[major=AI | course_id=DAP391m | syllabus_id=13944 | semester=4 | combo=core | title=AI-DS Project]
Course ID: DAP391m
Title EN: AI-DS Project
Title VI: Dự án TTNT-KHDL
Credits: 3.0
Prerequisites: PFP191, ADY201m
Description: This course will take student from the basics of data analysis with Python to building and evaluating data models. The students will learn to work with some Data Visualization tools and techniques and create interactive dashboards that allow even those without any Data Science experience to better understand data, and make more effective and informed decisions. A student will be able to write an application that leverages multiple Watson AI services. This course allows students to practice data scientists' work in real life when working with datasets.
Student tasks: - Students must attend at least 80% of contact slots in order to be accepted to the final examination.
- Student is responsible to do all exercises, assignments and labs given by instructor in class or at home and submit on time
- Use laptop in class only for learning purpose
- Promptly access to https://flm.fpt.edu.vn/ for up-to-date course information
Tools: Jupyter Notebooks
- JupyterLab
- RStudio IDE
- Git, GitHub
- Watson Studio.
Course type: coursera_hybrid
Decision: 1318/QĐ-ĐHFPT dated 11/27/2025
Approved date: 2025-11-27
CLO1: Understand the basics of data analysis with Python to building and evaluating data models.
[1] category=Final Project Evaluation; type=on-going; weight=20.0; duration=30'/groups; question_type=CLO1, CLO2, CLO3, CLO4, CLO5, CLO6, CLO7; grading_guide=All chapters; knowledge and skills; completion_criteria=; clos=4
[2] category=On going assessment; type=on-going; weight=30.0; duration=From start to finish in schedule.; question_type=CLO1, CLO2, CLO3, CLO4, CLO5, CLO6, CLO7; grading_guide=knowledge and skills; completion_criteria=; clos=>0
[3] category=Progress test; type=on-going; weight=10.0; duration=45'; question_type=CLO1, CLO2, CLO3, CLO4, CLO5; grading_guide=- cover chapter 1,2,3; completion_criteria=; clos=>0
[4] category=Project Planning; type=on-going; weight=10.0; duration=30'; question_type=CLO1; grading_guide=- cover chapter 1,2,3,4; completion_criteria=; clos=>0
[5] category=Final exam; type=Final exam; weight=30.0; duration=60'; question_type=CLO1, CLO2, CLO3, CLO4, CLO5, CLO6, CLO7; grading_guide=- cover chapter 1,2,3,4; completion_criteria=; clos=4
[1] desc=Data Analysis with Python; author=IBM; publisher=Coursera; edition=; isbn=; main=True; online=True; note=https://www.coursera.org/learn/data-analysis-with-python
[2] desc=Data Visualization with Python; author=IBM; publisher=Coursera; edition=; isbn=; main=True; online=True; note=https://www.coursera.org/learn/python-for-data-visualization
[3] desc=Building AI Applications with Watson APIs; author=IBM; publisher=Coursera; edition=; isbn=; main=True; online=True; note=https://www.coursera.org/learn/building-ai-applications
[4] desc=Applied Data Science Capstone; author=IBM; publisher=Coursera; edition=; isbn=; main=True; online=True; note=https://www.coursera.org/learn/applied-data-science-capstone
[5] desc=GP 1: Simple Linear Regression for the Absolute Beginner; author=Coursera; publisher=Coursera; edition=; isbn=; main=; online=True; note=https://www.coursera.org/projects/simple-linear-regression-for-the-absolute-beginner
[6] desc=GP 2: Predict Ad Clicks Using Logistic Regression and XG-Boost; author=Coursera; publisher=Coursera; edition=; isbn=; main=; online=True; note=https://www.coursera.org/projects/predict-ad-clicks-using-logistic-regression-and-xg-boost
Session 1: - Course Introduction
- Project Topic Introduction and discuss
Topic: Offline; Teaching type: CLO1, CLO2, CLO3, CLO4; LO: IT
ITU: - Slides: Introduction
Materials: mat1
Download: https://flm.fpt.edu.vn/gui/role/student/- Students choose groups of 3-4 members. - Students choose the topic of the group project

Session 2: - Project Topic Introduction and discuss
- Student create group
- Student register the topic
Topic: Offline; Teaching type: CLO1; LO: I
ITU: - Slides: Introduction
Materials: mat2
Download: https://flm.fpt.edu.vn/gui/role/student/- Students choose groups of 3-4 members. - Students choose the topic of the group project

Session 3: - Student presents Project Planning
Topic: Offline; Teaching type: CLO1; LO: U
ITU: - Slides: Chapter 1.1
Materials: mat3
Download: https://flm.fpt.edu.vn/gui/role/student/- Students present their project completion plans.

Session 4: - Student presents Project Planning (cont)
Topic: Offline; Teaching type: CLO1; LO: U
ITU: - Slides: Chapter 1.1
Materials: mat4
Download: https://flm.fpt.edu.vn/gui/role/student/- Students present their project completion plans.
CLO2: Understand how to import data from multiple sources, clean and wrangle data, perform exploratory data analysis (EDA), and create meaningful data visualizations.
Session 1: - Project report 1: P1
+ Business Understanding
Topic: Offline; Teaching type: CLO 4; LO: U
ITU: - Slides: Chapter 1.2
Materials: mat5
Download: - Report understanding of the business being processed, where the data is collected from, understand the data available, and perform data preprocessing steps

Session 2: - Project report 1: P2
+ Data Understand: Collect data, understand data
Topic: Offline; Teaching type: CLO 4; LO: U
ITU: - Slides: Chapter 1.2
Download: - Report understanding of the business being processed, where the data is collected from, understand the data available, and perform data preprocessing steps

Session 3: - Project report 1: P3

+ Perform data preprocessing
Topic: Offline; Teaching type: CLO 4; LO: U
ITU: - Slides: Chapter 1.2
Download: - Report understanding of the business being processed, where the data is collected from, understand the data available, and perform data preprocessing steps

Session 4: Project:
1.1. Data Analysis with Python- importing Datasets 1
1.2. Data Analysis with Python- importing Datasets 2
Topic: Offline; Teaching type: CLO1; LO: U
ITU: - slide chapter 1.3
Download: - Perform steps to import data and preprocess data
CLO3: Know difference ways to effectively visualize both small and large-scale data
Session 1: Project:
1.3 Data Analysis with Python- Data Wrangling 1
1.4 Data Analysis with Python- Data Wrangling 2
Topic: Offline; Teaching type: CLO1; LO: U
ITU: - slide chapter 1.3
Download: - Perform steps to import data and preprocess data

Session 2: - Project report 2: P1
+ Data Analysis
Topic: Offline; Teaching type: CLO2; LO: U
ITU: - slide chapter 1.4
Download: - Reporting: summarize and report basic data analysis steps using python

Session 3: - Project report 2: P2
+ Data Analysis
Topic: Offline; Teaching type: CLO2; LO: U
ITU: - slide chapter 1.4
Download: - Reporting: summarize and report basic data analysis steps using python

Session 4: - Project report 2: P3
+ Data Analysis
Topic: Offline; Teaching type: CLO2; LO: U
ITU: - slide chapter 1.4
Download: - Reporting: summarize and report basic data analysis steps using python
CLO4: Implement various types of basic and advanced graphs and charts like: Waffle Charts, Area Plots, Histograms, Bar Charts, Pie Charts, Scatter Plots, Word Clouds, Choropleth Maps, and many more
Session 1: - Project report 2: P4
+ Data Analysis
Topic: Offline; Teaching type: CLO2; LO: U
ITU: - slide chapter 1.4
Download: - Reporting: summarize and report basic data analysis steps using python

Session 2: - Project:
1.5 Data Analysis with Python- Exploratory Data Analysis 1
Topic: Offline; Teaching type: CLO2; LO: U
ITU: - slide chapter 1.5
Download: - Perform basic data analysis

Session 3: - Project:
1.6 Data Analysis with Python- Exploratory Data Analysis 2
Topic: Offline; Teaching type: CLO2; LO: U
ITU: - slide chapter 1.5
Download: - Perform basic data analysis

Session 4: - Project report 3:
+ Data Visualization in advanced: Waffle Charts
Topic: Offline; Teaching type: CL03; LO: U
ITU: - slide chapter 2.1
Download: - Reporting: Visualize analysis results through chart formats: Waffle Charts, Area Plots, Histograms, Bar Charts, Pie Charts, Scatter Plots, Word Clouds, Choropleth Maps
CLO5: Implement an application that leverages multiple Watson AI services (Discovery, Speech to Text, Assistant, and Text to Speech)
Session 1: - Project report 3:
+ Data Visualization in advanced: Area Plots, Histograms
Topic: Offline; Teaching type: CL03; LO: U
ITU: - slide chapter 2.1
Download: - Reporting: Visualize analysis results through chart formats: Waffle Charts, Area Plots, Histograms, Bar Charts, Pie Charts, Scatter Plots, Word Clouds, Choropleth Maps

Session 2: - Project report 3:
+ Data Visualization in advanced: Bar Charts, Pie Charts
Topic: Offline; Teaching type: CL03; LO: U
ITU: - slide chapter 2.1
Download: - Reporting: Visualize analysis results through chart formats: Waffle Charts, Area Plots, Histograms, Bar Charts, Pie Charts, Scatter Plots, Word Clouds, Choropleth Maps

Session 3: - Project report 3:
+ Data Visualization in advanced: Scatter Plots, Word Clouds
Topic: Offline; Teaching type: CL03; LO: U
ITU: - slide chapter 2.1
Download: - Reporting: Visualize analysis results through chart formats: Waffle Charts, Area Plots, Histograms, Bar Charts, Pie Charts, Scatter Plots, Word Clouds, Choropleth Maps

Session 4: - Project report 3:
+ Data Visualization in advanced: Choropleth Maps
Topic: Offline; Teaching type: CL03; LO: U
ITU: - slide chapter 2.1
Download: - Reporting: Visualize analysis results through chart formats: Waffle Charts, Area Plots, Histograms, Bar Charts, Pie Charts, Scatter Plots, Word Clouds, Choropleth Maps
CLO6: Implementing different techniques to develop applications and AI powered solutions.
Session 1: - Project:
2.1 Data Visualization with Python- Introduction to Data Visualization Tools 1
Topic: Offline; Teaching type: CL03; LO: U
ITU: - slide chapter 2.2
Download: - Perform results representation using advanced chart types

Session 2: - Project:
2.2 Data Visualization with Python- Introduction to Data Visualization Tools 2
Topic: Offline; Teaching type: CL03; LO: U
ITU: - slide chapter 2.2
Download: - Perform results representation using advanced chart types

Session 3: - Project:
2.3 Data Visualization with Python- Basic and Specialized Visualization Tools 1
Topic: Offline; Teaching type: CL03; LO: U
ITU: - slide chapter 2.2
Download: - Perform results representation using advanced chart types

Session 4: - Project:
2.4 Data Visualization with Python- Basic and Specialized Visualization Tools 2
Topic: Offline; Teaching type: CL03; LO: U
ITU: - slide chapter 2.2
Download: - Perform results representation using advanced chart types
CLO7: Implement the small mini capstone data science projec includes steps: involving data collection, data wrangling, exploratory data analysis, data visualization, model development, model evaluation, and reporting
Session 1: - Project:
2.5 Advanced Visualizations and Geospatial Data 1
Topic: Offline; Teaching type: CLO4; LO: U
ITU: - slide chapter 2.3
Download: - Perform results representation using advanced chart types

Session 2: - Project:

2.6 Advanced Visualizations and Geospatial Data 2
Topic: Offline; Teaching type: CLO4; LO: U
ITU: - slide chapter 2.3
Download: - Perform results representation using advanced chart types

Session 3: - Project:
2.7 Data Visualization with Python- Creating Dashboards with Plotly and Dash 1
Topic: Offline; Teaching type: CLO4; LO: U
ITU: - slide chapter 2.3
Download: - Perform results representation using advanced chart types

Session 4: - Project:
2.8 Data Visualization with Python- Creating Dashboards with Plotly and Dash 2
Topic: Offline; Teaching type: CLO4; LO: U
ITU: - slide chapter 2.3
Download: - Perform results representation using advanced chart types
Session 1: - Project review
Topic: Offline; Teaching type: CLO1, CLO2, CLO3, CLO4; LO: T
ITU: - slide chapter 2.4
Download: - Synthesize the results of the report writing

Session 2: - Project review (cont)
Topic: Offline; Teaching type: CLO1, CLO2, CLO3, CLO4; LO: T
ITU: - slide chapter 2.4
Download: - Synthesize the results of the report writing

Session 3: - Project review (cont)
Topic: Offline; Teaching type: CLO1, CLO2, CLO3, CLO4; LO: T
ITU: - slide chapter 2.4
Download: - Synthesize the results of the report writing

Session 4: - Project review (cont)
Topic: Offline; Teaching type: CLO1, CLO2, CLO3, CLO4; LO: T
ITU: - slide chapter 2.4
Download: - Synthesize the results of the report
Session 1: - Project report 4: P1
+ Chatbot: Create and integrate
Topic: Offline; Teaching type: CLO5; LO: U
ITU: - slide chapter 3.1
Download: - create chat bot and integrate using Waston IBM or other platform

Session 2: - Project report 4: P2
+ Chatbot: Create and integrate
Topic: Offline; Teaching type: CLO5; LO: U
ITU: - slide chapter 3.1
Download: - create chat bot and integrate using Waston IBM or other platform

Session 3: - Project report 4: P3
+ Chatbot: Create and integrate
Topic: Offline; Teaching type: CLO5; LO: U
ITU: - slide chapter 3.1
Download: - create chat bot and integrate using Watson IBM or other platform

Session 4: - Project report 4: P4
+ Chatbot: Create and integrate
Topic: Offline; Teaching type: CLO5; LO: U
ITU: - slide chapter 3.1
Download: - create chat bot and integrate using Watson IBM or other platform
Session 1: - Project:
3.1 Building AI Applications with Watson APIs- Introduction 1
Topic: Offline; Teaching type: CLO6; LO: U
ITU: - slide chapter 3.2
Download: - Create and integrate chatbot into Watson IBM or other platform

Session 2: - Project:

3.2 Building AI Applications with Watson APIs- Introduction 2
Topic: Offline; Teaching type: CLO6; LO: U
ITU: - slide chapter 3.2
Download: - Create and integrate chatbot into Watson IBM or other platform

Session 3: - Project:
3.3 Building AI Applications with Watson APIs- Giving it a Voice 1
Topic: Offline; Teaching type: CLO6; LO: U
ITU: - slide chapter 3.2
Download: - Create and integrate chatbot into Watson IBM or other platform

Session 4: - Project:
3.4 Building AI Applications with Watson APIs- Giving it a Voice 2
Topic: Offline; Teaching type: CLO6; LO: U
ITU: - slide chapter 3.2
Download: - Create and integrate chatbot into Watson IBM or other platform
Session 1: - Project:
3.5 Building AI Applications with Watson APIs- Deployment 1
Topic: Offline; Teaching type: CLO6; LO: U
ITU: - slide chapter 3.3
Download: - Create and integrate chatbot into Watson IBM or other platform

Session 2: - Project:
3.6 Building AI Applications with Watson APIs- Deployment 2
Topic: Offline; Teaching type: CLO6; LO: U
ITU: - slide chapter 3.3
Download: - Create and integrate chatbot into Watson IBM or other platform

Session 3: - Project Report 5: P1
+ Build model for prediction
Topic: Offline; Teaching type: CLO6; LO: U
ITU: - slide chapter 1.6
Download: - Report on model building for prediction

Session 4: - Project Report 5: P2
+ Build model for prediction
Topic: Offline; Teaching type: CLO6; LO: U
ITU: - slide chapter 1.6
Download: - Report on model building for prediction
Session 1: - Project Report 5: P3
+ Build model for prediction
Topic: Offline; Teaching type: CLO6; LO: U
ITU: - slide chapter 1.6
Download: - Report on model building for prediction

Session 2: - Project Report 5: P4
+ Build model for prediction
Topic: Offline; Teaching type: CLO6; LO: U
ITU: - slide chapter 1.6
Download: - Report on model building for prediction

Session 3: - Project:
1. 7 Data Analysis with Python- Model Development 1
Topic: Offline; Teaching type: CLO6; LO: U
ITU: - slide chapter 1.7
Download: - Conduct model building and model evaluation

Session 4: - Project:

1.8 Data Analysis with Python- Model Development 2
Topic: Offline; Teaching type: CLO6; LO: U
ITU: - slide chapter 1.7
Download: - Conduct model building and model evaluation
Session 1: - Project:
1.9 Data Analysis with Python- Model Evaluation 1
Topic: Offline; Teaching type: CLO6; LO: U
ITU: - slide chapter 1.7
Download: - Conduct model building and model evaluation

Session 2: - Project:
1.10 Data Analysis with Python- Model Evaluation 2
Topic: Offline; Teaching type: CLO6; LO: U
ITU: - slide chapter 1.7
Download: - Conduct model building and model evaluation

Session 3: - Project report 5: P1
+ Develop applications and AI powered solutions.
Topic: Offline; Teaching type: CLO6; LO: U
ITU: - Slides: Chapter 4
Download: - Build data analysis applications, integrate features in previous sections

Session 4: - Project report 5: P2
+ Develop applications and AI powered solutions.
Topic: Offline; Teaching type: CLO6; LO: U
ITU: - Slides: Chapter 4
Download: - Build data analysis applications, integrate features in previous sections
Session 1: - Project report 5: P3
+ Develop applications and AI powered solutions.
Topic: Offline; Teaching type: CLO6; LO: U
ITU: - Slides: Chapter 4
Download: - Build data analysis applications, integrate features in previous sections

Session 2: - Project report 5: P4
+ Develop applications and AI powered solutions.
Topic: Offline; Teaching type: CLO6; LO: U
ITU: - Slides: Chapter 4
Download: - Build data analysis applications, integrate features in previous sections

Session 3: - Project:
4.1 Applied Data Science Capstone: Introduction 1
4.2 Applied Data Science Capstone: Introduction 2
Topic: Offline; Teaching type: CLO7; LO: U
ITU: - Slides: Chapter 4
Download: - Implement data analysis application development

Session 4: - Project:
4.3 Applied Data Science Capstone: Interactive Visual Analytics and Dashboard 1
4.4 Applied Data Science Capstone: Interactive Visual Analytics and Dashboard 2
4.5 Applied Data Science Capstone: Predictive Analysis (Classification) 1
4.6 Applied Data Science Capstone: Predictive Analysis (Classification) 2
Topic: Offline; Teaching type: CLO7; LO: U
ITU: - Slides: Chapter 4
Download: - Implement data analysis application development
Session 1: - Project:
4.7 Applied Data Science Capstone: Present Your Data-Driven Insights 1
4.8 Applied Data Science Capstone: Present Your Data-Driven Insights 2
'- Progress test
Topic: Offline; Teaching type: CLO7; LO: U
ITU: - Slides: Chapter 4
Download: - Implement data analysis application development
- Conduct Progress test

Session 2: - Evaluate final project
Topic: Offline; Teaching type: CLO1, CLO2, CLO3, CLO4, CLO5, CLO6, CLO7; LO: T
ITU: - Slides chapter 1, 2, 3,4
Download: - Final project report

Session 3: - Evaluate final project (cont)
Topic: Offline; Teaching type: CLO1, CLO2, CLO3, CLO4, CLO5, CLO6, CLO7; LO: T
ITU: - Slides chapter 1, 2, 3,4
Download: - Final project report

Session 4: - Evaluate final project (cont)
- Review course
Topic: Offline; Teaching type: CLO1, CLO2, CLO3, CLO4, CLO5, CLO6, CLO7; LO: I, T
ITU: Syllabus DAP391m
Download: Syllabus DAP391m