[major=AI | course_id=ADY201m | syllabus_id=13675 | semester=3 | combo=core | title=AI, Data Science with Python & SQL]
Course ID: ADY201m
Title EN: AI, Data Science with Python & SQL
Title VI: TTNT và KHDL với Python và SQL
Credits: 3.0
Prerequisites: PFP191, DBI202
Description: The course covers relational database concepts, foundational knowledge of the SQL language. The students will learn some popular tools for data science, understand a methodology that can be used within data science, meet some data science practitioner, understand data gathering, summarize data using descriptive statistics, display and visualize data.
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 the FU FLM at 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 relational database concepts, and foundational knowledge of the SQL language.
[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 1; type=on-going; weight=10.0; duration=From start to 16th session in schedule.; question_type=CLO1, CLO2, CLO3; grading_guide=knowledge and skills; completion_criteria=; clos=>0
[3] category=On going assessment 2; type=on-going; weight=10.0; duration=From 16th to 36th session in schedule.; question_type=CLO4, CLO5; grading_guide=knowledge and skills; completion_criteria=; clos=>0
[4] category=On going assessment 3; type=on-going; weight=10.0; duration=From 37th to finish in schedule.; question_type=CLO6, CLO7; grading_guide=knowledge and skills; completion_criteria=; clos=>0
[5] category=Progress test 1; type=on-going; weight=10.0; duration=45'; question_type=CLO1, CLO2, CLO3, CLO4; grading_guide=- cover chapter 1,2,3,4; completion_criteria=; clos=>0
[6] category=Progress test 2; type=on-going; weight=10.0; duration=45'; question_type=CLO4, CLO5, CLO6, CLO7; grading_guide=- cover chapter 5,6,7; completion_criteria=; clos=>0
[7] category=Project Planning; type=on-going; weight=10.0; duration=30'; question_type=CLO1, CLO2; grading_guide=- cover chapter 1,2,3,4,5,6; completion_criteria=; clos=>0
[8] category=Final exam; type=Final exam; weight=20.0; duration=60'; question_type=CLO1, CLO2, CLO3, CLO4, CLO5, CLO6, CLO7; grading_guide=- cover chapter 1,2,3,4,5,6,7; completion_criteria=1) Every on-going assessment component > 0
2) Final Project Evaluation >=4
3) Final Exam Score >= 4 & Final Result >= 5
Note: Final Project plus 0.5 points for completed IBM certification; clos=4
[1] desc=What is Data Science?; author=IBM; publisher=Coursera; edition=; isbn=; main=True; online=True; note=https://www.coursera.org/learn/what-is-datascience?specialization=ibm-data-science
[2] desc=Data Science Methodology; author=IBM; publisher=Coursera; edition=; isbn=; main=True; online=True; note=https://www.coursera.org/learn/data-science-methodology?specialization=ibm-data-science
[3] desc=Databases and SQL for Data Science with Python; author=IBM; publisher=Coursera; edition=; isbn=; main=True; online=True; note=https://www.coursera.org/learn/sql-data-science
[4] desc=Tools for Data Science; author=IBM; publisher=Coursera; edition=; isbn=; main=True; online=True; note=https://www.coursera.org/learn/open-source-tools-for-data-science?specialization=ibm-data-science
[5] desc=Python for Data Science, AI & Development; author=IBM; publisher=Coursera; edition=; isbn=; main=True; online=True; note=https://www.coursera.org/learn/python-for-applied-data-science-ai?specialization=ibm-data-science
[6] desc=Statistics for Data Science with Python; author=IBM; publisher=Coursera; edition=; isbn=; main=True; online=True; note=https://www.coursera.org/learn/statistics-for-data-science-python
[7] desc=Python Project for Data Science; author=IBM; publisher=Coursera; edition=; isbn=; main=True; online=True; note=https://www.coursera.org/learn/python-project-for-data-science?specialization=ibm-data-science
[8] desc=GP1-Data Manipulation with dplyr in R; author=Coursera; publisher=Coursera; edition=; isbn=; main=; online=True; note=https://www.coursera.org/projects/data-manipulation-with-dplyr-in-r
[9] desc=GP2-Scikit-Learn to Solve Regression Machine Learning Problems; author=Coursera; publisher=Coursera; edition=; isbn=; main=; online=True; note=https://www.coursera.org/projects/scikit-learn-to-solve-regression-ml-problems
Session 1: Course Introduction
Topic: Offline; Teaching type: CLO1; LO: IT
ITU: - Slides: Introduction
Materials: mat1
Download: Read slide introduction
Syllabus ADY201m

Session 2: 1.1. Introduction to Data Science 1
Topic: Offline; Teaching type: CLO2; LO: T
ITU: - Slides: Chapter 1.1
Materials: mat2
Download: https://flm.fpt.edu.vn/gui/role/student/Read Chapter 1.1

Session 3: 1.2. Introduction to Data Science 2
Topic: Offline; Teaching type: CLO2; LO: T
ITU: - Slides: Chapter 1.2
Materials: mat3
Download: https://flm.fpt.edu.vn/gui/role/student/Read Chapter 1.2

Session 4: 1.3 Data Science Topics 1
Topic: Offline; Teaching type: CLO2; LO: I
ITU: - slide chapter 1.3
Materials: mat4
Download: https://flm.fpt.edu.vn/gui/role/student/Read chapter 1.3
CLO2: Define an overview of what data science is today.
Session 1: 1.4 Data Science Topics 2
Topic: Offline; Teaching type: CLO2; LO: I
ITU: - slide chapter 1.4
Download: https://flm.fpt.edu.vn/gui/role/student/Read Chapter 1.4

Session 2: + Practice- Discussing the data science around us:
- Discussing the data science around us
Topic: Offline; Teaching type: CLO2, CLO7; LO: U
ITU: - slide chapter 1
Download: https://flm.fpt.edu.vn/gui/role/student/- Each group discusses problems in which data science is applied to provide solutions.- Create presentation slides about data science problems, including:+ Application domain+ Data sources+ How data science is applied+ What the results are

Session 3: + Project:
- Topic Introduction and discuss
Topic: Offline; Teaching type: CLO2, CLO7; LO: T
ITU: - slide chapter 1
Download: - Research topics provided by the lecturer
- Can suggest topics that the group can develop
- Discuss the group's capabilities
- Ask questions about the topics

Session 4: Project:
- Topic Resgistration
Topic: Offline; Teaching type: CLO4, CLO7; LO: T
ITU: - Slides: Chapter 2
Download: - Student groups choose topics or propose topics themselves
CLO3: Know tools for Data Science, know how to use at least one tool for Data Science
Session 1: Practice: Data Science Methodology in theory and practice
- Understanding of the data science methodology
Topic: Offline; Teaching type: CLO4; LO: U
ITU: - Slides: Chapter 2
Download: - Student groups propose methodologies and ways to solve data science problems
- Provide questions for data science problems
- Distinguish between descriptive problems and data prediction problems

Session 2: Project:
- Understand the Problem
Topic: Offline; Teaching type: CLO4, CLO7; LO: U, I
ITU: - Slides: Chapter 2
Download: - Groups discuss their understanding of the chosen topic
- Can come up with a plan for addressing the topic

Session 3: Project:
- Business Understanding
- Understand Analytic Approach
Topic: Offline; Teaching type: CLO4, CLO7; LO: U
ITU: - Slides: Chapter 2
Download: https://flm.fpt.edu.vn/gui/role/student/Corresponding to the chosen project, the student group discusses and gives the answer: what is the problem we are solving?- Give 5 questions to clarify what problem we need to solve.- Understand the importance of Business Understanding- Understand the types of data analysis: description, answering questions (why, what), prediction, or providing solutions- Apply to the group project

Session 4: Project:
- Data Requirements
- Data Collection
Topic: Offline; Teaching type: CLO4, CLO7; LO: U
ITU: - Slides: Chapter 2
Download: - Students understand the data needed for the project
- Students understand the methods of data collection
- Apply to the group project
CLO4: Understand why we are interested in data science, what a methodology is, and why data scientists need a methodology.
Session 1: Project:
- Data Understand
- Data Preprocessing
Topic: Offline; Teaching type: CLO4, CLO7; LO: U
ITU: - Slides: Chapter 2
Download: - Understand the data that has been collected, what data is needed
- Understand the concepts of data preparation, data cleaning
- Understand the ways to prepare, clean data
- Apply to the group project

Session 2: Project:
- Modeling
- Evaluation
Topic: Offline; Teaching type: CLO4, CLO7; LO: U
ITU: - Slides: Chapter 2
Download: - Learn ways to represent data after analysis to answer the questions if
- Evaluate whether the model answers the questions, satisfies the problem stated
- Apply to the group project

Session 3: Project:
- Deployment
- Feedback
Topic: Offline; Teaching type: CLO4, CLO7; LO: U
ITU: - Slides: Chapter 2
Download: - Learn how to deploy data science projects
- Understand the feedback process after deployment to update or upgrade the model
- Apply to the team project

Session 4: 2.6 Data science methodology
- Project Review 1
Topic: Offline; Teaching type: CLO4; LO: T
ITU: - slide chapter 2
Download: - Students Summarize the group project report
CLO5: Discusses Python fundamentals, python libraries, API suport for data science
Session 1: 2.7 Data science steps
- Project Review 1 (cont)
Topic: Offline; Teaching type: CLO4; LO: T
ITU: - slide chapter 2.6, 2.7
Download: - Students Summarize the group project report

Session 2: Project Planing
Topic: Offline; Teaching type: CLO1, CLO2, CLO3, CLO7; LO: U
ITU: - Slides: Chapter 2, 3
Download: - Students complete the final project plan through the steps above
- Changes may be made after feedback from the instructor

Session 3: Project:
- Accessing Databases using Python
Topic: Offline; Teaching type: CLO1, CLO2, CLO3, CLO7; LO: U
ITU: - Slides: Chapter 3
Download: - Students know how to read files to import into the database management system
- Students understand how to connect to the database
- Apply to the group project

Session 4: Project:
- Data Analysis with SQL- Basic
Topic: Offline; Teaching type: CLO1, CLO2, CLO3, CLO7; LO: U
ITU: - Slides: Chapter 3
Download: - Students perform data queries on db using sql
- The questions above or the lecturer gives requirements on data queries
CLO6: Explain the statistics for Data Science: mean, median, mode, variance, and standard deviation, data visualization, regression analysis
Session 1: Project:
- Data Analysis with SQL- Intermediate
Topic: Offline; Teaching type: CLO1, CLO2, CLO3, CLO7; LO: U
ITU: - Slides: Chapter 3
Download: - Students perform data queries on db using sql
- The questions above or the lecturer gives requirements on data queries

Session 2: Project:
- Data Analysis with SQL - Advance
Topic: Offline; Teaching type: CLO1, CLO2, CLO3, CLO7; LO: U
ITU: - Slides: Chapter 3
Download: - Students perform data queries on db using sql
- The questions above or the lecturer gives requirements on data queries

Session 3: +Practice: database basic, intermediate
- practice composing nested queries
- execute select statements to access data from multiple tables
Topic: Offline; Teaching type: CLO1, CLO2, CLO3; LO: U
ITU: - Slides: Chapter 3
Download: - Students perform data queries on db using sql
- The questions above or the lecturer gives requirements on data queries

Session 4: Practice: cont'
Topic: Offline; Teaching type: CLO1, CLO2, CLO3; LO: U
ITU: - Slides: Chapter 3
Download: - Students perform data queries on db using sql
- The questions above or the lecturer gives requirements on data queries
CLO7: Implement the small data science project by applying Python fundamentals, and Python data structures, and working with data in Python.
Session 1: - Getting started with SQL
- Data analysis with SQL
Topic: Offline; Teaching type: CLO1; LO: T
ITU: slide chapter 3
Download: read chapter 3

Session 2: + Practice: Introduce students to data science tools. Perform basic operations on data
+ Project:
- Analysis with tool introduction
Topic: Offline; Teaching type: CLO3, CLO7; LO: U
ITU: - Slides: Chapter 4
Download: - Students learn about tools used for data analysis
- Know how to use tools for data analysis

Session 3: + Project:
- Analysis with tool introduction
Topic: Offline; Teaching type: CLO3, CLO7; LO: U
ITU: - Slides: Chapter 4
Download: - Review chapter 4
- Do project

Session 4: Project:
- Analysis with tool using Python
Topic: Offline; Teaching type: CLO3, CLO7; LO: U
ITU: - Slides: Chapter 4
Download: - Students use python language to program on tools (basic pandas)
Session 1: Project:
- Analysis with tool using R
Topic: Offline; Teaching type: CLO3, CLO7; LO: U
ITU: - Slides: Chapter 4
Download: - Students use R to analyze data

Session 2: Project:
- Analysis with tool using Scala
Topic: Offline; Teaching type: CLO3, CLO7; LO: U
ITU: - Slides: Chapter 4
Download: - Students use Scala to analyze data

Session 3: Project:
- Analysis with tool using SQL
Topic: Offline; Teaching type: CLO3, CLO7; LO: U
ITU: - Slides: Chapter 4
Download: - Students use SQL to query data on the tool's DB

Session 4: Project:
- Analysis with tool using GitHub
Topic: Offline; Teaching type: CLO3, CLO7; LO: U
ITU: - Slides: Chapter 4
Download: https://flm.fpt.edu.vn/gui/role/student/- Students use github to share data, code, and projects.
Session 1: Project:
- Analysis with tool using Jupyter Notebooks
Topic: Offline; Teaching type: CLO3, CLO7; LO: U
ITU: - Slides: Chapter 4
Download: - Students know how to use Jupyter Notebooks to code data analysis

Session 2: Project:
- Analysis with tool using RStudio IDE
Topic: Offline; Teaching type: CLO3, CLO7; LO: U
ITU: - Slides: Chapter 4
Download: - Students use RStudio IDE to analyze data

Session 3: Project:
- Analysis with tool using Watson Studio
Topic: Offline; Teaching type: CLO3, CLO7; LO: U
ITU: - Slides: Chapter 4
Download: https://flm.fpt.edu.vn/gui/role/student/Students create accounts and use Watson Studio for data analysis.

Session 4: Project Review 2
Topic: Offline; Teaching type: CLO1, CLO2, CLO3, CLO4, CLO7; LO: T
ITU: - slide chapter 1, 2, 3,4
Download: - Summarize and report the results of data analysis implementation on the tool
Session 1: Project Review 2 (cont)
Topic: Offline; Teaching type: CLO1, CLO2, CLO3, CLO4, CLO7; LO: T
ITU: - slide chapter 1, 2, 3,4
Download: - Summarize and report the results of data analysis implementation on the tool

Session 2: Progress test and/or
Review Exercises
Guiding Exercises/Assignment
Topic: Offline; Teaching type: CLO1, CLO2, CLO3, CLO4; LO: U
ITU: - slide chapter 1, 2, 3,4
Download: - review slide chapter 1, 2, 3,4

Session 3: Project:
- Understand python API
Topic: Offline; Teaching type: CLO5, CLO7; LO: U
ITU: - slide chapter 5
Download: - Students know how to use API to scrape data

Session 4: Project:
- Analysis with Python- Collect Data
Topic: Offline; Teaching type: CLO5, CLO7; LO: U
ITU: - slide chapter 5
Download: - The group self-scrapes data for the group's topic
Session 1: Project:
- Analysis with Python- Understand Data
Topic: Offline; Teaching type: CLO5, CLO7; LO: U
ITU: - slide chapter 5
Download: - Understand the data of the group that has been scraped

Session 2: Project:
- Analysis with Python- Preprocessing Data
Topic: Offline; Teaching type: CLO5, CLO7; LO: U
ITU: - slide chapter 5
Download: - History of processing and cleaning data of the scraped group

Session 3: Project:
- Analysis
Topic: Offline; Teaching type: CLO1, CLO2, CLO3, CLO4, CLO5, CLO6, CLO7; LO: U
ITU: - slide chapter 5
Download: - History of processing and cleaning data of the scraped group

Session 4: Project:
- Analysis
Topic: Offline; Teaching type: CLO1, CLO2, CLO3, CLO4, CLO5, CLO6, CLO7; LO: U
ITU: - slide chapter 5
Download: - History of processing and cleaning data of the scraped group
Session 1: - Practice: Python for Data Science, AI & Development
Topic: Offline; Teaching type: CLO5; LO: U
ITU: - slide chapter 5
Download: - Complete data scraping and data analysis on the tool

Session 2: Project:
- Basic Data Statistics
Topic: Offline; Teaching type: CLO6, CLO7; LO: U
ITU: - slide chapter 6
Download: - Students understand the basic concepts of statistics
- Apply to group projects

Session 3: Project:
- Advance Data Statistics
Topic: Offline; Teaching type: CLO6, CLO7; LO: U
ITU: - slide chapter 6
Download: - Students understand advanced concepts of statistics
- Apply to group projects

Session 4: Project:
- Basic Data Visualization
Topic: Offline; Teaching type: CLO6, CLO7; LO: U
ITU: - slide chapter 6
Download: - Students understand the ways of data visualization
- Apply to group projects
Session 1: Project:
- Advance Data Visualization
Topic: Offline; Teaching type: CLO6, CLO7; LO: U
ITU: - slide chapter 6
Download: - Students understand advanced data visualization methods with chart types
- Apply to group projects

Session 2: Project:
- Basic Data Probability Distributions
Topic: Offline; Teaching type: CLO6, CLO7; LO: U
ITU: - slide chapter 6
Download: - Students understand basic statistical probability
- Apply to group projects

Session 3: Project:
- Advance Data Probability Distributions
Topic: Offline; Teaching type: CLO6, CLO7; LO: U
ITU: - slide chapter 6
Download: - Students understand advanced statistical probability
- Apply to group projects

Session 4: Project:
- Basic Regression Analysis
Topic: Offline; Teaching type: CLO6, CLO7; LO: U
ITU: - slide chapter 6
Download: - Students understand the basic regression analysis model
- Apply to group projects
Session 1: Project:
- Advance Regression Analysis
Topic: Offline; Teaching type: CLO6, CLO7; LO: U
ITU: - slide chapter 6
Download: - Students understand advanced regression analysis models
- Apply to group projects

Session 2: Project:
- Advance Regression Analysis
Topic: Offline; Teaching type: CLO1, CLO2, CLO3, CLO4, CLO5, CLO6, CLO7; LO: U
ITU: - slide chapter 6
Download: - Students understand advanced regression analysis models
- Apply to group projects

Session 3: Project:
- Advance Regression Analysis
Topic: Offline; Teaching type: CLO1, CLO2, CLO3, CLO4, CLO5, CLO6, CLO7; LO: U
ITU: - slide chapter 6
Download: - Students understand advanced regression analysis models
- Apply to group projects

Session 4: Practice: Statistics for Data Science with Python- Housing data
Topic: Offline; Teaching type: CLO6; LO: U
ITU: - slide chapter 5.1, 5.2, 5.3, 5.4, 5.5, 5.6
Download: - Use statistical and probability knowledge to analyze the group's project
- Model project data: answer the given questions
- Perform data prediction
Session 1: - Project Review 3
Topic: Offline; Teaching type: CLO1, CLO2, CLO3, CLO4, CLO5, CLO6, CLO7; LO: T
ITU: - slide chapter 1, 2, 3, 4, 5, 6
Download: - project progress report

Session 2: - Project Review 3 (cont)
Topic: Offline; Teaching type: CLO1, CLO2, CLO3, CLO4, CLO5, CLO6, CLO7; LO: T
ITU: - slide chapter 1, 2, 3, 4, 5, 6
Download: - project progress report

Session 3: Progress test and/or
Review Exercises
Guiding Exercises/Assignment
Topic: Offline; Teaching type: CLO1, CLO2, CLO3, CLO4, CLO5, CLO6, CLO7; LO: T
ITU: - slide chapter 1, 2, 3, 4,5, 6, 7
Download: Process test

Session 4: - Review course
- Final report
Topic: Offline; Teaching type: CLO1, CLO2, CLO3, CLO4, CLO5, CLO6, CLO7; LO: I, T
ITU: Syllabus ADY201m
Download: Syllabus ADY201m