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Duration 21 hours
Course Outline
Introduction to Data Analysis and Big Data
- What Defines Big Data as "Big"?
- Velocity, Volume, Variety, Veracity (VVVV)
- Limitations of Traditional Data Processing
- Distributed Processing
- Statistical Analysis
- Categories of Machine Learning Analysis
- Data Visualization
Big Data Roles and Responsibilities
- Administrators
- Developers
- Data Analysts
Languages for Data Analysis
- Python
- The Case for Python in Data Analysis
- Data manipulation, processing, cleaning, and analysis
Methodologies for Data Analysis
- Statistical Analysis
- Time Series analysis
- Forecasting using Correlation and Regression models
- Inferential Statistics (estimation)
- Descriptive Statistics in Big Data sets (e.g., calculating mean)
- Machine Learning
- Supervised vs. unsupervised learning
- Classification and clustering
- Estimating the cost of specific methods
- Filtering
Big Data Infrastructure
- Data Storage
- Relational databases (SQL)
- MySQL
- Postgres
- Oracle
- Nuances of Database Types
- Hierarchical databases
- Object-oriented databases
- Document-oriented databases
- Graph-oriented databases
- Other types
- Relational databases (SQL)
The Future of Big Data
Summary and Next Steps
Requirements
- A general familiarity with mathematics
- A general understanding of programming
- A general grasp of databases
Target Audience
- Developers / Programmers
- IT Consultants
Testimonials (3)
Learning that the QGIS and a tool that can used by other different professionals such land survey
Bame Duncan Koko - Bentel Technologies (Pty) Ltd
Course - QGIS for Geographic Information System
How to use open satellites data for real applications
Tshering Dorji - Druk Holding and Investments
Course - Advanced Geographic Information Systems (GIS)
Hands-on examples allowed us to get an actual feel for how the program works. Good explanations and integration of theoretical concepts and how they relate to practical applications.
