Introduction to Data Analytics with Python

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.

This course is designed for anyone interested in pursuing a career in data analytics. It will be particularly useful for data analysts looking to add an additional tool to their data analytics repertoire.

This course is designed for anyone interested in pursuing a career in data analytics. It will be particularly useful for data analysts looking to add an additional tool to their data analytics repertoire.

• Apply the basic elements of the Python language for data analytics.
• Apply advanced data operations using the Python package: Pandas.
• Demonstrate data ingestion and data wrangling operations in Pandas.
• Develop, enhance, and customise data visualisations using the Python plotting library: Seaborn.