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.

  • 3rd week of July, 2019
  • 6 sessions
  • 2.5 hours/session
  • Data Science
Data Science Introduction (Python)
U.P. $2,000
$600

Price before GST

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.

Objectives

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.

Course Plan

Students will be taught how to use Python to do file processing, including reading in tabular (CSV, Excel) data.
We will be covering basic statistics knowledge, such as mean medium, mode, and looking at doing regression models.
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.
For this lesson, we will be looking at how websites build recommendation services. e.g. Amazon's "You might also be interested in purchasing ...".

We will be working on a movie database and learning how to use collaborative filtering to make recommendations. At the end of the class, we will be able to correctly recommend movies based on their ratings.

For example, when a user rates "Star Wars: A New Hope" 10/10, our code will be able to recommend "Star Wars: The Empire Strikes Back".
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.
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.

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.
Active Course Runs

Lesson Dates/Timings

  • July 17, 20191930 - 2200 hrs
  • July 20, 20190930 - 1200 hrs
  • July 24, 20191930 - 2200 hrs
  • July 27, 20190930 - 1200 hrs
  • July 31, 20191930 - 2200 hrs
  • August 03, 20190930 - 1200 hrs
  • one-north

    Blk 81 Ayer Rajah Crescent #02-67 S139967

    Instructor

    ZP


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