Data Analysis And Visualization in Sichuan

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Data Analysis And Visualization

Mianyang , Sichuan , China |

Part-Time / Offline Teaching

6000-8000 USD / Per Course

Air Ticket Visa Provided Commercial MedicalInsurance Accommodation Provided

Basic Info

Course Name: Data Analysis and Visualization

Students: Undergraduate Students

Class Size: 80-100 students

Location: A public university in Mianyang City, Sichuan China

Teaching Period: 8 Weeks -10 Weeks

Contract: One Semester

Course Description

This course is designed for master's degree students in artificial intelligence, focusing on data-driven insight extraction and visual expression. The course takes the Python ecosystem as its core, systematically explaining the fundamentals of data processing such as data cleaning, feature transformation, statistical inference, and multi-dimensional analysis, and deeply dissecting key methods like comparative analysis, correlation mining, and time series trend modeling. The visualization section covers tools such as Matplotlib, Seaborn, Plotly and Tableau, with a focus on training the design and implementation of static publishing-level charts, interactive dashboards and high-dimensional data dimensionality reduction visualization (PCA/t-SNE). Combining real cases such as financial risk control, bioinformatics, and large model evaluation logs, it emphasizes extracting effective features from disordered data and discovering hidden patterns through visualization methods to support algorithm selection and model diagnosis, providing solid data understanding and presentation capabilities for the entire AI modeling process.

Job Highlights

1. Visa application fee reimbursement

2. Free round trip air tickets

3. Free accommodation

4. Medical Insurance

Job Responsibilities

1. Make a curriculum plan according to the requirements of the university, prepare lesson plans carefully, teach flexibly, and accomplish teaching tasks and goals efficiently;

2. Submit teaching documents regularly according to university's requirements based on the teaching progress, including course notes, slides, classroom exercises, and homework;

3. According to the university’s exam regulations, submit exam papers on time and assist the university in completing invigilation, grading, timely complete student grade registration and feedback reports.