Big Data (BDI302c)
Vietnamese title: Dữ liệu lớn
Credits: 3

Description:
This course covers 5 of 6 courses of Big Data Specialization (UC San Diego) on the Coursera platform. This course will prepare students to ask the right questions about data, communicate effectively with data scientists, and do basic exploration of large, complex datasets. By following along with provided code, students will experience how one can perform predictive modeling and leverage graph analytics to model problems. They will be guided through the basics of using Hadoop with MapReduce, Spark, Pig and Hive.

Learning outcomes:
Explain basis concepts in big data, architectural components and programming models used for scalable big data analysis.
Collect, store and organize data using big data solutions
Design a big data information system for small company
Execute simple big data integration and processing on Hadoop and Spark platforms
Use tools and algorithms to create machine learning models that learn from data, and to scale those models up to big data problems
Model a problem into a graph database and perform analytical tasks over the graph in a scalable manner.

Student tasks:
1. Complete the online courses and get all course certifications to be allowed to take Final Exam
2. Final Exam included Final Theory Exam (TE): 100%
3. Students who complete all MOOCs before the course deadline will receive 1 bonus point; otherwise, no bonus point will be awarded.
4. Completion Criteria: Final TE Score >=4 & (Final TE Score + bonus) >= 5

Tools:
Hadoop, Cloudera VM, KNIME, Spark

Materials:
description: https://www.coursera.org/specializations/big-data
publisher: Coursera
note: Big Data Specialization
description: https://www.coursera.org/learn/big-data-introduction?specialization=big-data
publisher: Coursera
note: MOOC 1: Introduction to Big Data
description: https://www.coursera.org/learn/big-data-management?specialization=big-data
publisher: Coursera
note: MOOC 2: Big Data Modeling and Management Systems
description: https://www.coursera.org/learn/big-data-integration-processing?specialization=big-data
publisher: Coursera
note: MOOC 3: Big Data Integration and Processing
description: https://www.coursera.org/learn/big-data-machine-learning?specialization=big-data
publisher: Coursera
note: MOOC 4: Machine Learning With Big Data
description: https://www.coursera.org/learn/big-data-graph-analytics?specialization=big-data
publisher: Coursera
note: MOOC 5: Graph Analytics for Big Data
description: https://learner.coursera.help/hc/en-us/articles/208280036-Coursera-Code-of-Conduct
publisher: Coursera

Assessments:
category: Final exam
type: Final exam
weight: 100.0
duration: 90'
question_type: All Los
no_question: Multiple choicesMarked by Computer
knowledge_and_skill: 75
grading_guide: All studied courses. Each module of course contributes 3-5 questions.
note: by exam board,
using computer

Schedule:
session: Introduction to Big Data
- Welcome
- Big Data: Why and Where
-Characteristics of Big Data and Dimensions of Scalability
Offline 1: Introduction to the online course BDI302c
learning_outcomes: TU
materials: BDI302c_1
session: - Data Science: Getting Value out of Big Data
'- Foundations for Big Data Systems and Programming
- Systems: Getting Started with Hadoop
learning_outcomes: TU
materials: BDI302c_2
session: Big Data Modeling and Management Systems
- Introduction to Big Data Modeling and Management
- Big Data Modeling
- Big Data Modeling (Part 2)
learning_outcomes: TU
materials: BDI302c_3
session: - Working With Data Models
- Big Data Management: The "M" in DBMS
- Designing a Big Data Management System for an Online Game
learning_outcomes: TU
materials: BDI302c_4
session: Big Data Integration and Processing
- Welcome to Big Data Integration and Processing
- Retrieving Big Data (Part 1)
- Retrieving Big Data (Part 2)
learning_outcomes: TU
materials: BDI302c_5
session: '- Big Data Integration
- Processing Big Data
learning_outcomes: TU
materials: BDI302c_6
session: - Big Data Analytics using Spark
- Learn By Doing: Putting MongoDB and Spark to Work
learning_outcomes: TU
materials: BDI302c_7
session: Machine Learning With Big Data
- Welcome
- Introduction to Machine Learning with Big Data
- Data Exploration
- Data Preparation
learning_outcomes: TU
materials: BDI302c_8
session: - Classification
- Evaluation of Machine Learning Models
learning_outcomes: TU
materials: BDI302c_9
session: - Regression, Cluster Analysis, and Association Analysis
learning_outcomes: TU
materials: BDI302c_10
session: Graph Analytics for Big Data
- Welcome to Graph Analytics
- Introduction to Graphs
- Graph Analytics
learning_outcomes: TU
materials: BDI302c_11
session: - Graph Analytics Techniques
- Computing Platforms for Graph Analytics
Offline 2: Review Big Data Specialization (Spec)
learning_outcomes: TU
materials: BDI302c_12