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Introduction to Data Analytics with Python

Learn the fundamentals of using Python for data analysis and develop skills in two of Python’s core libraries, Pandas and Seaborn with this online Python programming course.

Duration

4 weeks

Weekly study

3 hours

100% online

How it works

Unlimited subscription

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Build your data analytics toolkit with Python

We are in the era of ‘big data’. According to a Forbes article published in 2018, around 2.5 quintillion bytes of data were being generated each day globally.

On this four-week course, created in collaboration with Tableau, you’ll gain a foundational knowledge of data science for business applications, acting as a launchpad to help you become a successful data scientist.

Discover the business value of data science

Traditionally, data was collected from a single source in a standard format, classed as ‘structured’ data. But with data now being collected from various sources in different forms, known as unstructured data, data scientists are becoming increasingly in demand.

This course will show you the value of data science to any business, from data security to predicting market trends. You’ll also delve into the data science life cycle and how to identify and frame business needs to solve problems.

Explore the scientific approach to data science

Data science is a multidisciplinary domain that uses scientific methods, processes, algorithms, and systems to draw knowledge and insights from unstructured data.

During the second week, you’ll dive deeper into solving business problems with data. You’ll learn how to design a structured thinking problem, build a hypothesis, and then test it all to discover a solution to a business need.

Learn to use spreadsheets for data analysis and visualisation

The second half of this course will introduce you to data analysis, data visualisation, and using Excel to perform and display your analysis.

You’ll explore the different functions of Excel and how to create formulas and build charts. You’ll then learn the communication frameworks to help you communicate your insights to stakeholders in a concise and engaging way.

Week 1
Basics of Python programming
- Welcome to the course
  Before we dive deep into understanding Python and its data science applications, let’s understand how this short course is designed. Understanding the course design will clarify what you can expect and what is expected from you.
- Leveraging Python for advanced data analytics
  Are you curious to learn how Python supports data analytics? This week, you'll answer this and get an overview of advanced data analytics, its future, and the role of data analysts and programming languages in this field.
- Setting up for Python programming
  In this section, you will learn how to set up a Python environment on your device and acquaint yourself with the building blocks of Python to begin your programming journey.
- Data structures in Python
  You are now ready to learn about some advanced concepts and features of the Python language. These concepts and features will serve as the foundational blocks of actual Python programs.
Week 2
Python library: Pandas
- Getting started with Pandas
  This week, you’ll learn about Python modules, packages, and libraries that will enable you to write well-organised and effective code for your data analysis projects.
- Data structures in Pandas
  How do Pandas Series and DataFrames help with data analysis? What are some essential data manipulation functions in Pandas, and how do you use them? Let’s find out the answers to these questions in the upcoming section.
- Advanced data operations in Pandas
  In this topic, let’s explore some of the advanced functionalities, such as reindexing, mapping, filtering, and selecting, utilised for cleaning and preparing the data for data analysis in Pandas Series and DataFrames.
Week 3
Data ingestion and wrangling using Python
- Introduction to data processing using Python
  Having gained a basic understanding of preparing and modifying data in Pandas data structures, the next question you could be asking yourself is how and where do you apply these skills?
- Data ingestion using Python
  Here, we will learn how to transport different forms of data from various sources into Python data structures for data processing in order to generate insights and conclusions.
- Data wrangling using Python
  It's now to learn how to use Python to perform various data processing activities. This phase of processing data is referred to as data wrangling.
- Reshaping data sets using Python
  Let us learn about the Python operations to reorganise the information into a single data set. Python houses functions for rearranging tabular data, known as reshaping or pivoting operations.
Week 4
Data visualisation using Python
- Fundamentals of data visualisation
  Here, you will learn the importance of data visualisation, its principles, and a human-centred approach to data visualisation that will empower you to tell captivating stories from your data analysis.
- Getting started with Seaborn
  You will now be introduced to Python’s data visualisation library, Seaborn. You will also learn to design scatter plots and box plots in Seaborn to visualise data effectively.
- Customising and enhancing charts in Seaborn
  Now, you will learn how to enhance and customise data visualisations in order to create effective and appealing visualisations and practise these skills through a practical activity.