[major=AI | course_id=BDI302c | syllabus_id=12550 | semester=5 | combo=AI17_COM1 | title=Big Data]
Course ID: BDI302c
Title EN: Big Data
Title VI: Dữ liệu lớn
Credits: 3.0
Prerequisites: 
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.
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
Course type: coursera_only
Decision: 359/QĐ-ĐHFPT dated 04/09/2025
Approved date: 2025-04-09
CLO1: Explain basis concepts in big data, architectural components and programming models used for scalable big data analysis.
[1] category=Final exam; type=Final exam; weight=100.0; duration=90'; question_type=All Los; grading_guide=All studied courses. Each module of course contributes 3-5 questions.; completion_criteria=; clos=4
[1] desc=https://www.coursera.org/specializations/big-data; author=; publisher=Coursera; edition=; isbn=; main=; online=True; note=Big Data Specialization
[2] desc=https://www.coursera.org/learn/big-data-introduction?specialization=big-data; author=; publisher=Coursera; edition=; isbn=; main=True; online=True; note=MOOC 1: Introduction to Big Data
[3] desc=https://www.coursera.org/learn/big-data-management?specialization=big-data; author=; publisher=Coursera; edition=; isbn=; main=True; online=True; note=MOOC 2: Big Data Modeling and Management Systems
[4] desc=https://www.coursera.org/learn/big-data-integration-processing?specialization=big-data; author=; publisher=Coursera; edition=; isbn=; main=True; online=True; note=MOOC 3: Big Data Integration and Processing
[5] desc=https://www.coursera.org/learn/big-data-machine-learning?specialization=big-data; author=; publisher=Coursera; edition=; isbn=; main=True; online=True; note=MOOC 4: Machine Learning With Big Data
[6] desc=https://www.coursera.org/learn/big-data-graph-analytics?specialization=big-data; author=; publisher=Coursera; edition=; isbn=; main=True; online=True; note=MOOC 5: Graph Analytics for Big Data
[7] desc=https://learner.coursera.help/hc/en-us/articles/208280036-Coursera-Code-of-Conduct; author=; publisher=Coursera; edition=; isbn=; main=; online=True; note=
Session 1: 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
Topic: Offline,Online; Teaching type: LO1; LO: TU
ITU: 
Materials: BDI302c_1
Download: - Watch all videos, read all materials in the MOOC
- Finish quizzes, self-assessment, assignments and take part in discussion boards (if needed)
All students should participate in offline slot (if any question)

Session 2: - Data Science: Getting Value out of Big Data
'- Foundations for Big Data Systems and Programming
- Systems: Getting Started with Hadoop
Topic: Online; Teaching type: LO1; LO: TU
ITU: 
Materials: BDI302c_2
Download: - Watch all videos, read all materials in the MOOC
- Finish quizzes, self-assessment, assignments and take part in discussion boards (if needed)

Session 3: Big Data Modeling and Management Systems
- Introduction to Big Data Modeling and Management
- Big Data Modeling
- Big Data Modeling (Part 2)
Topic: Online; Teaching type: LO2; LO: TU
ITU: 
Materials: BDI302c_3
Download: - Watch all videos, read all materials in the MOOC
- Finish quizzes, self-assessment, assignments and take part in discussion boards (if needed)

Session 4: - Working With Data Models
- Big Data Management: The "M" in DBMS
- Designing a Big Data Management System for an Online Game
Topic: Online; Teaching type: LO2; LO: TU
ITU: 
Materials: BDI302c_4
Download: - Watch all videos, read all materials in the MOOC
- Finish quizzes, self-assessment, assignments and take part in discussion boards (if needed)
CLO2: Collect, store and organize data using big data solutions
Session 1: Big Data Integration and Processing
- Welcome to Big Data Integration and Processing
- Retrieving Big Data (Part 1)
- Retrieving Big Data (Part 2)
Topic: Online; Teaching type: LO3; LO: TU
ITU: 
Materials: BDI302c_5
Download: - Watch all videos, read all materials in the MOOC
- Finish quizzes, self-assessment, assignments and take part in discussion boards (if needed)

Session 2: '- Big Data Integration
- Processing Big Data
Topic: Online; Teaching type: LO3, LO4; LO: TU
ITU: 
Materials: BDI302c_6
Download: - Watch all videos, read all materials in the MOOC
- Finish quizzes, self-assessment, assignments and take part in discussion boards (if needed)

Session 3: - Big Data Analytics using Spark
- Learn By Doing: Putting MongoDB and Spark to Work
Topic: Online; Teaching type: LO3, LO4; LO: TU
ITU: 
Materials: BDI302c_7
Download: - Watch all videos, read all materials in the MOOC
- Finish quizzes, self-assessment, assignments and take part in discussion boards (if needed)

Session 4: Machine Learning With Big Data
- Welcome
- Introduction to Machine Learning with Big Data
- Data Exploration
- Data Preparation
Topic: Online; Teaching type: LO5; LO: TU
ITU: 
Materials: BDI302c_8
Download: - Watch all videos, read all materials in the MOOC
- Finish quizzes, self-assessment, assignments and take part in discussion boards (if needed)
CLO3: Design a big data information system for small company
Session 1: - Classification
- Evaluation of Machine Learning Models
Topic: Online; Teaching type: LO5; LO: TU
ITU: 
Materials: BDI302c_9
Download: - Watch all videos, read all materials in the MOOC
- Finish quizzes, self-assessment, assignments and take part in discussion boards (if needed)

Session 2: - Regression, Cluster Analysis, and Association Analysis
Topic: Online; Teaching type: LO5; LO: TU
ITU: 
Materials: BDI302c_10
Download: - Watch all videos, read all materials in the MOOC
- Finish quizzes, self-assessment, assignments and take part in discussion boards (if needed)

Session 3: Graph Analytics for Big Data
- Welcome to Graph Analytics
- Introduction to Graphs
- Graph Analytics
Topic: Online; Teaching type: LO6; LO: TU
ITU: 
Materials: BDI302c_11
Download: - Watch all videos, read all materials in the MOOC
- Finish quizzes, self-assessment, assignments and take part in discussion boards (if needed)

Session 4: - Graph Analytics Techniques
- Computing Platforms for Graph Analytics
Offline 2: Review Big Data Specialization (Spec)
Topic: Offline,Online; Teaching type: LO6; LO: TU
ITU: 
Materials: BDI302c_12
Download: https://flm.fpt.edu.vn/gui/role/student/- Watch all videos, read all materials in the MOOC- Finish quizzes, self-assessment, assignments and take part in discussion boards (if needed)Deadline of Coursera completion: End of Friday of the week.All students should participate in review slot (if any question)
CLO4: Execute simple big data integration and processing on Hadoop and Spark platforms
CLO5: Use tools and algorithms to create machine learning models that learn from data, and to scale those models up to big data problems
CLO6: Model a problem into a graph database and perform analytical tasks over the graph in a scalable manner.