Want to learn Python but not sure how and where to start? Try DataCamp!

Knowledge of data science and analytics has become increasingly useful for all graduates entering the 21st-century workforce in all subject disciplines. Data-driven approach to support decision making has become more crucial than ever in every industry. As a student, it is important to equip yourself with the skills to confidently work effectively and efficiently with data.

The Library has recently subscribed to DataCamp*, an online learning platform that allows you to acquire data science, data analytics and data visualisation skills with various technologies, such as R, Python and SQL, at your own pace.

Here are some typical data science topics that may be of interest to you:

• Data Collection

  Learn how to efficiently import data from various resources. In the digital age, web scraping is getting more popular for collecting large-scale data and manually extracting data from websites can help save your time and cost. Courses in DataCamp like Web Scraping in R and Web Scraping in Python are a perfect place to start.

• Data Manipulation

  Primarily for data preparation, data manipulation can help you retrieve data from other sources and organise raw data into tidy datasets so that it is ready for analysis. Learn the skills through Regular Expression in Python, Joining Data with pandas in Python, and Joining Data in SQL.

• Data Cleaning

  Learn about data cleaning, another important process for data preparation which can help you handle missing and inconsistent data to improve the accuracy of your analysis, for example, Cleaning Data in Python and Cleaning Data in PostgreSQL Databases.

• Data Analysis

  Learn how to use different hypothesis tests to help you analyse and find interesting trends, patterns, and relationships in the datasets, for example, Correlation and Regression in R and Network Analysis in the Tidyverse in R.

• Machine Learning

  Apply different machine learning algorithms to help you create learning models for making prediction or recommendations based on the datasets. Take the courses Cluster Analysis in Python and Machine Learning with Tree-Based Models in Python to understand more about machine learning algorithms.

• Data Visualisation

  To make trends and patterns in data easier to understand and to help present your data or findings effectively, learn about data visualisation and how to create your own via Introduction to Tableau, Introduction to Power BI, and Introduction to Data Visualization with Plotly in Python.

DataCamp has also provided a wide range of resources, such as tutorials, cheat sheets and podcast, for you to learn more about data science.

Register here to access the full contents of DataCamp!

For PolyU staff teaching data courses, you can consider using the materials from DataCamp to supplement your teaching courses. Do check with your Faculty Librarian for more information.

Should you have any queries about accessing DataCamp, email us at lbres@polyu.edu.hk, or call us at 2766-6863 during the library opening hours.

*For PolyU students and staff only