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Python for Data Science

Course Reference No: CRS-N-0046392

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 Scikit-learn and Keras.

This programme introduces basic Python programming and community best practices such as using Jupyter/Python. The programme then moves on to show how Python can be applied to data mining, analytics, data science and artificial intelligence projects. At the end of this programme, participants will gain an overview of the Python ecosystem as well as the skills necessary to self-learn and continue on their Python learning journey.  

At the end of the programme, participants will be able to:
• Use Python for basic data munging to aggregate, clean and process data from local files, databases,    and online.
• Create visualization 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, analyze them, learn from   them, visualize them, and share them.

Outline
Day 1
1. Python Basics (I): Python Environments    
    a. Python statement and operation 
    b. Variable Assignment
    c. Functions and Classes

2. Python Basics (II)    
    a. Lists and Dictionaries 
    b. Conditional and looping statement
    c. File Input/Output
    d. Managing Python Environments and Packages

3. Working with Data Sources    
    a. Reading CSV 
    b. Web Scraping
    c. Interacting with local and remote databases (ODBC)
    d. Reading from HTML

4. Mini-Project: Making a Data Product with Python and Jupyter

Day 2
1. Data Exploration and Wrangling    
    a. Series/Data frame 
    b. Data cleaning
    c. Data analytics e.g., Descriptive statistics using Python

2. Data Visualization with the matplotlib    
    a. Basic visualization technique 
    b. Creating visualization tools using matplotlib

3. Introduction to key Data Science    
    a. Data analytics process: Supervised and Unsupervised Learning 
    b. Regression and Classification using Sci-kit Learn

4. Mini-Project (and/or) Recap: Creating data visualization and data analytics product


Tools
Jupyter, Python.

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

Who Should Attend
Business Analysts, Data Analysts, Software Engineers, Programmers 

Mode of Training
Classroom

Python for Data Science

Date

07 - 08 Mar 2019

Duration

2 Days
9.00am to 5.30pm
(Daily)

Venue

National University of Singapore
University Town

International Participants




S$ 1605.00

  • Incl. GST

Singapore Citizens
(39 yrs old or younger) 
or Singapore PRs


S$ 481.50

  • Incl. GST

Singapore Citizens
(40 yrs or older)




S$ 181.50

  • Incl. GST

Enchanced Training Support for SMEs




S$ 181.50

  • Incl. GST

Fees & Fundings

International 
Participant

Singapore Citizen1
39 years old or younger
Singapore Citizen1
40 years or older eligible for MCES2
Singapore
Citizen1 eligible
for WTS3
Singapore PRs

Enhanced Training
Support for SMEs4
Full Programme FeeS$1,500.00S$1,500.00S$1,500.00S$1,500.00S$1,500.00S$1,500.00
SkillsFuture Funding
Eligible for Claim Period
(19 Oct 2017 - 30 Sep 2020)
-(S$1,050.00)(S$1,050.00)(S$1,050.00)(S$1,050.00)(S$1,050.00)
Nett Programme FeeS$1,500.00S$450.00S$450.00S$450.00S$450.00S$450.00
7% GST on Nett
Programme Fee
S$105.00S$31.50S$31.50S$31.50S$31.50S$31.50
Total Nett Programme
Fee Payable, Incl. GST
S$1,605.00S$481.50S$481.50S$481.50S$481.50S$481.50
Less Additional Funding if
Eligible Under Various Scheme
--(S$300.00)(S$375.00)-(S$300.00)
Total Nett Programme Fee, Incl. GST,
after additional funding from the various funding schemes
S$1,605.00S$481.50S$181.50S$106.50S$481.50S$181.50

1 All self-sponsored Singaporeans aged 25 and above can use their $500 SkillsFuture Credit to pay for the programme. Visit http://www.skillsfuture.sg/credit to select the programme.
2 Mid-Career Enhanced Subsidy (MCES) - Singaporeans aged 40 and above may enjoy subsidies up to 90% of the programme fee.
3 Workfare Training Support (WTS) - Singaporeans aged 35 and above (13 years and above for persons With disabilities) and earn not more than S$2,000 per month, may enjoy subsidies up to 95% of the programme fee.
4 Enhanced Training Support for SMEs (ETSS) - SME-sponsored employees (Singaporean Citizens and PRs) may enjoy subsidies up to 90% of the programme fee. For more information, visit http://www.ssg.gov.sg/programmes-and-initiatives/training/enhanced-training-support-for-smes.html?_ga=2.154478072.1748789781.1519700056-512306731.1519700056
5 Eligible organisations (excluding government entities) may apply for the absentee payroll funding via SkillsConnect at www.skillsconnect.gov.sg for Singaporean/permanent resident participants attending the programme during working hours. The absentee payroll funding is computed at 80% of hourly basic salary capped at $4.50 per hour or $7.50 per hour for SME or 95% of hourly basic salary for WTS. For more information, visit https://www.skillsconnect.gov.sg/sop/portal/e-Services/For%20Employers/AbsenteePayroll.jsp

Ver: 88160119

Registration will close 5 working days prior to programme commencement date