Do you want to make your organisation’s data more valuable? The first step is organising and structuring it for analysis. Data analysts need to use databases and other technologies to efficiently collect, organise and manipulate this data.
This course will help you learn how to confidently use the Python programming language to analyse data and conduct data modelling.
Familiarise yourself with data analytics techniques
You’ll compare data analytics and advanced data analytics, and discuss the fundamentals of statistics and its application in data analytics.
You’ll learn a range of different techniques that will enable you to manipulate data in different ways, and adjust your approach to suit the subject, circumstances, and time you have available.
Learn new Python functions
You’ll also use Python to support data wrangling and ingestion, and learn advanced data analysis techniques including data mining and machine learning.
As you solidify your new knowledge by reviewing real-world examples and theories, you’ll develop critical employability skills and a foundational knowledge in Python to set yourself apart from other candidates when applying for jobs across a range of industries.
Boost your career with data analytics skills
This course will further any prior understanding you have of working with data and analytics, and you’ll be able to add Python skills to your CV.
Upon completion of the full ExpertTrack, you’ll have the knowledge and confidence you need to apply your skills in a real-world professional setting.
This course is suitable for:
- business analysts or junior data analysts looking to develop their advanced data analytics skills and programming capabilities to achieve career progression within data analytics
- those with existing programming capabilities looking to start a career in data analytics
- those lacking the programming capabilities to conduct more advanced data analysis and modelling
During the course we’ll be using Jupyter notebook. We recommend you use a computer to access these elements.
