Python Beginner

Length 1 day

Course overview

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Why study this course

Python is a very versatile programming language, broad in its application due to its simplicity and power. While it can be used for automation, artificial intelligence, web development, and more, this series of courses focuses on using Python for data analysis. You'll learn to manipulate, analyse, and visualise data more effectively with Python and related tools and libraries.

The Python Beginner course focuses on the fundamentals of working with Python for data analysis. You'll be introduced to Anaconda, JupyterLab, and the basics of Python syntax. You'll learn how to work with objects in Python, access and manipulate dataframes, how to use functions and methods, and create basic visualisations. You’ll also gain hands-on experience using pandas, NumPy, and Matplotlib libraries.

Nexacu Public Schedule

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What you’ll learn

After completing this course, students 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
Write basic markdown files

Python at Lumify Work

Lumify Work's Python offering has been refreshed to include courses which fully align to certifications from the Python Institute. Our courses are delivered by Python programming experts who can structure their topic flow to your goals and functions, whether it's Python for automation or for data science or for finance.

View all Python at Lumify Work courses

Who is the course for?

This course is designed for complete beginners who have never used Python before.

Course subjects

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
Accessing help
Autocomplete
Basics of running code
Markdown
Shutting down kernels and the Jupyter Server

Using Python as a Calculator

Arithmetic operators
Relational operators
Logical operators
Order of operations

The Python Standard Library

Built-in functions
Other functions in the standard library

Functions vs Methods

Basic syntax for functions
Basic syntax for methods
Arguments

Working with Objects

Objects in Python
What are objects?
Creating objects
Naming rules
Naming conventions
Names as references
Namespaces
Using dir() to list objects, attributes, and methods

Data Types and Structures in Python

Data types
Conversion between data types
Built-in data structures
Tuples, lists, ranges, and dictionaries
Conversion between data structures
Referring to data by position
Slicing
Strings
Referring to data by name
Which data structure should I use?

pandas Data Structures

Creating Series and DataFrames
Importing data into a DataFrame
Uploading data in JupyterLab
Referring to data by name
Accessing data from Series
Accessing data from DataFrames
Accessing data that meet specific criteria
Making changes in place
Renaming columns and rows

Manipulating Objects

Replace parts of an object
Add data to an object
Remove data from a data object

Supplementary Contents

Vectorised computation with pandas and NumPy
Vectorised arithmetic
NumPy
Vectorised methods and functions
Broadcasting

Working with Data in DataFrames

Calculating summary statistics

Plotting Data

Plotting with Matplotlib
Creating a scatterplot
Creating a linechart
Adding text
Adding a legend
Exporting plots

Exporting Data

Export data to csv file

Notebook to Markdown

View your Notebook as a rendered Markdown file

Prerequisites

No prior experience with Python is required.

Terms & Conditions

The supply of this course by Lumify Work is governed by the booking terms and conditions. Please read the terms and conditions carefully before enrolling in this course, as enrolment in the course is conditional on acceptance of these terms and conditions.