visualization Basics
- Linear Algebra for Data Science
- Calculus Basics for Data Science
- Data Types and Structures
- Feature Engineering
- Sampling Techniques
- Statistical Inference
- Hypothesis Testing
- Regression Analysis
- Classification Basics
- Clustering Techniques
- Dimensionality Reduction
- Time Series Analysis
- Big Data Concepts
- Data Science Ethics
Machine Learning Fundamentals
Advanced Machine Learning
Deep Learning & Neural Networks
Data Visualization & Analytics
Natural Language Processing
Big Data & Scalable Systems
- Introduction to Big Data
- Hadoop Fundamentals
- Introduction to Apache Spark
- Real-Time Stream Processing
- Data Partitioning and Sharding
- Big Data Storage Solutions
- Parallel Computing Concepts
- Big Data in the Cloud
- Big Data Case Studies
- Advanced Apache Spark Techniques
- Data Science in the Cloud
- Apache Spark for Data Science
- Big Data Analytics
- Parallel Computing for Data Science
- Cloud-Based Data Science Solutions
- Real-Time Data Processing
- Edge Computing for Data Science
- Distributed Machine Learning
- Big Data Techniques for ML
- Scalable Data Science Architectures
- Cloud-Based Data Science
Data Science Tools & Techniques
- Introduction to Jupyter Notebooks
- Pandas for Data Analysis
- NumPy Fundamentals
- Introduction to scikit-learn
- Data Preprocessing with Python
- Data Visualization with Python
- Data Wrangling Techniques
- Building ML Pipelines
- Collaborative Data Science with Notebooks
- Deploying Machine Learning Models
- Introduction to MLOps
- Monitoring Machine Learning Models
- Automated Machine Learning (AutoML)
- Building MLOps Pipelines
- Automated Data Preprocessing
- Model Serving and Deployment
- Collaboration in Data Science
- Automated Feature Engineering
- Advanced Data Cleaning Techniques
- Advanced Statistical Methods
- Scripting for Data Science