Learning Unit
Data Analytics with Python
Part of Qualifi Level 3 Diploma in Data Science. Study this unit through structured learning outcomes, sequenced lessons, and AI-supported academic guidance.
Learning Outcomes
What learners will be able to demonstrate.
Gain the mathematical and statistical knowledge and understanding required to conduct basic data analysis.
Develop analytical and machine learning skills with Python.
Develop a strong understanding of data and data processes, including data cleaning, data structuring, and preparing data for analysis and visualisation.
Understand the data science landscape and ecosystem, including relational databases, graph databases, programming languages such as Python, visualisation tools, and other analytical tools.
Understand the machine learning processes, understanding which algorithms to apply to different problems, and the steps required build, test and verify a model.
Develop an understanding of contemporary and emerging areas of data science, and how they can be applied to modern challenges.
Assessment & Certificate
Complete the unit assessment.
When you are ready, take the unit assessment. If you pass, your verified Oxbridge Pathways certificate will become available immediately.
Take Unit AssessmentAI Lessons
Study in sequence, one lesson at a time.
Orientation to Data Analytics with Python
By the end of this lesson, learners will be able to engage with 'Gain the mathematical and statistical knowledge and understanding required to conduct basic data analysis.' through the context of 'Data Analytics with Python', using clear academic reasoning and practical examples.
Understanding: Gain the mathematical and statistical knowledge and understanding requ
By the end of this lesson, learners will be able to engage with 'Gain the mathematical and statistical knowledge and understanding required to conduct basic data analysis.' through the context of 'Data Analytics with Python', using clear academic reasoning and practical examples.
Understanding: Develop analytical and machine learning skills with Python.
By the end of this lesson, learners will be able to engage with 'Develop analytical and machine learning skills with Python.' through the context of 'Data Analytics with Python', using clear academic reasoning and practical examples.
Understanding: Develop a strong understanding of data and data processes, including d
By the end of this lesson, learners will be able to engage with 'Develop a strong understanding of data and data processes, including data cleaning, data structuring, and preparing data for analysis and visualisation.' through the context of 'Data Analytics with Python', using clear academic reasoning and practical examples.
Understanding: Understand the data science landscape and ecosystem, including relatio
By the end of this lesson, learners will be able to engage with 'Understand the data science landscape and ecosystem, including relational databases, graph databases, programming languages such as Python, visualisation tools, and other analytical tools.' through the context of 'Data Analytics with Python', using clear academic reasoning and practical examples.
Understanding: Understand the machine learning processes, understanding which algorit
By the end of this lesson, learners will be able to engage with 'Understand the machine learning processes, understanding which algorithms to apply to different problems, and the steps required build, test and verify a model.' through the context of 'Data Analytics with Python', using clear academic reasoning and practical examples.
Understanding: Develop an understanding of contemporary and emerging areas of data sc
By the end of this lesson, learners will be able to engage with 'Develop an understanding of contemporary and emerging areas of data science, and how they can be applied to modern challenges.' through the context of 'Data Analytics with Python', using clear academic reasoning and practical examples.
Applying: Gain the mathematical and statistical knowledge and understanding requ
By the end of this lesson, learners will be able to engage with 'Gain the mathematical and statistical knowledge and understanding required to conduct basic data analysis.' through the context of 'Data Analytics with Python', using clear academic reasoning and practical examples.
Applying: Develop analytical and machine learning skills with Python.
By the end of this lesson, learners will be able to engage with 'Develop analytical and machine learning skills with Python.' through the context of 'Data Analytics with Python', using clear academic reasoning and practical examples.
Applying: Develop a strong understanding of data and data processes, including d
By the end of this lesson, learners will be able to engage with 'Develop a strong understanding of data and data processes, including data cleaning, data structuring, and preparing data for analysis and visualisation.' through the context of 'Data Analytics with Python', using clear academic reasoning and practical examples.
Applying: Understand the data science landscape and ecosystem, including relatio
By the end of this lesson, learners will be able to engage with 'Understand the data science landscape and ecosystem, including relational databases, graph databases, programming languages such as Python, visualisation tools, and other analytical tools.' through the context of 'Data Analytics with Python', using clear academic reasoning and practical examples.
Applying: Understand the machine learning processes, understanding which algorit
By the end of this lesson, learners will be able to engage with 'Understand the machine learning processes, understanding which algorithms to apply to different problems, and the steps required build, test and verify a model.' through the context of 'Data Analytics with Python', using clear academic reasoning and practical examples.
Applying: Develop an understanding of contemporary and emerging areas of data sc
By the end of this lesson, learners will be able to engage with 'Develop an understanding of contemporary and emerging areas of data science, and how they can be applied to modern challenges.' through the context of 'Data Analytics with Python', using clear academic reasoning and practical examples.
Mastering: Gain the mathematical and statistical knowledge and understanding requ
By the end of this lesson, learners will be able to engage with 'Gain the mathematical and statistical knowledge and understanding required to conduct basic data analysis.' through the context of 'Data Analytics with Python', using clear academic reasoning and practical examples.
Mastering: Develop analytical and machine learning skills with Python.
By the end of this lesson, learners will be able to engage with 'Develop analytical and machine learning skills with Python.' through the context of 'Data Analytics with Python', using clear academic reasoning and practical examples.
Mastering: Develop a strong understanding of data and data processes, including d
By the end of this lesson, learners will be able to engage with 'Develop a strong understanding of data and data processes, including data cleaning, data structuring, and preparing data for analysis and visualisation.' through the context of 'Data Analytics with Python', using clear academic reasoning and practical examples.
Mastering: Understand the data science landscape and ecosystem, including relatio
By the end of this lesson, learners will be able to engage with 'Understand the data science landscape and ecosystem, including relational databases, graph databases, programming languages such as Python, visualisation tools, and other analytical tools.' through the context of 'Data Analytics with Python', using clear academic reasoning and practical examples.
Integrated Case Study for Data Analytics with Python
By the end of this lesson, learners will be able to engage with 'Gain the mathematical and statistical knowledge and understanding required to conduct basic data analysis.' through the context of 'Data Analytics with Python', using clear academic reasoning and practical examples.
Assessment Preparation and Evidence Building
By the end of this lesson, learners will be able to engage with 'Develop an understanding of contemporary and emerging areas of data science, and how they can be applied to modern challenges.' through the context of 'Data Analytics with Python', using clear academic reasoning and practical examples.
Final Mastery Review for Data Analytics with Python
By the end of this lesson, learners will be able to engage with 'Develop an understanding of contemporary and emerging areas of data science, and how they can be applied to modern challenges.' through the context of 'Data Analytics with Python', using clear academic reasoning and practical examples.