Python is a very versatile programming language, broad in its application due to its simplicity and power. While Python can be used for everything from developing websites to programming robots, our courses focus on using Python for data analytics.

Our Python Beginner course focuses on the fundamentals of working with Python for Data Analysis. We introduce Anaconda, JupyterLab, and the basics of Python syntax. You will learn how to work with objects in Python, access and manipulate dataframes, how to use functions and methods, and create basic visualisations.

By the end of the course, you will be able to:

  • Set up and manage Anaconda environments, including installing packages
  • Use JupyterLab and Jupyter Notebooks for coding and documentation
  • Create and work with Python objects, functions, and methods
  • Build simple data visualisations and write basic markdown files

Prerequisite:

No prior experience with Python is required. This course is designed for complete beginners who have never used Python before.

Course Details

Download Course PDF
Price
SG$655
Duration
1 day
Times
9am-4pm
Class Size (max)
10
Class Size (avg)
5
Reference Materials
Provided
CPD Hours
6 hours
Delivery
Instructor-led training
Live Online
Address
N/A

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Python Beginner
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Python Training Courses

Course Icon Python Intermediate

Boost your skills with our intermediate Python course. Learn data manipulation, build custom Python functions, and create visualisations with Matplotlib and Seaborn.

download course pdf
Price: SG$655
Course Icon Python Advanced

Advance your data skills with our Python advanced course. Automate analysis, write efficient Python code, and build interactive dashboards using pandas and Bokeh.

download course pdf
Price: SG$655

Python Beginner Course Content

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Introduction

Introduction to Python

Introduction to Anaconda and JupyterLab

The Python Standard Library

Installing Python

Anaconda

JupyterLab

Installing additional packages

Anaconda and JupyterLab

Using Anaconda

Working with environments

Launching JupyterLab

Working in JupyterLab

Using Jupyter Notebooks

Basics of running code

Markdown

Shutting down kernels and the Jupyter Server

Using Python as a Calculator

Arithmetic operators

Relational operators

Logical operators

The Python Standard Library

Built-in functions

Other functions in the standard library

Working with Objects

Objects in Python

What are objects?

Creating variables

Naming rules

Naming conventions for variables

Data Types and Structures

Built-in data types

Built-in data structures

Tuples, lists, ranges and dictionaries

Pandas Series and DataFrames

Which data structure should I use?

Pandas DataFrame

Attributes

Methods

Pandas functions

Creating DataFrames

Importing data into a DataFrame

Uploading data in JupyterLab

Accessing data within DataFrames

Accessing specific rows

Accessing specific columns

Accessing data subsets by name or position

Manipulating DataFrames

Making changes in place

Renaming columns and rows

Replace a single value

Replace multiple values

Add data to a DataFrame

Remove rows or columns

Filter based on condition

Sort data

Working with data in DataFrames

Calculating summary statistics

Evaluation in Python

Order of operations

Evaluation with Numpy

Vectorised arithmetic

Vectorised functions

Broadcasting

Creating new columns with vectorised arithmetic and functions

Functions vs Methods

What is a function?

Syntax for using functions in Python

Syntax for using methods in Python

Parameters and arguments

Getting help with a function

Overview of help documentation

Exporting Data

Export data to csv file

Basic Data Visualisation

Matplotlib

Create a scatterplot

Create a linechart

Add text

Add a legend

Exporting plots

Notebook to Markdown

View your completed Notebook as a rendered Markdown file

Frequently Asked Questions

Course Introduction

Our Python courses were designed by Tamara Shatar, who holds a PhD in Agricultural Data Science. She focused her extensive experience and skills in modelling using machine learning, simulation and other techniques to create a course with depth and applicability.

The course is consistently well-reviewed by students.

"Very well presented and structured. Thank you for such a fruitful day." – Python Beginner, Sydney

What is Python used for?

Python is a versatile programming language used across data analysis, automation, artificial intelligence, web development, and more. In this course, you’ll learn how to use Python for working with data, creating basic visualisations, and simplifying repetitive tasks.

Is this course suitable for beginners?

Yes. This course is designed for complete beginners. No prior programming knowledge is required. We’ll start with the basics and guide you through setup, coding in Python, using Anaconda, and working with Jupyter Notebooks.

What tools will I learn to use?

You’ll learn to work in Anaconda and JupyterLab—industry-standard tools for data science. These platforms let you write, test, and document your code in one place. You’ll also gain hands-on experience using pandas, NumPy, and Matplotlib libraries.

What’s the difference between a function and a method in Python?

Functions and methods are both used to perform actions, but they differ in syntax and use. Functions stand alone, while methods are tied to objects like lists or DataFrames. You'll explore how to use both, and how to get help through built-in documentation.

Will I learn how to work with data?

Absolutely. You’ll learn how to create, import, and manipulate data using pandas DataFrames. You’ll practise filtering, sorting, renaming columns, calculating summary statistics, and exporting results.

What is Markdown and how is it used?

Markdown is a lightweight markup language used to format text in Jupyter Notebooks. You’ll use it to document your work, add headings, bullet points, and explanations to your code, making your notebooks clearer and more professional.

Do I need to install Python before the course?

No. The course will walk you through installing Anaconda, which includes Python and all the packages you need. We’ll help you set up everything during the session, whether you're learning in person or remotely.

What is Remote Training?

Remote training at Nexacu means our team of experienced trainers will deliver your training live online. With remote learning, students can access our usual classroom training courses via video conferencing, ask questions, participate in the discussion, and share their screen with the trainer if they need help at any point. Students have the same level of participation and access to the trainer as they would in classroom training sessions.

Course Details

Download Course PDF
Price
SG$655
Duration
1 day
Times
9am-4pm
Class Size (max)
10
Class Size (avg)
5
Reference Materials
Provided
CPD Hours
6 hours
Delivery
Instructor-led training
Live Online
Address
N/A

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Find the nearest location and date that works for you

Related Training Courses

Course Icon Python Intermediate

Boost your skills with our intermediate Python course. Learn data manipulation, build custom Python functions, and create visualisations with Matplotlib and Seaborn.

download course pdf
Price: SG$655
Course Icon Python Advanced

Advance your data skills with our Python advanced course. Automate analysis, write efficient Python code, and build interactive dashboards using pandas and Bokeh.

download course pdf
Price: SG$655

Locations In-Person & Online

Find the nearest location and date that works for you

Locations In-Person & Online

Find the nearest location and date that works for you

Trusted Globally by Leading Organisations

At Nexacu, we are proud to be the trusted training partner for hundreds of leading organisations across Australia, New Zealand, and around the world. From government agencies to multinational corporations, we help teams build practical skills and achieve real outcomes through expert-led training.

  • 400+ companies rely on Nexacu for workforce development
  • Trusted by government agencies at all levels
  • Delivering training across 9 countries and growing

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