| Course title | |||||
| データサイエンス演習 [Exercise for Data Science] | |||||
| Course category | Requirement | Credit | 1 | ||
| Department | Year | ～ | Semester | 3rd | |
| Course type | 3rd | Course code | WISE4003 | ||
| Instructor(s) | |||||
| 近藤 敏之, PHAN MINH KHANH [KONDO Toshiyuki, PHAN Minh Khanh] | |||||
| Facility affiliation | Faculty of Engineering | Office | afjgxte/L1151 | Email address | |
| Course description |
| This course is an exercise subject linked to the lecture on "Outline of Data Science." Using the programming language Python, we carry out practical exercises on data processing, analysis, and visualization that are the foundation of data science. In addition, students will understand and learn basic machine learning methods (support vector machines, neural networks, etc.). |
| Expected Learning |
|
- Learn the basics of Python. - Learn the data processing and analysis skills using Python, NumPy, SciPy, and Pandas. - Learn the skills to visualize data using matplotlib. - Learn the basic machine learning methods using scikit-learn etc. See the Curriculum maps. |
| Course schedule |
|
1: Orientation and setup of the programming practice environment 2-3: Basics of Python (variables, data types, control structures) 4-5: The basics of NumPy (array, matrix operation) 6-7: Basics of Pandas (Construction of DataFrame, Data Visualization) 8-9: Data visualization (matplotlib) 10-12: Supervised learning using scikit-learn (support vector machine) 13-14: Basics of Deep Learning 15: Summary |
| Prerequisites |
|
- Programming experience in C, Java, Python (of course), etc. - In addition to 30 hours that students spend in the class, students are recommended to prepare for and revise the lectures, spending the standard amount of time as specified by the University. |
| Required Text(s) and Materials |
| Digital documents are distributed in the lecture. |
| References |
| Assigned as appropriate, when necessary |
| Assessment/Grading |
|
- Weekly exercise (40%) to confirm the level of understanding - Final project (60%). |
| Message from instructor(s) |
| Learn the basics of data science and use it for your research. |
| Course keywords |
| Office hours |
| Ask questions at any time by email. |
| Remarks 1 |
| Remarks 2 |
| Related URL |
| Lecture Language |
| English |
| Language Subject |
| Last update |
| 6/16/2020 10:34:10 PM |