• Python basic: data structures, list and dictionary, programming logics, define function
• Introduction to Pandas: Series / DataFrame
• Data Visualization Techniques
• Practical use of Pandas features: data aggregation / joining / datetime management
• Different types of charts

Module 2: Web Scraping with Python

• Use of BeautifulSoup and Selenium

Module 3: Overview of the Use of Machine Learning

• Supervised learning / unsupervised learning
• Model evaluation
• Data mining workflow

Module 4: Tree Based Machine Learning Algorithms

• Decision tree algorithm / random forest
  　

Module 5: Artificial Neural Network (ANN) & Deep Learning

• ANN and DNN with Tensorflow
  
  　

Module 6: Clustering Algorithms

• Kmeans and other algorithms

Module 7: Regression

• Linear and polynomial regression techniques
  
  　

Module 8: Use of Gen AI
　

• Common use cases of Gen AI
  
  　

Module 9: Final Assessment
　

• Final Assessment

This programme requires the participants to perform practical workshops and final assessment to assess their ability.

The practical workshops are continuous assessments (CA).

The final assessment (FA) is to be conducted at the end of the programme.

The overall contributions to the final results are 60% for Continuous Assessments and 40% for Final Assessment.

Certificate in Data Science with Python will be awarded to those who have:

1. Complete all assessment tasks; and

2. Obtain a total of 50% or above in continuous assessment(s); and

3. Obtain 50% of above in final assessment; and

4. Attend at least 70% of the total contact hours.

Admission Requirements

Applicants should submit the document(s) as proof of fulfilling the following admission requirements:

1) Completion of Form 5 (under the HKCEE academic structure); or Completion of Secondary 6 (under the HKDSE academic structure); or Equivalent qualifications; or

2) Aged 18 or above at the time when the course commenced with basic computer knowledge.