Python for Data Analytics and Visualisation
- Full-time
- About
- Who Should Attend
- Pre-requisites
- Course Outline And Duration
- Exam Details
- Certification
- Course Fee
Understanding and analysing data is one of the key skills required in the industry today. This course is completely focused on the various aspects of data analytics using Python.
Participants will be taught about the key libraries for data ingestion and manipulation, exploratory data analysis, model building and data visualisation, as well as how to use them. In addition, they will be provided the basic statistics knowledge required to understand the concepts in the latter courses.
Those who want to learn data analytics using Python, such as students, working professionals and PMETs.
- Minimum age: 16 years old
- Knowledge of basic PC skills
- A basic proficiency in reading, writing and understanding English
- A basic understanding of Python. Participants who are unfamiliar with it are encouraged to take up Training Course 1: Basics of Python prior to this course.
Duration: 8 hours – 1 day
Consists of 5 modules:
Module 1: Understanding data
The module aims to teach students how to apply data from external sources into the Python environment and manipulate and analyse it. Before any data analytics project, it is very important to use statistical algorithms and methods to analyse data as part of the data analytics process.
Module 2: Data Wrangling
The module aims to teach students about how Python libraries can be leveraged to deal with data inconsistencies, issues with data and to make them fit for data analytics. This is where 80% of today’s data scientists and engineers spend their time and it is very important to know how to do it.
Module 3: Exploratory Data Analysis
The objective of this module is to understand how to use appropriate statistical methods and visualisations for descriptive analytics.
Module 4: Model Development for Analysis
This module guides the participants on the very first steps towards forming hypotheses and doing predictive analytics. It aims to equip participants with the basics of how supervised machine learning models work and how evaluation and optimisation can be carried out.
Module 5: Data Visualisation
The objective of this module is to understand basic metrics and KPIs (Key Performance Indicators) of different business cases and plotting advanced interactive visualisations for data analysis to gain insights from data.
No Exam
Certificate of Completion
Course Fee: S$481.50 (inclusive of GST)
