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Python For Data Science

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Apply Python as a data science tool for programming and business analysis. Learn the best practices of data mining and analytics with this course in Singapore.

Date

  • 21 Oct, 22 Oct 2021 (9am – 5.30pm)
  • 29 Nov, 30 Nov 2021 (9am – 5.30pm)

Duration

 2 Days

Overview

In an age where data is ubiquitous, it is critical to be well-versed in tools that will allow us to extract useful insights, decisions and products from the data that we collect. Python, with its wide array of libraries streamlining each part of the data science process, is an essential part of our quantitative toolkit. Building upon a review of basic Python syntax, this course focuses on how we can better work with, and make use of, data using Python, from cleaning messy datasets, exploring our data by way of visualisations, and setting up machine learning models. It should also be mentioned that Python is the no 1 programing language for DS.

Course Objectives

New libraries for data manipulation, visualization and data modeling have made Python an increasingly exciting alternative to R as a data science language.
This programme aims to quickly bring up to speed a programmer or business analyst who already knows how to programme in Python to begin using Python as a data science tool.
The programme will define data science and explore the first two things a data scientist must do – cleaning and visualizing data. It will then cover the Data Science Workflow – training models and testing them through the application of machine learning models to various industry-relevant data science problems. The tools used will be including but not limited to Pandas, Scikit-learn and Keras.

Learning Outcomes

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

  • Use Python for basic data munging to aggregate, clean and process data from local files, databases, and online
  • Create visualisation with Matplotlib, Pandas.plot, and Seaborn
  • Create basic to intermediate analytics models with Python/Sckit-learn
  • Using the above tools within the context of solving essential data science problems
  • Applying Python tools to import data from various sources, explore them, analyse them, learn from them, visualise them, and share them

Topics

  • Python Basics (I): Python Environments
    • Python statement and operation
    • Variable Assignment
    • Functions and Classes
  • Python Basics (II)
    • Lists and Dictionaries
    • Conditional and looping statement
    • File Input/Output
    • Managing Python Environments and Packages
  • Working with Data Sources
    • Reading CSV
    • Web Scraping
    • Interacting with local and remote databases (ODBC)
    • Reading from HTML
  • Mini-Project: Making a Data Product with Python and Jupyter
  • Data Exploration and Wrangling
    • Series/Data frame
    • Data cleaning
    • Data analytics e.g., Descriptive statistics using Python
  • Data Visualization with the matplotlib
    • Basic visualization technique
    • Creating visualization tools using matplotlib
  • Introduction to key Data Science
    • Data analytics process: Supervised and Unsupervised Learning
    • Regression and Classification using Sci-kit Learn
  • Mini-Project (and/or) Recap: Creating data visualization and data analytics product

Who Should Attend

Business/Data Analysts, Programmers, Executives

Prerequisites

Must be familiar with the Python programming language, or have attended the Introduction to Python training and statistics 101 at a pre-university level.

Course Fees

Singapore Citizens Singapore PRs Enhanced Training Support for SMEs International Participants
39 years old or younger 40 years old or older
Total Nett Programme Fee Payable, Including GST, after additional funding from the various funding schemes S$609.90 S$229.90 S$609.90 S$229.90 S$2,033.00

To enquire, email soc-ace@nus.edu.sg

To register, click Register

For members of public and NUS Alumnus (without R&G Voucher), please follow the steps below:

Select Short Course / Modular Course -> Apply for Myself -> Browse Academic Modules / Short Courses-> Module/Course Category -> Short Courses -> Browse Courses-> Strategic Tech Mgt Institute (Faculty/Department / Unit)

Please download the user guide for NUS Online Application Portal after you click ‘Apply for Myself’ if you need assistance.

Instructor

(Click their names to view their short biographies)

Dr Amirhassan Monajemi

Dr Edmund Low

Assoc Prof Danny Poo

*Course Fee breakdown

Singapore Citizens Singapore PRs Enhanced Training Support for SMEs International Participants
39 years old or younger 40 years old or older
Full Programme Fee S$1,900.00 S$1,900.00 S$1,900.00 S$1,900.00 S$1,900.00
Less: SSG Grant Amount (S$1,330.00) (S$1,330.00) (S$1,330.00) (S$1,330.00)
Nett Programme Fee S$570.00 S$570.00 S$570.00 S$570.00 S$1,900.00
7% GST on Nett Programme Fee S$39.90 S$39.90 S$39.90 S$39.90 S$133.00
Total Nett Programme Fee Payable, Including GST S$609.90 S$609.90 S$609.90 S$609.90 S$2,033.00
Less Additional Funding if Eligible Under Various Schemes (S$380.00) (S$380.00)
Total Nett Programme Fee Payable, Including GST, after additional funding from the various funding schemes S$609.90 S$229.90 S$609.90 S$229.90 S$2,033.00