Python Data Analysis and Decision Making Bootcamp
This camp allows participants to experience data analysis and decision-making using Python. Even if you have no prior experience with Python, you can learn it comfortably in this camp.
Our instructors will guide students through the basics of Python, starting with basic syntax, and then lead them through more complex data analysis operations in a hands-on setting.
At the end of the camp, students will be required to complete a knowledge assessment to demonstrate their knowledge mastery.
(Course Target Audience:
People who have frequent contact with data and have basic concepts and understanding of data analysis and are interested in strengthening their data visualization, analysis and decision-making skills.
Target group:
People who need to work with data or who want to join or want to join the data analysis industry
Duration: 40 hours
Teaching method: Classroom, demonstration and practice
Requirements for the certificate:
Students must meet the following graduation requirements in order to receive a certificate of completion.
(i) the total attendance must meet the minimum requirement (80%) of the course; and
(ii) must receive an overall passing grade on the course evaluation; and
(iii) must receive a passing grade on the final examination.
Course contents are shown as below:
1. Python basic grammar and application training (10 hrs)
a. Python Basic Grammar
b. Use advanced Python to process table formatting
c. Extract data from API via Python
2. Data analysis and decision-making training (28 hrs)
a. The nature of data and its application
b. Using basic tools to explore and describe data
c. Use visualization tools
d. Understanding and Interpreting Data
e. Presentation of latest data analysis
f. Development of key concepts of data and data analysis
g. Data analysis and modeling
h. Visualization and presentation of data insights
3. Assessment- final Exam (2 hrs))
40
English
Learning Outcomes
1. Master the basic syntax and applications of Python
2. Understand how to visualize data and interpret data
3. Master the use of images to analyze data
4. Master the collection and organization of information from multiple sources, such as the extraction of data from the application interface through Python
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