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Data Science Introduction (Python)

The course bridges the gap between programming and data science, focusing on the libraries for introducing data science, web development and basic statistics knowledge.

5

Created By : ZP

3rd Week of March, 2019

Part Time

6 weeks

2.5 h/session

Data Science Introduction (Python)

5 3rd Week of March, 2019 Part Time 6 weeks 2.5 h/session

What You'll Learn

A level up from our Python Development course, our Data Science Introduction (Python) course will teach students to build a simple yet functional web application. Working within the parameters set by the individual instructors, this fun project will see students building three web applications: a spam email classifier, taxi availability predictor and an air pollution index predictor.

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Course Plan

Lesson 1: Reading Reports in Python

Students will be taught how to use Python to do file processing, including reading in tabular (CSV, Excel) data.

Lesson 2: Basic Statistics Explained

We will be covering basic statistics knowledge, such as mean medium, mode, and looking at doing regression models.

Lesson 3: HTTP and Web Services

Digressing a little from statistics, we will look at how to build web servers using Python. This lesson will teach us simple HTML structures, that we can use for crawling and mining data on web pages.

Lesson 4: Web Scraping

Building off last week's lesson, you will learn how to write scripts which will allow you to mine web data by crawling HTML pages and using it to build a database of information.

Lesson 5: Generating and Visualising Data

We will look at how to use Python to visualise and present data in graphs and reports. We will also look at building realtime dashboards to measure data.

Lesson 6: Working with a Classifier Web Service

In the last lesson, we will combine all that we learnt so far to build a classifier web server. We will be using the web service to process data and make predictions.

Timetable

COHORT

March 16th, 2019
(6 weeks)
Location one-north
Lesson 1 16/03/19
09:30am - 12:00pm
Lesson 2 23/03/19
09:30am - 12:00pm
Lesson 3 30/03/19
09:30am - 12:00pm
Lesson 4 06/04/19
09:30am - 12:00pm
Lesson 5 13/04/19
09:30am - 12:00pm
Lesson 6 20/04/19
09:30am - 12:00pm

Prerequisites

This course requires a basic understanding of Python. You should either have sat and completed our Python Development Course or already have intermediate-level understanding of Python.

If you have not sat our Python Development course, a Student Affairs Officer will reach out to you upon registration to confirm your mastery of Python.

About this Course:

Our Data Science Introduction (Python) course serves as a starter for students looking to move on to Data Science I (Python). This course pays special attention to specialised Python libraries for data retrieval and visualisation techniques. Basic statistic knowledge will also be taught to help students understand the advanced concepts in Data Science I (Python).

As part of the course, students will also be taught key data libraries, namely Pandas, Numpy and Matplotlib; these libraries are responsible for data loading, mathematical computations and data visualisation respectively.

Students can also look forward to receiving course materials that will serve as useful reference for post-course revision and practice. At the end of the course, students will be taught the basics of web service development and will be equipped with the basic tools needed to start their career in data science.

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