[major=AI | course_id=DAT301m | syllabus_id=13293 | semester=7 | combo=core | title=AI Development]
Course ID: DAT301m
Title EN: AI Development
Title VI: Phát triển UDTTNT với TensorFlow
Credits: 3.0
Prerequisites: CPV301, DPL302m
Description: Learn how to build real-world AI applications with TensorFlow! In this hands-on course, you’ll train neural networks for computer vision, apply techniques like data augmentation, dropout, and transfer learning, and build natural language processing systems using RNNs, GRUs, and LSTMs. Through project-based learning, you’ll gain practical experience creating image classifiers, object detectors, and text generators—preparing you with the skills to design and deploy powerful AI solutions.
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, Google Colab, ChatGPT, Github Copilot
Course type: coursera_hybrid
Decision: 932/QĐ-ĐHFPT dated 08/22/2025
Approved date: 2025-08-22
CLO1: Understand the basics of TensorFlow and application of TensorFlow framework in Machine Learning, Deep Learning.
[1] category=Progress test; type=on-going; weight=10.0; duration=45'; question_type=CLO1, CLO2, CLO3, CLO4, CLO5, CLO6; grading_guide=- cover chapter 1,2,3; completion_criteria=; clos=>0
[2] category=Report 1: Project Proposal [ Oral group presentation]; type=on-going; weight=10.0; duration=225'; question_type=CLO9, CLO10; grading_guide=- cover chapter 1; completion_criteria=; clos=>0
[3] category=Report 2: Data Tasks [ Oral group presentation]; type=on-going; weight=10.0; duration=225'; question_type=CLO9, CLO10; grading_guide=- cover chapter 2; completion_criteria=; clos=>0
[4] category=Report 3: Model & Results [ Oral group presentation]; type=on-going; weight=30.0; duration=225'; question_type=CLO9, CLO10; grading_guide=- cover chapter 3; completion_criteria=; clos=>0
[5] category=Report 4: Final report & Group presentation; type=on-going; weight=10.0; duration=225'; question_type=CLO9, CLO10; grading_guide=- cover chapter 4; completion_criteria=; clos=>0
[6] category=Final exam; type=Final exam; weight=30.0; duration=60'; question_type=CLO1, CLO2, CLO3, CLO4, CLO5, CLO6, CLO7, CLO8; grading_guide=- cover chapter 1, 2, 3, 4; completion_criteria=1) Every on-going assessment component > 0
2) Final Exam Score >= 4 & Final Result >= 5; clos=4
[1] desc=Convolutional Neural Networks in TensorFlow; author=Coursera; publisher=https://www.coursera.org/learn/convolutional-neural-networks-tensorflow; edition=; isbn=; main=True; online=True; note=
[2] desc=Guided Project
Object Localization with TensorFlow; author=Coursera; publisher=https://www.coursera.org/programs/fptu-fall-2024-zb2kn/projects/object-localization-tensorflow?source=search; edition=; isbn=; main=; online=True; note=
[3] desc=Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning; author=Coursera; publisher=https://www.coursera.org/learn/introduction-tensorflow; edition=; isbn=; main=True; online=True; note=
[4] desc=Natural Language Processing in TensorFlow; author=Coursera; publisher=https://www.coursera.org/learn/natural-language-processing-tensorflow; edition=; isbn=; main=True; online=True; note=
[5] desc=Sequences, Time Series and Prediction; author=Coursera; publisher=https://www.coursera.org/learn/tensorflow-sequences-time-series-and-prediction; edition=; isbn=; main=True; online=True; note=
Session 1: Course Introduction
Topic: Offline; Teaching type: CLO1,CLO9; LO: T
ITU: - slides: Introduction
Materials: mat1
Download: Read slide introduction
Syllabus DAT301m

Session 2: 1.1. Working with TensorFlow
Topic: Offline; Teaching type: CLO1,CLO9; LO: T
ITU: - slides: chapter 1.1
Download: https://flm.fpt.edu.vn/gui/role/student/Read Chapter 1.1

Session 3: 1.2. Machine learning and computer vision in TensorFlow
Topic: Offline; Teaching type: CLO1,CLO9; LO: T
ITU: - slides: chapter 1.2
Download: https://flm.fpt.edu.vn/gui/role/student/Read Chapter 1.2

Session 4: 1.3 Coding with TensorFlow in Google Colaboratory
Topic: Offline; Teaching type: CLO1,CLO9; LO: T
ITU: - slide chapter 1.3
Download: https://flm.fpt.edu.vn/gui/role/student/Read chapter 1.3
CLO10: Implement a AI project includes steps: data collection, data wrangling, exploratory data analysis, model development, model evaluation, and reporting
Session 1: 1.4 Computer Vision Neural Network
Topic: Offline; Teaching type: CLO2,CLO9; LO: T
ITU: - slide chapter 1.4
Download: https://flm.fpt.edu.vn/gui/role/student/Read Chapter 1.4

Session 2: 1.5 Understand Convolutional Neural Networks in TensorFlow
Topic: Offline; Teaching type: CLO2,CLO9; LO: T
ITU: - slide chapter 1.5
Download: https://flm.fpt.edu.vn/gui/role/student/Read Chapter 1.5

Session 3: 1.6 The techniques of Convolutional Neural Networks in TensorFlow
Topic: Offline; Teaching type: CLO2,CLO9; LO: T
ITU: - slide chapter 1.6
Download: https://flm.fpt.edu.vn/gui/role/student/Read Chapter 1.6

Session 4: Discussion on the Capstone Project (CP) topic
Topic: Offline; Teaching type: CLO9,CLO10; LO: U
ITU:
CLO2: Understand how to build a basic neural network in TensorFlow and train a neural network for a computer vision application.
Session 1: Formation of teams/groups
Topic: Offline; Teaching type: CLO9,CLO10; LO: U
ITU: 

Session 2: Discuss and choose a project topic
Topic: Offline; Teaching type: CLO9,CLO10; LO: U
ITU: 

Session 3: Report 1: Project Proposal (Discussion)
Topic: Offline; Teaching type: CLO9,CLO10; LO: U
ITU: 

Session 4: 2.1 The large dataset in the Neural network
Topic: Offline; Teaching type: CLO3,CLO9; LO: T
ITU: - slide chapter 2.1
Download: https://flm.fpt.edu.vn/gui/role/student/Read Chapter 2.1
CLO3: Understan the convolutional Neural Networks in TensorFlow, include the strategies to prevent overfitting, including augmentation and dropout
Session 1: 2.2 Image Augmentation
Topic: Offline; Teaching type: CLO3,CLO9; LO: T
ITU: - slide chapter 2.2
Download: https://flm.fpt.edu.vn/gui/role/student/Read Chapter 2.2

Session 2: 2.3 Overfitting and solutions
Topic: Offline; Teaching type: CLO3,CLO9; LO: T
ITU: - slide chapter 2.3
Download: https://flm.fpt.edu.vn/gui/role/student/Read Chapter 2.3

Session 3: 2.4 The concept of transfer learning
Topic: Offline; Teaching type: CLO4,CLO9; LO: T
ITU: - slide chapter 2.4
Download: https://flm.fpt.edu.vn/gui/role/student/Read Chapter 2.4

Session 4: 2.5 Create model with transferred features
Topic: Offline; Teaching type: CLO4,CLO9; LO: T
ITU: - slide chapter 2.5
Download: https://flm.fpt.edu.vn/gui/role/student/Read Chapter 2.5
CLO4: Undesrstand the transfer learning and how learned features can be extracted from models
Session 1: 2.6 Exploring dropouts and Transfer Learning with Inception
Topic: Offline; Teaching type: CLO4,CLO9; LO: T
ITU: - slide chapter 2.6
Download: https://flm.fpt.edu.vn/gui/role/student/Read Chapter 2.6

Session 2: 2.7 The multi-class classification: discusses and examples
Topic: Offline; Teaching type: CLO4,CLO9; LO: T
ITU: - slide chapter 2.7
Download: https://flm.fpt.edu.vn/gui/role/student/Read Chapter 2.7

Session 3: Team Meeting: Project Proposal Writing (Report 1)
Topic: Offline; Teaching type: CLO9,CLO10; LO: U
ITU: 

Session 4: Team Meeting: Project Proposal Writing (Report 1)
Topic: Offline; Teaching type: CLO9,CLO10; LO: U
ITU:
CLO5: Understand basic concepts of sentiment in text, word Embeddings, sequence model and literature
Session 1: Team Meeting: Instructor's feedbacks for Project Proposal (Report 1)
Topic: Offline; Teaching type: CLO9,CLO10; LO: U
ITU: 

Session 2: Team Meeting: Instructor's feedbacks for Project Proposal (Report 1)
Topic: Offline; Teaching type: CLO9,CLO10; LO: U
ITU: 

Session 3: Team Meeting: Instructor's feedbacks for Project Proposal (Report 1)
Topic: Offline; Teaching type: CLO9,CLO10; LO: U
ITU: 

Session 4: Team Meeting: Instructor's feedbacks for Project Proposal (Report 1)
Topic: Offline; Teaching type: CLO9,CLO10; LO: U
ITU:
CLO6: Implementing natural language processing systems using TensorFlow
Session 1: Team Meeting: Data Collection(Present the issues discussed and agreed upon by the group) (Report 2)
Topic: Offline; Teaching type: CLO9,CLO10; LO: U
ITU: 

Session 2: 3.1 The word based encodings in TensorFlow
Topic: Offline; Teaching type: CLO5,CLO9; LO: T
ITU: - slide chapter 3.1
Download: https://flm.fpt.edu.vn/gui/role/student/Read Chapter 3.1

Session 3: 3.2 Text to sequence in TensorFlow
Topic: Offline; Teaching type: CLO5,CLO9; LO: T
ITU: - slide chapter 3.2
Download: https://flm.fpt.edu.vn/gui/role/student/Read Chapter 3.2

Session 4: 3.3 The Tokenizer in TensorFlow
Topic: Offline; Teaching type: CLO5,CLO9; LO: T
ITU: - slide chapter 3.3
Download: https://flm.fpt.edu.vn/gui/role/student/Read Chapter 3.3
CLO7: Understand the sequences, time series and prediction problems in TensorFlow
Session 1: 3.4 The padding in TensorFlow
Topic: Offline; Teaching type: CLO5.CLO9; LO: T
ITU: - slide chapter 3.4
Download: https://flm.fpt.edu.vn/gui/role/student/Read Chapter 3.4

Session 2: 3.5 The vector in TensorFlow
Topic: Offline; Teaching type: CLO5,CLO9; LO: T
ITU: - slide chapter 3.5
Download: https://flm.fpt.edu.vn/gui/role/student/Read Chapter 3.5

Session 3: 3.6 Classifier for the sarcasm dataset
Topic: Offline; Teaching type: CLO6,CLO9; LO: T
ITU: - slide chapter 3.6
Download: https://flm.fpt.edu.vn/gui/role/student/Read Chapter 3.6

Session 4: 3.7 Subwords text encoder
Topic: Offline; Teaching type: CLO6,CLO9; LO: T
ITU: - slide chapter 3.7
Download: https://flm.fpt.edu.vn/gui/role/student/Read Chapter 3.7
CLO8: Understand how to apply RNNs, GRUs, and LSTMs as you train them using text repositories
Session 1: 3.8 The Long Short Term Memory (LSTM) for NLP
Topic: Offline; Teaching type: CLO6,CLO9; LO: T
ITU: - slide chapter 3.8
Download: https://flm.fpt.edu.vn/gui/role/student/Read Chapter 3.8

Session 2: 3.9 Exploring different sequence models
Topic: Offline; Teaching type: CLO6,CLO9; LO: T
ITU: - slide chapter 3.9
Download: https://flm.fpt.edu.vn/gui/role/student/Read Chapter 3.9

Session 3: 3.10 Sequence models and literature for NLP
Topic: Offline; Teaching type: CLO6,CLO9; LO: T
ITU: - slide chapter 3.10
Download: https://flm.fpt.edu.vn/gui/role/student/Read Chapter 3.10

Session 4: Team Meeting: Data Collection(Present the issues discussed and agreed upon by the group) (Report 2)
Topic: Offline; Teaching type: CLO9,CLO10; LO: U
ITU:
CLO9: Understand how to apply AI tools to complete a mini project
Session 1: Team Meeting: Instructor's feedbacks for Data Tasks all phase (Report 2)
Topic: Offline; Teaching type: CLO9,CLO10; LO: U
ITU: 

Session 2: Team Meeting: Instructor's feedbacks for Data Tasks all phase (Report 2)
Topic: Offline; Teaching type: CLO9,CLO10; LO: U
ITU: 

Session 3: Team Meeting: Instructor's feedbacks for Data Tasks all phase (Report 2)
Topic: Offline; Teaching type: CLO9,CLO10; LO: U
ITU: 

Session 4: Progess test
Topic: Offline; Teaching type: CLO1, CLO2, CLO3, CLO4, CLO5, CLO6; LO: T
ITU: - slide chapter 1, 2,3
Download: - slide chapter 1, 2,3
Session 1: 4.1 The introduction of Time series and its application
Topic: Offline; Teaching type: CLO7,CLO9; LO: T
ITU: - slide chapter 4.1
Download: https://flm.fpt.edu.vn/gui/role/student/Read Chapter 4.1

Session 2: 4.2 Machine learning applied to time series
Topic: Offline; Teaching type: CLO7,CLO9; LO: T
ITU: - slide chapter 4.2
Download: https://flm.fpt.edu.vn/gui/role/student/Read Chapter 4.2

Session 3: 4.3 Time series: Train, validation and test sets
Topic: Offline; Teaching type: CLO7,CLO9; LO: T
ITU: - slide chapter 4.3
Download: https://flm.fpt.edu.vn/gui/role/student/Read Chapter 4.3

Session 4: 4.4 Time series: Metrics for evaluating performance
Topic: Offline; Teaching type: CLO7,CLO9; LO: T
ITU: - slide chapter 4.4
Download: https://flm.fpt.edu.vn/gui/role/student/Read Chapter 4.4
Session 1: 4.5 Time series:tips to build the forecasting
Topic: Offline; Teaching type: CLO7,CLO9; LO: T
ITU: - slide chapter 4.5
Download: https://flm.fpt.edu.vn/gui/role/student/Read Chapter 4.5

Session 2: 4.6 Deep neural networks for time series: Preparing features and labels
Topic: Offline; Teaching type: CLO8,CLO9; LO: T
ITU: - slide chapter 4.6
Download: https://flm.fpt.edu.vn/gui/role/student/Read Chapter 4.6

Session 3: 4.7 Deep neural networks for time series: build the layer neural network
Topic: Offline; Teaching type: CLO8,CLO9; LO: T
ITU: - slide chapter 4.7
Download: https://flm.fpt.edu.vn/gui/role/student/Read Chapter 4.7

Session 4: 4.8 Deep neural networks for time series: training, tuning and prediction
Topic: Offline; Teaching type: CLO8,CLO9; LO: T
ITU: - slide chapter 4.8
Download: https://flm.fpt.edu.vn/gui/role/student/Read Chapter 4.8
Session 1: 4.9 Conceptual of Recurrent neural network for time series
Topic: Offline; Teaching type: CLO8,CLO9; LO: T
ITU: - slide chapter 4.9
Download: https://flm.fpt.edu.vn/gui/role/student/Read Chapter 4.9

Session 2: 4.10 Recurrent neural network for time series: input, lambda layer, learnig rate, output
Topic: Offline; Teaching type: CLO8,CLO9; LO: T
ITU: - slide chapter 4.10
Download: https://flm.fpt.edu.vn/gui/role/student/Read Chapter 4.10

Session 3: Team Meeting: Model & Results (Present the issues discussed and agreed upon by the group) (Report 3)
Topic: Offline; Teaching type: CLO9,CLO10; LO: U
ITU: 

Session 4: Team Meeting: Model & Results (Present the issues discussed and agreed upon by the group) (Report 3)
Topic: Offline; Teaching type: CLO9,CLO10; LO: U
ITU:
Session 1: Team Meeting: Instructor's feedbacks for Model & Results (Report 3)
Topic: Offline; Teaching type: CLO9,CLO10; LO: U
ITU: 

Session 2: Team Meeting: Instructor's feedbacks for Model & Results (Report 3)
Topic: Offline; Teaching type: CLO9,CLO10; LO: U
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Session 3: Team Meeting: Instructor's feedbacks for Model & Results (Report 3)
Topic: Offline; Teaching type: CLO9,CLO10; LO: U
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Session 4: Team Meeting: Practice for Presentation of Capstone Project (Report 4)
Topic: Offline; Teaching type: CLO9,CLO10; LO: U
ITU:
Session 1: Team Meeting: Practice for Presentation of Capstone Project (Report 4)
Topic: Offline; Teaching type: CLO9,CLO10; LO: U
ITU: 

Session 2: Team Meeting: Practice for Presentation of Capstone Project (Report 4)
Topic: Offline; Teaching type: CLO9,CLO10; LO: U
ITU: 

Session 3: Team Meeting: Practice for Presentation of Capstone Project (Report 4)
Topic: Offline; Teaching type: CLO9,CLO10; LO: U
ITU: 

Session 4: Review course
Results
Topic: Offline; Teaching type: CLO1, CLO2, CLO3, CLO4, CLO5, CLO6, CLO7, CLO8; LO: U
ITU: Syllabus DAT301m
Slide chapter 1,2,3,4
Download: Syllabus DAT301m
Slide chapter 1,2,3,4