Developing skills and capability as a Data Scientist
Data Scientists perform statistical analysis and employ machine learning to extract insights from data. This requires higher mathematical or coding skills acquired through experience handling data or a degree or masters level education in data related subjects.
Here are some potential job roles you could pursue after completing this pathway:
A data Scientist performs statistical analysis and employs machine learning to extract insights from data. Responsibilities evolve from conducting basic statistical analyses and data wrangling to applying advanced machine learning algorithms and deep learning methods.
A senior data scientist analyses complex data, develops advanced machine learning models, and uses their findings to drive strategic business decisions. They are responsible for managing projects, mentoring junior staff, and communicating insights to stakeholders in a clear and understandable way.
A Lead Data Scientist defines the data science strategy, leads and mentors a team, and oversees complex projects from conception to delivery. They act as a technical leader, ensuring best practices, building relationships with stakeholders, and staying current with new AI and data science techniques to solve business problems and drive innovation.
A Chief Data Scientist leads an organisation's data science initiatives, which includes developing the data strategy, managing and mentoring a team of data scientists, and using data to solve business problems and drive strategy. They act as a bridge between technical data science teams and business stakeholders, ensuring data projects align with organizational goals and communicating complex findings to executives.
We make sure we provide our students with the most relevant, industry standard content, which is why this course is made up of material accredited by the following education leaders.
The leading global IT trade association, CompTIA, gives the industry a unified voice and real leadership in the IT community. As a non-profit organisation, CompTIA offers a unique range of training courses that validate your IT skills without restricting you to individual product suites.
Microsoft Azure, commonly referred to as Azure, is a cloud computing service created by Microsoft for building, testing, deploying, and managing applications and services through Microsoft-managed data centers.
Amazon Web Services is a subsidiary of Amazon providing on-demand cloud computing platforms and APIs to individuals, companies, and governments, on a metered pay-as-you-go basis.
The CompTIA DataX course and certification provides you with the essential skills to transform raw data into actionable business insights. By completing the course and passing the certification exam you'll learn to navigate various data environments, understand different data schemas, structures, and databases, both relational and non-relational.
Study time: 30 guided learning hours
1 x 165 minute exam, 90 questions.
The Microsoft Certified: Azure Data Scientist Associate course provides you with an overview of how to use Azure Machine Learning to build, train, and deploy machine learning models at scale. Throughout the course you'll cover essential skills for data preparation, model development, training, evaluation, and deployment using tools like the Python SDK, the Azure portal, and MLflow and be prepared to sit the official DP-100 examination.
Study time: 30 guided learning hours
1 x 100 minute exam, 40-60 questions.
The Microsoft Certified: Fabric Analytics Engineer Associate course provides you with the skills and knowledge to design, implement, and manage enterprise-scale data analytics solutions using Microsoft Fabric. The key skills that you'll cover throughout the course preparing you for the DP-600 examination include preparing and serving data, implementing and managing semantic models, and exploring and analysing data with tools like lakehouses, data warehouses, dataflows, pipelines, and notebooks.
Study time: 40 guided learning hours
1 x 100 minute exam, 40-60 questions.
The Microsoft Certified: Azure AI Fundamentals AI-900 certification serves as a valuable credential for individuals pursuing a career within the Microsoft Azure cloud ecosystem. As artificial intelligence becomes an integral component of modern cloud solutions, a solid understanding of AI principles and their practical application within Azure is increasingly essential for cloud professionals.
This certification provides a structured introduction to key AI concepts including machine learning, computer vision, natural language processing, and conversational AI, while emphasizing their implementation through Azure’s portfolio of AI services.
By developing this foundational knowledge, professionals are better prepared to design, evaluate, and support intelligent cloud-based solutions that align with organisational objectives.
Course modules:
Study time: 20 guided learning hours
Exam: 1 x 60 minute exam, featuring multiple choice questions
*content is made available once your first core pathway certification has been passed
(Please note the Microsoft Certified: Azure AI Fundamentals AI 900 retires on June 30 2026 being replaced by the updated Exam AI-901. The new AI-901 content is scheduled to be available in July 2026.)
Once you have worked through the core Data Science content in your pathway, you will find additional learning at the bottom of your playlist. This learning has been selected to enhance your knowledge and skills in data analytics.
Your pathway also includes our communications skills and critical thinking course. While technical skills are important, communication and critical thinking skills are often the distinguishing factor that sets successful businesses and professionals apart. They enable individuals to effectively navigate the complexities of the business world, build strong relationships, and drive innovation and growth.
