NUS Institute of Systems Science

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About the course

Python is a fun, flexible and expressive scripting language that can automate repetitive process and tasks, evaluate performance of your servers, and even interact with your IoT devices. Python can also be used to handle data such as crawling, scraping, cleaning and processing your data from webpages external APIs, or other sources for mining and manipulation.

By the end of the course, you'll have the basic capability in using Python for simple data transformation and analysis. The course is hands-on; spotted with many case studies in what you need to do to solve problems including your very own real-world challenge. Rather than covering the entire Python language, this course is designed to firm your foundation – to ready you to the world of backend development that involves data, algorithms, server management, administration and machine learning and interaction.

This course is part of the StackUp - Startup Tech Talent Development programme offered by NUS-ISS.

Key Takeaways

At the end of the course, you will be able to:

  • Apply basic Python syntax
  • Use Python to automate your daily operational work
  • Use Python to evaluate server performance (i.e., processes, file system)
  • Plan and implement Python code to collect structured data from API
  • Use Python to process and organize unstructured data in website scraping
  • Apply Python for data analysis
  • Apply Python to do simple data transformation

What Will Be Covered

  • How to run Python codes (virtual environment, Jupyter Notebook)
  • Basic data structures, math operation, String
  • Basic Python data structures
  • Function in Python
  • Advanced python concepts
  • Overview of Linux operating system: Concepts of file system, process and how they work together in the operating system
  • File system concepts
  • File searching in Python
  • Process concepts
  • Process monitoring using Python
  • Networking concepts
  • Port scanner using Python
  • Introduction to Secure Shell Access (SSH)
  • Log file processing on remote server using Python
  • Introduction to API & example of API documentation
  • Data Collection via REST API using request & json library
  • Introduction to HTML for web scraping
  • Web scraping using scrapy
  • Data Analysis in Python with Pandas
  • Python coding practices: Pandas
  • Data visualization using Bokeh, Matplotlib
  • Python coding practices: visualization
  • Data Analysis in Python: numpy & scipy
  • Python coding practices: numpy, scipy
  • Python for Things - IoT
  • MQTT
  • Full data processing pipeline & visualization


Lectures, quizes and assesments

Who should attend

This course is designed for:

  • Data/Business/Financial Analyst
  • Data Analytic/Data Science Professional
  • Hardware/Data/Systems/IoT Engineers
  • Systems Administrator
  • Managers, Engineers, Designers, Accountants, Lawyers, Healthcare Professionals
  • Other professionals with disciplines from many background

What to Bring

  • Please bring along your laptop during the training.
  • Specs: 8 GB RAM minimum
  • 16 GB RAM recommended
  • 64 GB storage 1280x1024 minimum screen resolution
  • Windows 10 or Later/Mac OSX 10.10 or Later (64-Bit OS Required)

Trust the experts

Prasanna Veerapandi

Associate Lecturer & Consultant, Software Systems Practice


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