Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
課程簡介
Introduction to Data Analysis and Big Data
- What Makes Big Data "Big"?
- Velocity, Volume, Variety, Veracity (VVVV)
- Limits to Traditional Data Processing
- Distributed Processing
- Statistical Analysis
- Types of Machine Learning Analysis
- Data Visualization
Big Data Roles and Responsibilities
- Administrators
- Developers
- Data Analysts
Languages Used for Data Analysis
- R Language
- Why R for Data Analysis?
- Data manipulation, calculation and graphical display
- Python
- Why Python for Data Analysis?
- Manipulating, processing, cleaning, and crunching data
Approaches to Data Analysis
- Statistical Analysis
- Time Series analysis
- Forecasting with Correlation and Regression models
- Inferential Statistics (estimating)
- Descriptive Statistics in Big Data sets (e.g. calculating mean)
- Machine Learning
- Supervised vs unsupervised learning
- Classification and clustering
- Estimating cost of specific methods
- Filtering
- Natural Language Processing
- Processing text
- Understaing meaning of the text
- Automatic text generation
- Sentiment analysis / topic analysis
- Computer Vision
- Acquiring, processing, analyzing, and understanding images
- Reconstructing, interpreting and understanding 3D scenes
- Using image data to make decisions
Big Data Infrastructure
- Data Storage
- Relational databases (SQL)
- MySQL
- Postgres
- Oracle
- Non-relational databases (NoSQL)
- Cassandra
- MongoDB
- Neo4js
- Understanding the nuances
- Hierarchical databases
- Object-oriented databases
- Document-oriented databases
- Graph-oriented databases
- Other
- Relational databases (SQL)
- Distributed Processing
- Hadoop
- HDFS as a distributed filesystem
- MapReduce for distributed processing
- Spark
- All-in-one in-memory cluster computing framework for large-scale data processing
- Structured streaming
- Spark SQL
- Machine Learning libraries: MLlib
- Graph processing with GraphX
- Hadoop
- Scalability
- Public cloud
- AWS, Google, Aliyun, etc.
- Private cloud
- OpenStack, Cloud Foundry, etc.
- Auto-scalability
- Public cloud
Choosing the Right Solution for the Problem
The Future of Big Data
Summary and Conclusion
最低要求
- A general understanding of math.
- A general understanding of programming.
- A general understanding of databases.
Audience
- Developers / programmers
- IT consultants
35 時間:
客戶評論 (5)
大數據如何工作,數據程式,更深入地了解我們當前世界如何使用數據運作
Ozayr Hussain - Vodacom
Course - A Practical Introduction to Data Analysis and Big Data
機器翻譯
培訓的實踐方面。
Patrick - Vodacom PTy Ltd
Course - A Practical Introduction to Data Analysis and Big Data
機器翻譯
Interactive topics and the style used by the lecture to simplified the topics for the students
Miran Saeed - Sulaymaniyah Asayish Agency
Course - A Practical Introduction to Data Analysis and Big Data
the trainer and his ability to lecture
ibrahim hamakarim - Sulaymaniyah Asayish Agency
Course - A Practical Introduction to Data Analysis and Big Data
Practical exercises