Final Project - Data Science
ABOUT THE COURSE!
You have completed four courses of Data Science Program. Having started with Introduction to Data Science course, you learned about Data Science's concepts, methodology, algorithms and applications of Data Science. In the second course, Data Analysis, you acquired how to query data from database, process data using Python and analyze data with visualization. Then, in the Machine Learning course, you learned the basics of machine learning and its application in different fields such as health care, banking, telecommunication and about the most effective machine learning techniques. Also in the Deep Learning course, you acquired knowledge on the modern neural networks and their applications in computer vision and natural language understanding.
In this final project, you will have a chance to engage in a real-world project and actually experience the tasks of a data scientist first-hand. For the project requirements, you will describe the Business Understanding in a report. Then you will use your analysis skill to understand provided data to find the best features. After that, you will apply machine learning to build a predictive model. Finally, you will learn how to make a RestFul API that makes prediction with new data.
COURSE INFORMATION
| Course code: | DSP305x |
| Course name: |
Final Project - Data Science |
| Credits: | 3 |
| Estimated Time: | 6 weeks. |
COURSE OBJECTIVES
- Comprehensively manipulate data science life cycle to a real problem.
- Apply analytical and visualization skills to analyze the data and complete feature selection.
- Choose the suitable Machine Learning algorithms and reasonable evaluation metrics for a real problem.
- Apply a great number of techniques to improve the model accuracy.
- Understand and apply Flask to create an API for a data science project.
- Be able to write a data science report in details.
COURSE STRUCTURE
- Guide 1: Project Overview
- Guide 2: Project Details
- Guide 3: Project Instruction
- Guide 4: Project Rubrics
- Guide 5: Project Schedule Guide
- Guide 6: Project Submission & Defense
DEVELOPMENT TEAM
COURSE DESIGNER
M.S. Vu Thuong Huyen
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REVIEWERS & TESTER
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Course Reviewer
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Course Tester
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Ph.D. Dang Hoang Vu |
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B.A. Ho Quoc Bao |
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Program Reviewers
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Assoc. Prof. Tu Minh Phuong |
Ph.D. Nguyen Van Vinh |
Ph.D. Tran The Trung |
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Learning resources
In modern times, each subject has numerous relevant studying materials including printed and online books. FUNiX Way does not provide a specific learning resource but offers recommendation for students to choose the most appropriate source to them. In the process of studying from many different sources based on that personal choice, students will be timely connected to a mentor to respond to their questions. All the assessments including multiple choice questions, exercises, projects and oral exams are designed, developed and conducted by FUNiX.
Learners are under no obligation to choose a fixed learning material. They are encouraged to actively find and study from any appropriate sources including printed textbooks, MOOCs or websites. Students are on their own responsibilities in using these learning sources and ensuring full compliance with the source owners’ policies; except for the case in which they have an official cooperation with FUNiX. For further support, feel free to contact FUNiX Academic Department for detailed instructions.
Learning resources are recommended below. It should be noted that listing these learning sources does not necessarily imply that FUNiX has an official partnership with the source’s owner: Coursera, tutorialspoint, edX Training, or Udemy.
Feedback channel
FUNiX is ready to receive and discuss all comments and feedback related to learning materials via email [email protected] or [email protected]