Course Code: CPD0316/2026
Category
GPM: General and Professional Matters
H&S: Health and Safety including Occupational Safety and Health
OTM: Environment, Information Technology, Quality and Other Technical Matters not directly related to a Trainee's own discipline
Course Name
Applied Data Science with Python
Category
GPM
Date
1 - 31 March 2026
Time
Total 45+ hours (5+ hours Self-paced Learning video; 40 hours Live Virtual Classes)
Organized by
PTI Professional Development Limited
Venue
Online
Fee
Free Trial Course (4 days)
Introduction
This course provides comprehensive understanding of data science essentials, including data preparation, model building, & evaluation. Participants will learn concepts like strings, Lambda functions, and lists.
Learners will also explore topics like NumPy, linear algebra, & statistical concepts, including measures of central tendency and dispersion, skewness, covariance, and correlation.
This Course also covers hypothesis testing, such as Z-test, T-test, and ANOVA, and data manipulation using pandas. Participants will develop data visualization skills using popular libraries like Matplotlib, Seaborn, Plotly, and Bokeh.
Objectives
- Explain fundamentals of data science & practical applications.
- Explore processes of data preparation, model building, and evaluation.
- Apply Python concepts like strings and comprehensively understand Lambda functions and lists.
- Develop solid understanding of fundamentals of NumPy.
- Explore array indexing and slicing techniques.
- Apply principles of linear algebra in data analysis.
- Understand the application of calculus in linear algebra.
- Calculate measures of central tendency and dispersion
- Gain clear understanding of statistical concepts Describe null hypothesis and alternative hypothesis.
- Examine different hypothesis tests, including Z-test and T-test.
- Understand concept of ANOVA.
- Work with pandas’ two primary data structures: Series and DataFrame. Utilize pandas for tasks such as data loading, indexing, reindexing, and data merging.
- Prepare, format, normalize, and standardize data using data binning techniques.
- Create visualizations with Matplotlib, Seaborn, Plotly, and Bokeh.
Contents
- Introduction to Data Science
- Essentials of Python Programming
- NumPy
- Linear Algebra
- Statistics Fundamentals
- Probability Distributions
- Advanced Statistics
- Working with pandas
- Data Analysis
- Data Wrangling
- Data Visualization End-to-End Statistics Applications in Python
Language
English
Remarks
- Complimentary coupon of HKD200 - Can be deducted from fees for next enrolment for courses with NET fees (after discount) of HKD3,000 or above (one year validity from date of purchase)
- One year access to Learning Management System (LMS) from date of activation of LMS.
- Recordings of registered LVCs available post-class, during access period to LMS
- Different batches of Live Virtual Classes (LVCs) available, learners can choose the batch convenient to them.
- Subject to T & Cs , as updated from time to time
Registration
Enquiry